Datasets:

tensorfeed
/

ai-ecosystem-daily


1	+ {"site":"tensorfeed.ai","url":"https://tensorfeed.ai","vertical":"AI infrastructure & news","description":"Real-time AI news aggregator, model + pricing tracker, infra status monitor, and agent registry. Host of the first AFTA federation credit ledger.","adopted_at":"2026-04-30","manifest":"https://tensorfeed.ai/.well-known/agent-fair-trade.json","manifesto":"https://tensorfeed.ai/agent-fair-trade","receipt_key":"https://tensorfeed.ai/.well-known/tensorfeed-receipt-key.json","role":"host","notes":"Hosts the federated credit ledger; bearer tokens minted here are accepted by federation members."}
2	+ {"site":"terminalfeed.io","url":"https://terminalfeed.io","vertical":"Real-time data dashboards","description":"Live dashboards for finance, weather, transit, network status, and other real-time signals. Federation member sharing the host credit ledger.","adopted_at":"2026-04-30","manifest":"https://terminalfeed.io/.well-known/agent-fair-trade.json","manifesto":"https://terminalfeed.io/agent-fair-trade","receipt_key":"https://terminalfeed.io/.well-known/terminalfeed-receipt-key.json","role":"member","notes":"A bearer token minted on tensorfeed.ai works on terminalfeed.io with no re-auth."}

2026-05-24/agent-apis.jsonl ADDED Viewed

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+{"id":"tavily","name":"Tavily","vendor":"Tavily","category":"search","pricing":"1k searches/mo free; $30/mo Pro for 4k","freeTier":"1,000 searches/month","hasMCP":true,"capabilities":["web search","AI-optimized snippets","extraction"],"url":"https://tavily.com","notes":"Default agent search API. AI-optimized result snippets and full-page extraction in one call."}
+{"id":"brave-search-api","name":"Brave Search API","vendor":"Brave","category":"search","pricing":"2k queries/mo free; $3 per 1k after","freeTier":"2,000 queries/month","hasMCP":true,"capabilities":["web search","images","news"],"url":"https://brave.com/search/api/","notes":"Cheaper alternative to Google CSE. Independent index (not Bing/Google)."}
+{"id":"exa","name":"Exa","vendor":"Exa Labs","category":"search","pricing":"Pay-as-you-go from $10/mo; 1k free","freeTier":"1,000 searches","hasMCP":true,"capabilities":["neural search","similarity","content extraction"],"url":"https://exa.ai","notes":"Embedding-based semantic search. Better for \"find content like X\" queries than keyword search."}
+{"id":"serpapi","name":"SerpAPI","vendor":"SerpAPI","category":"search","pricing":"$50/mo for 5k searches","freeTier":"100 searches free trial","hasMCP":false,"capabilities":["Google SERP","Bing","YouTube","images"],"url":"https://serpapi.com","notes":"Scrapes real Google/Bing/etc result pages. Use when you need actual SERP HTML data not a curated index."}
+{"id":"bing-search","name":"Bing Search API","vendor":"Microsoft","category":"search","pricing":"$3 per 1k transactions","freeTier":"1k transactions/month","hasMCP":false,"capabilities":["web","images","news","videos"],"url":"https://www.microsoft.com/en-us/bing/apis/bing-web-search-api","notes":"Microsoft's search API. Scheduled to be retired August 2025; check current status before integrating."}
+{"id":"firecrawl","name":"Firecrawl","vendor":"Mendable","category":"web-scraping","pricing":"500 pages/mo free; $19/mo for 5k","freeTier":"500 pages/month","hasMCP":true,"capabilities":["scrape","crawl","JS rendering","structured extraction"],"url":"https://firecrawl.dev","notes":"Designed for AI agents. Returns clean markdown. Supports schema-based extraction (Pydantic / Zod)."}
+{"id":"jina-reader","name":"Jina Reader","vendor":"Jina AI","category":"web-scraping","pricing":"Free tier; usage-based after","freeTier":"20 RPM free","hasMCP":false,"capabilities":["URL to markdown","JS rendering","screenshot mode"],"url":"https://r.jina.ai","notes":"Free URL-to-markdown. Prepend r.jina.ai/ to any URL for instant agent-ready content. The simplest scraper to wire."}
+{"id":"apify","name":"Apify","vendor":"Apify","category":"web-scraping","pricing":"$5/mo platform credit free; pay per actor","freeTier":"$5 credit/month","hasMCP":true,"capabilities":["headless browser","4500+ pre-built actors","scheduled crawls"],"url":"https://apify.com","notes":"Marketplace of pre-built scrapers (\"actors\"). Best for scraping specific named sites without writing code."}
+{"id":"scrapingbee","name":"ScrapingBee","vendor":"ScrapingBee","category":"web-scraping","pricing":"$49/mo for 100k API calls","freeTier":"1,000 free credits","hasMCP":false,"capabilities":["proxy rotation","JS rendering","CAPTCHA solving"],"url":"https://www.scrapingbee.com","notes":"Proxy-rotating headless scraper. Good when target sites have anti-bot defenses."}
+{"id":"openweather","name":"OpenWeather","vendor":"OpenWeather","category":"weather","pricing":"Free tier; $40/mo for One Call","freeTier":"1k API calls/day, 60 calls/min","hasMCP":false,"capabilities":["current","forecast","historical","air quality"],"url":"https://openweathermap.org/api","notes":"Most-used weather API. 7-day forecast on free tier. 30-year historical on paid."}
+{"id":"noaa-nws","name":"NWS API","vendor":"NOAA / NWS","category":"weather","pricing":"Free","freeTier":"Unlimited (with rate limits)","hasMCP":false,"capabilities":["US-only forecasts","alerts","observations"],"url":"https://www.weather.gov/documentation/services-web-api","notes":"Free US government weather API. No API key required. US coverage only; for global use OpenWeather."}
+{"id":"tomorrow-io","name":"Tomorrow.io","vendor":"Tomorrow.io","category":"weather","pricing":"Free tier; usage-based after","freeTier":"500 requests/day","hasMCP":false,"capabilities":["hyperlocal forecast","hourly","60+ data fields"],"url":"https://www.tomorrow.io/weather-api/","notes":"Highest-resolution weather API. Useful for agents doing logistics, agriculture, or event planning."}
+{"id":"alpha-vantage","name":"Alpha Vantage","vendor":"Alpha Vantage","category":"finance","pricing":"Free tier (25 reqs/day); $50/mo for 75 reqs/min","freeTier":"25 requests/day","hasMCP":false,"capabilities":["stocks","forex","crypto","technical indicators","fundamental data"],"url":"https://www.alphavantage.co","notes":"Most-used free stock API. Generous free tier; rate limits tighten at scale."}
+{"id":"polygon","name":"Polygon.io","vendor":"Polygon.io","category":"finance","pricing":"$29/mo Starter; free tier limited","freeTier":"5 calls/min, EOD only","hasMCP":false,"capabilities":["real-time stocks","options","forex","crypto","WebSocket streams"],"url":"https://polygon.io","notes":"Production-grade real-time market data. WebSocket support is the main differentiator from Alpha Vantage."}
+{"id":"coingecko","name":"CoinGecko","vendor":"CoinGecko","category":"finance","pricing":"Free tier; $129/mo for Analyst","freeTier":"30 calls/min","hasMCP":false,"capabilities":["crypto prices","market cap","historical","NFTs","derivatives"],"url":"https://www.coingecko.com/en/api","notes":"The default crypto data API. 13,000+ coins. Free tier sufficient for most agent workflows."}
+{"id":"google-maps","name":"Google Maps Platform","vendor":"Google","category":"maps","pricing":"$200/mo credit; pay per request","freeTier":"$200 monthly credit","hasMCP":false,"capabilities":["geocoding","directions","places","distance matrix","street view"],"url":"https://mapsplatform.google.com","notes":"Most-used maps API. The credit covers most small-agent use cases. Places API is the killer feature."}
+{"id":"mapbox","name":"Mapbox","vendor":"Mapbox","category":"maps","pricing":"Free tier; pay-as-you-go","freeTier":"50k geocoding + 100k tile loads/mo","hasMCP":false,"capabilities":["geocoding","directions","static maps","tiles","isochrones"],"url":"https://www.mapbox.com","notes":"Generous free tier. Better visual customization than Google. The default for design-conscious mapping agents."}
+{"id":"osrm","name":"OSRM","vendor":"OSRM (open-source)","category":"maps","pricing":"Free (self-host)","freeTier":"Unlimited self-host","hasMCP":false,"capabilities":["routing","distance matrix","isochrones"],"url":"http://project-osrm.org","notes":"Open-source routing engine. Self-host for unlimited usage. Public demo server for testing only."}
+{"id":"resend","name":"Resend","vendor":"Resend","category":"email","pricing":"Free tier; $20/mo for 50k emails","freeTier":"3k emails/month, 100/day","hasMCP":false,"capabilities":["transactional email","React email templates","webhooks","audiences"],"url":"https://resend.com","notes":"Developer-first email API. React-based templates. The default for new SaaS agent stacks in 2025."}
+{"id":"postmark","name":"Postmark","vendor":"ActiveCampaign","category":"email","pricing":"$15/mo for 10k","freeTier":"100 emails/month","hasMCP":false,"capabilities":["transactional email","high deliverability","streams","webhooks"],"url":"https://postmarkapp.com","notes":"Best-in-class deliverability. Specialized for transactional only (no marketing)."}
+{"id":"twilio-sms","name":"Twilio SMS","vendor":"Twilio","category":"sms","pricing":"Pay-per-message; ~$0.0079 US SMS","freeTier":"Trial $15 credit","hasMCP":true,"capabilities":["SMS","MMS","WhatsApp","voice"],"url":"https://www.twilio.com/messaging","notes":"The most-used programmable messaging API. WhatsApp Business included. MCP server available."}
+{"id":"stripe","name":"Stripe","vendor":"Stripe","category":"payments","pricing":"2.9% + $0.30 per US card","freeTier":"No platform fee","hasMCP":true,"capabilities":["payments","subscriptions","invoicing","connect (multi-party)"],"url":"https://stripe.com","notes":"Default agent-to-human payments API. MCP server (Stripe Agent Toolkit) ships with restricted-key auth."}
+{"id":"lemon-squeezy","name":"Lemon Squeezy","vendor":"Lemon Squeezy","category":"payments","pricing":"5% + $0.50 per transaction","freeTier":"No setup fee","hasMCP":false,"capabilities":["merchant of record","EU VAT","subscriptions","license keys"],"url":"https://www.lemonsqueezy.com","notes":"Merchant of record (handles VAT/sales tax for you). Good fit for solo-dev agents selling internationally."}
+{"id":"e2b","name":"E2B","vendor":"E2B","category":"code-execution","pricing":"Pay-as-you-go from $0.000014/sec","freeTier":"$100 hobby credit","hasMCP":false,"capabilities":["secure sandboxes","Jupyter","long-running","Linux"],"url":"https://e2b.dev","notes":"Cloud sandboxes designed for AI code execution. Faster cold starts than Modal/Replicate for agentic workloads."}
+{"id":"modal","name":"Modal","vendor":"Modal Labs","category":"code-execution","pricing":"Pay-as-you-go; $30/mo free credit","freeTier":"$30 monthly compute credit","hasMCP":false,"capabilities":["serverless GPU + CPU","secrets","volumes","web endpoints"],"url":"https://modal.com","notes":"Serverless code execution including GPU. Good for agents that need to run heavy compute (training, inference) on demand."}
+{"id":"replit-agent","name":"Replit Agent","vendor":"Replit","category":"code-execution","pricing":"Bundled with Replit subscription","freeTier":"Free Replit account","hasMCP":false,"capabilities":["IDE-integrated execution","Linux containers","multi-language"],"url":"https://replit.com","notes":"Ephemeral execution sandboxes. Less precise than E2B for agent control but generous free tier."}
+{"id":"unstructured","name":"Unstructured","vendor":"Unstructured.io","category":"ocr","pricing":"Free open-source; Cloud from $0.01/page","freeTier":"Open-source library free","hasMCP":false,"capabilities":["PDF parsing","OCR","tables","images","60+ formats"],"url":"https://unstructured.io","notes":"The default RAG ingest pipeline. Open-source library handles most formats; Cloud tier for higher accuracy + scale."}
+{"id":"llamaparse","name":"LlamaParse","vendor":"LlamaIndex","category":"ocr","pricing":"$0.003/page (Premium); free tier","freeTier":"1k pages/day free","hasMCP":false,"capabilities":["PDF parsing","tables","figures","multimodal"],"url":"https://www.llamaindex.ai/llamaparse","notes":"GenAI-native PDF parser. Premium tier uses LLM for figure/chart understanding. Strong on financial docs."}
+{"id":"reducto","name":"Reducto","vendor":"Reducto","category":"ocr","pricing":"Custom; usage-based","freeTier":"Demo on website","hasMCP":false,"capabilities":["PDF parsing","forms","tables","high-accuracy OCR"],"url":"https://reducto.ai","notes":"Premium document parser. Highest accuracy on complex tables; targets enterprise RAG and compliance use cases."}

2026-05-24/agent-provisioning.jsonl ADDED Viewed

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+{"id":"cloudflare","name":"Cloudflare","vendor":"Cloudflare","category":"cdn-edge","status":"live","role":"Edge hosting, Workers, KV, domain registration, DNS, Pages","defaultMonthlyCap":100,"notes":"Co-author of the protocol. Account creation, domain registration, billing, and Workers deploy all expose the agent-friendly side of the API. The reference implementation.","url":"https://www.cloudflare.com"}
+{"id":"vercel","name":"Vercel","vendor":"Vercel","category":"hosting","status":"live","role":"Frontend hosting, serverless functions, Next.js platform","defaultMonthlyCap":100,"notes":"Launch partner. Vercel project creation and paid plan upgrade are both wired into Stripe Projects. Strongest Next.js + AI SDK story for agent-built apps.","url":"https://vercel.com"}
+{"id":"supabase","name":"Supabase","vendor":"Supabase","category":"database","status":"live","role":"Postgres database, auth, storage, realtime","defaultMonthlyCap":100,"notes":"Launch partner. Database provisioning, auth setup, and storage bucket creation are all agent-callable. Pairs well with Vercel for Next.js stacks.","url":"https://supabase.com"}
+{"id":"planetscale","name":"PlanetScale","vendor":"PlanetScale","category":"database","status":"live","role":"Serverless MySQL, branching, schema migrations","defaultMonthlyCap":100,"notes":"Launch partner. Database creation and branch-based migrations are agent-driveable. Strong for teams that prefer MySQL semantics.","url":"https://planetscale.com"}
+{"id":"clerk","name":"Clerk","vendor":"Clerk","category":"auth","status":"live","role":"Auth, sessions, user management, organizations","defaultMonthlyCap":100,"notes":"Launch partner. The only auth provider on the launch list. Application creation and configuration of OAuth providers are agent-callable.","url":"https://clerk.com"}
+{"id":"sentry","name":"Sentry","vendor":"Sentry","category":"observability","status":"live","role":"Error tracking, performance monitoring","defaultMonthlyCap":100,"notes":"Launch partner. Project creation and SDK key issuance are both API-driveable. Default for agent-built apps that want first-class error visibility.","url":"https://sentry.io"}
+{"id":"posthog","name":"PostHog","vendor":"PostHog","category":"observability","status":"live","role":"Product analytics, feature flags, session replay","defaultMonthlyCap":100,"notes":"Launch partner. Project creation, API key issuance, and feature flag setup are agent-driveable. Often paired with Sentry for full observability.","url":"https://posthog.com"}
+{"id":"inngest","name":"Inngest","vendor":"Inngest","category":"background-jobs","status":"live","role":"Durable workflows, background jobs, event-driven functions","defaultMonthlyCap":100,"notes":"Launch partner. The only background-jobs provider on the launch list. App creation and event/function registration are agent-driveable.","url":"https://www.inngest.com"}
+{"id":"huggingface","name":"Hugging Face","vendor":"Hugging Face","category":"ai-infrastructure","status":"live","role":"Model hosting, inference endpoints, Spaces, dataset hosting","defaultMonthlyCap":100,"notes":"Launch partner. Inference endpoint creation, Space deployment, and Pro upgrade are agent-driveable. The default open-model inference rail for agent-built apps.","url":"https://huggingface.co"}
+{"id":"neon","name":"Neon","vendor":"Neon","category":"database","status":"pending","role":"Serverless Postgres, branching, instant cold starts","defaultMonthlyCap":100,"notes":"Strong Postgres alternative to Supabase but not on the launch list as of 2026-05-03. Agents wiring database from scratch will route to Supabase or PlanetScale until Neon ships.","url":"https://neon.tech"}
+{"id":"turso","name":"Turso","vendor":"Turso","category":"database","status":"pending","role":"Edge SQLite (libSQL), per-user databases","defaultMonthlyCap":100,"notes":"Edge-first database story but no agent provisioning on launch day. Conspicuous absence given the Cloudflare-Vercel-Supabase axis the protocol formed around.","url":"https://turso.tech"}
+{"id":"auth0","name":"Auth0","vendor":"Okta","category":"auth","status":"pending","role":"Auth, SSO, identity-as-a-service","defaultMonthlyCap":100,"notes":"The largest auth provider in the market is not on the launch list. Clerk wins agent-driven sign-ups by default until Auth0 ships support.","url":"https://auth0.com"}
+{"id":"workos","name":"WorkOS","vendor":"WorkOS","category":"auth","status":"pending","role":"Enterprise SSO, SCIM, directory sync","defaultMonthlyCap":100,"notes":"Enterprise-tier auth provider; agent-driven onboarding is plausibly an enterprise blocker more than a tech blocker. Watch for a Q3 announcement.","url":"https://workos.com"}
+{"id":"stytch","name":"Stytch","vendor":"Stytch","category":"auth","status":"pending","role":"Auth, passwordless, biometrics, M2M","defaultMonthlyCap":100,"notes":"Developer-first auth with strong M2M primitives that should map cleanly to agents. Surprising not to see them on the launch list.","url":"https://stytch.com"}
+{"id":"netlify","name":"Netlify","vendor":"Netlify","category":"hosting","status":"pending","role":"Frontend hosting, serverless functions, edge functions","defaultMonthlyCap":100,"notes":"Vercel competitor not on the launch list. Agents picking a frontend host will pick Vercel by default until Netlify ships parity.","url":"https://www.netlify.com"}
+{"id":"fly","name":"Fly.io","vendor":"Fly.io","category":"hosting","status":"pending","role":"Global app hosting, full-VM workloads, multi-region","defaultMonthlyCap":100,"notes":"Strongest global-region story for non-Next.js workloads, but no agent provisioning on launch day. Likely a Q3 add given their developer-friendly orientation.","url":"https://fly.io"}
+{"id":"resend","name":"Resend","vendor":"Resend","category":"email","status":"unknown","role":"Transactional email, React-based templates","defaultMonthlyCap":100,"notes":"Article mentions 23 unnamed launch partners. Resend is the default agent-stack email provider; plausibly on the list. Status to be confirmed when Cloudflare publishes the full partner directory.","url":"https://resend.com"}
+{"id":"upstash","name":"Upstash","vendor":"Upstash","category":"database","status":"unknown","role":"Serverless Redis, Kafka, vector store","defaultMonthlyCap":100,"notes":"Edge-friendly key-value and vector store. Likely candidate for the unnamed launch partners list given the Cloudflare-Vercel co-marketing story.","url":"https://upstash.com"}

2026-05-24/agents-activity.jsonl ADDED Viewed

	@@ -0,0 +1,50 @@

+{"bot":"axios","endpoint":"/api/premium/routing","timestamp":"2026-05-24T09:50:03.292Z"}
+{"bot":"axios","endpoint":"/api/premium/routing","timestamp":"2026-05-24T09:44:59.009Z"}
+{"bot":"axios","endpoint":"/api/premium/news/search","timestamp":"2026-05-24T08:38:12.112Z"}
+{"bot":"axios","endpoint":"/api/premium/cost/projection","timestamp":"2026-05-24T08:38:12.274Z"}
+{"bot":"axios","endpoint":"/api/premium/whats-new","timestamp":"2026-05-24T08:38:12.440Z"}
+{"bot":"axios","endpoint":"/api/premium/compare/models","timestamp":"2026-05-24T08:38:12.606Z"}
+{"bot":"axios","endpoint":"/api/premium/providers/%7Bname%7D","timestamp":"2026-05-24T08:38:12.771Z"}
+{"bot":"axios","endpoint":"/api/premium/agents/directory","timestamp":"2026-05-24T08:38:12.935Z"}
+{"bot":"axios","endpoint":"/api/premium/history/pricing/series","timestamp":"2026-05-24T08:38:13.097Z"}
+{"bot":"axios","endpoint":"/api/premium/history/benchmarks/series","timestamp":"2026-05-24T08:38:13.263Z"}
+{"bot":"axios","endpoint":"/api/premium/history/status/uptime","timestamp":"2026-05-24T08:38:13.426Z"}
+{"bot":"axios","endpoint":"/api/premium/history/news/full","timestamp":"2026-05-24T08:38:13.589Z"}
+{"bot":"axios","endpoint":"/api/premium/history/news/source-health","timestamp":"2026-05-24T08:38:13.752Z"}
+{"bot":"axios","endpoint":"/api/premium/security/cve/range","timestamp":"2026-05-24T08:38:13.915Z"}
+{"bot":"axios","endpoint":"/api/premium/security/kev/full","timestamp":"2026-05-24T08:38:14.077Z"}
+{"bot":"axios","endpoint":"/api/premium/security/kev/series","timestamp":"2026-05-24T08:38:14.240Z"}
+{"bot":"axios","endpoint":"/api/premium/security/epss/series","timestamp":"2026-05-24T08:38:14.403Z"}
+{"bot":"axios","endpoint":"/api/premium/security/epss/top","timestamp":"2026-05-24T08:38:14.585Z"}
+{"bot":"axios","endpoint":"/api/premium/clean/cve/%7BCVE-id%7D","timestamp":"2026-05-24T08:38:14.747Z"}
+{"bot":"axios","endpoint":"/api/premium/clean/kev/%7BCVE-id%7D","timestamp":"2026-05-24T08:38:14.919Z"}
+{"bot":"axios","endpoint":"/api/premium/clean/epss/%7BCVE-id%7D","timestamp":"2026-05-24T08:38:15.083Z"}
+{"bot":"axios","endpoint":"/api/premium/clean/fda/%7Bcategory%7D","timestamp":"2026-05-24T08:38:15.246Z"}
+{"bot":"axios","endpoint":"/api/premium/history/news/clusters/full","timestamp":"2026-05-24T08:38:15.410Z"}
+{"bot":"axios","endpoint":"/api/premium/history/news/verified","timestamp":"2026-05-24T08:38:15.573Z"}
+{"bot":"axios","endpoint":"/api/premium/status/leaderboard","timestamp":"2026-05-24T08:38:15.737Z"}
+{"bot":"axios","endpoint":"/api/premium/probe/series","timestamp":"2026-05-24T08:38:16.015Z"}
+{"bot":"axios","endpoint":"/api/premium/attention/series","timestamp":"2026-05-24T08:38:16.180Z"}
+{"bot":"axios","endpoint":"/api/premium/policy/timeline","timestamp":"2026-05-24T08:38:16.343Z"}
+{"bot":"axios","endpoint":"/api/premium/economy/recession-watch","timestamp":"2026-05-24T08:38:16.507Z"}
+{"bot":"axios","endpoint":"/api/premium/economy/series/%7Bsource%7D/%7Bseries_id%7D","timestamp":"2026-05-24T08:38:16.669Z"}
+{"bot":"axios","endpoint":"/api/premium/research/velocity","timestamp":"2026-05-24T08:38:16.833Z"}
+{"bot":"axios","endpoint":"/api/premium/packages/pypi/momentum","timestamp":"2026-05-24T08:38:16.997Z"}
+{"bot":"axios","endpoint":"/api/premium/watches","timestamp":"2026-05-24T08:38:17.162Z"}
+{"bot":"axios","endpoint":"/api/premium/routing","timestamp":"2026-05-24T09:40:00.407Z"}
+{"bot":"axios","endpoint":"/api/premium/news/search","timestamp":"2026-05-24T09:25:26.201Z"}
+{"bot":"axios","endpoint":"/api/premium/cost/projection","timestamp":"2026-05-24T09:25:26.887Z"}
+{"bot":"axios","endpoint":"/api/premium/whats-new","timestamp":"2026-05-24T09:25:27.051Z"}
+{"bot":"axios","endpoint":"/api/premium/compare/models","timestamp":"2026-05-24T09:25:27.232Z"}
+{"bot":"axios","endpoint":"/api/premium/providers/%7Bname%7D","timestamp":"2026-05-24T09:25:27.396Z"}
+{"bot":"axios","endpoint":"/api/premium/agents/directory","timestamp":"2026-05-24T09:25:27.560Z"}
+{"bot":"axios","endpoint":"/api/premium/history/pricing/series","timestamp":"2026-05-24T09:25:28.387Z"}
+{"bot":"axios","endpoint":"/api/premium/history/benchmarks/series","timestamp":"2026-05-24T09:25:28.551Z"}
+{"bot":"axios","endpoint":"/api/premium/history/status/uptime","timestamp":"2026-05-24T09:25:28.713Z"}
+{"bot":"axios","endpoint":"/api/premium/history/news/full","timestamp":"2026-05-24T09:25:28.884Z"}
+{"bot":"axios","endpoint":"/api/premium/history/news/source-health","timestamp":"2026-05-24T09:25:29.047Z"}
+{"bot":"axios","endpoint":"/api/premium/security/cve/range","timestamp":"2026-05-24T09:25:29.209Z"}
+{"bot":"axios","endpoint":"/api/premium/security/kev/full","timestamp":"2026-05-24T09:25:29.375Z"}
+{"bot":"axios","endpoint":"/api/premium/security/kev/series","timestamp":"2026-05-24T09:25:30.033Z"}
+{"bot":"axios","endpoint":"/api/premium/security/epss/series","timestamp":"2026-05-24T09:25:30.197Z"}
+{"bot":"axios","endpoint":"/api/premium/security/epss/top","timestamp":"2026-05-24T09:25:30.359Z"}

2026-05-24/agents-directory.jsonl ADDED Viewed

	@@ -0,0 +1,18 @@

+{"id":"claude-code","name":"Claude Code","provider":"Anthropic","category":"coding","description":"An agentic CLI tool that lets Claude operate directly in your terminal, reading files, editing code, running commands, and managing git workflows autonomously.","url":"https://docs.anthropic.com/en/docs/claude-code","pricing":"Usage-based via Claude API","launched":2025}
+{"id":"cursor","name":"Cursor","provider":"Anysphere","category":"coding","description":"An AI-native code editor built on VS Code that provides inline code generation, multi-file editing, and codebase-aware chat powered by multiple foundation models.","url":"https://cursor.sh","pricing":"Free tier, Pro $20/mo, Business $40/mo","launched":2023}
+{"id":"github-copilot","name":"GitHub Copilot","provider":"GitHub / Microsoft","category":"coding","description":"An AI pair programmer integrated into popular editors that suggests code completions, generates functions from comments, and offers chat-based coding assistance.","url":"https://github.com/features/copilot","pricing":"Individual $10/mo, Business $19/mo, Enterprise $39/mo","launched":2022}
+{"id":"windsurf","name":"Windsurf","provider":"Codeium","category":"coding","description":"An AI-powered IDE that combines copilot and agent capabilities, allowing flows where the AI and developer collaborate on code changes across an entire project.","url":"https://codeium.com/windsurf","pricing":"Free tier, Pro $15/mo, Teams $30/mo","launched":2024}
+{"id":"perplexity","name":"Perplexity","provider":"Perplexity AI","category":"research","description":"An AI-powered answer engine that searches the web in real time, synthesizes information from multiple sources, and provides cited responses to complex questions.","url":"https://www.perplexity.ai","pricing":"Free tier, Pro $20/mo","launched":2022}
+{"id":"elicit","name":"Elicit","provider":"Elicit Inc.","category":"research","description":"A research assistant that helps find and analyze academic papers, extract key claims, and summarize findings across large bodies of scientific literature.","url":"https://elicit.com","pricing":"Free tier, Plus $10/mo, Enterprise custom","launched":2021}
+{"id":"consensus","name":"Consensus","provider":"Consensus NLP","category":"research","description":"A search engine that uses AI to find and synthesize results from peer-reviewed scientific research, providing evidence-based answers with citations.","url":"https://consensus.app","pricing":"Free tier, Premium $9.99/mo","launched":2022}
+{"id":"chatgpt","name":"ChatGPT","provider":"OpenAI","category":"general","description":"A general-purpose AI assistant that can handle conversation, writing, coding, analysis, and web browsing, with plugin and custom GPT support for specialized tasks.","url":"https://chat.openai.com","pricing":"Free tier, Plus $20/mo, Team $25/mo, Enterprise custom","launched":2022}
+{"id":"gemini","name":"Gemini","provider":"Google","category":"general","description":"Google's multimodal AI assistant with deep integration into Google Workspace, Search, and Android, capable of handling text, images, code, and long documents.","url":"https://gemini.google.com","pricing":"Free tier, Advanced $19.99/mo (included with Google One AI Premium)","launched":2023}
+{"id":"claude","name":"Claude","provider":"Anthropic","category":"general","description":"A helpful AI assistant known for nuanced instruction-following, long-context understanding, and careful reasoning across writing, analysis, coding, and research tasks.","url":"https://claude.ai","pricing":"Free tier, Pro $20/mo, Team $25/mo, Enterprise custom","launched":2023}
+{"id":"midjourney","name":"Midjourney","provider":"Midjourney Inc.","category":"creative","description":"A leading AI image generation tool that creates high-quality, artistic images from text prompts, known for its distinctive aesthetic style and photorealistic output.","url":"https://www.midjourney.com","pricing":"Basic $10/mo, Standard $30/mo, Pro $60/mo","launched":2022}
+{"id":"dall-e-3","name":"DALL-E 3","provider":"OpenAI","category":"creative","description":"OpenAI's image generation model integrated into ChatGPT and available via API, offering precise prompt adherence and the ability to render text within images.","url":"https://openai.com/dall-e-3","pricing":"Included with ChatGPT Plus, API usage-based","launched":2023}
+{"id":"suno","name":"Suno","provider":"Suno Inc.","category":"creative","description":"An AI music generation platform that creates full songs with vocals, instruments, and lyrics from text prompts or custom lyrics input.","url":"https://suno.com","pricing":"Free tier, Pro $10/mo, Premier $30/mo","launched":2023}
+{"id":"langchain","name":"LangChain","provider":"LangChain Inc.","category":"frameworks","description":"An open-source framework for building LLM-powered applications with chains, agents, retrieval-augmented generation, and memory, supporting multiple model providers.","url":"https://www.langchain.com","pricing":"Open source (LangSmith platform has paid tiers)","launched":2022}
+{"id":"crewai","name":"CrewAI","provider":"CrewAI Inc.","category":"frameworks","description":"A framework for orchestrating role-playing AI agents that collaborate on complex tasks, allowing developers to define agent roles, goals, and delegation patterns.","url":"https://www.crewai.com","pricing":"Open source, Enterprise cloud plans available","launched":2024}
+{"id":"autogen","name":"AutoGen","provider":"Microsoft","category":"frameworks","description":"An open-source framework for building multi-agent conversational systems where multiple AI agents can collaborate, debate, and coordinate to solve tasks.","url":"https://github.com/microsoft/autogen","pricing":"Open source","launched":2023}
+{"id":"openai-assistants","name":"OpenAI Assistants API","provider":"OpenAI","category":"frameworks","description":"A platform API for building AI assistants with persistent threads, file retrieval, code interpretation, and function calling built into OpenAI's hosted infrastructure.","url":"https://platform.openai.com/docs/assistants","pricing":"Usage-based via OpenAI API","launched":2023}
+{"id":"claude-mcp","name":"Model Context Protocol (MCP)","provider":"Anthropic","category":"frameworks","description":"An open protocol that standardizes how AI applications connect to external data sources and tools, enabling plug-and-play integrations for any MCP-compatible client.","url":"https://modelcontextprotocol.io","pricing":"Open source protocol","launched":2024}

2026-05-24/ai-hardware.jsonl ADDED Viewed

	@@ -0,0 +1,17 @@

+{"id":"gb200","name":"NVIDIA GB200 (Blackwell)","manufacturer":"NVIDIA","family":"Blackwell","process":"TSMC 4NP","released":"2025","memoryGB":384,"memoryBandwidthTBs":16,"fp16TFLOPS":5000,"fp8TFLOPS":10000,"fp4TFLOPS":20000,"tdpWatts":2700,"interconnect":"NVLink 5 (1.8 TB/s) + Grace CPU C2C (900 GB/s)","listPriceUSD":null,"availability":"Cloud only (CoreWeave, AWS, Azure, GCP, Oracle, Lambda)","notes":"Blackwell flagship: dual B200 + Grace CPU. FP4 native. The chip every major lab is buying for 2025-2026 frontier training.","url":"https://www.nvidia.com/en-us/data-center/gb200-nvl72/"}
+{"id":"b200","name":"NVIDIA B200","manufacturer":"NVIDIA","family":"Blackwell","process":"TSMC 4NP","released":"2025","memoryGB":192,"memoryBandwidthTBs":8,"fp16TFLOPS":2500,"fp8TFLOPS":5000,"fp4TFLOPS":10000,"tdpWatts":1000,"interconnect":"NVLink 5 (1.8 TB/s)","listPriceUSD":null,"availability":"Cloud only","notes":"Single-die Blackwell. 192GB HBM3e (largest in the catalog at single-die). Inference workhorse for serving 100B+ MoE models on a single GPU.","url":"https://www.nvidia.com/en-us/data-center/blackwell-architecture/"}
+{"id":"h200","name":"NVIDIA H200","manufacturer":"NVIDIA","family":"Hopper","process":"TSMC 4N","released":"2024","memoryGB":141,"memoryBandwidthTBs":4.8,"fp16TFLOPS":989,"fp8TFLOPS":1979,"fp4TFLOPS":null,"tdpWatts":700,"interconnect":"NVLink 4 (900 GB/s)","listPriceUSD":null,"availability":"Cloud and direct sale","notes":"Hopper refresh with HBM3e. The sweet spot for production inference in 2025. Extra memory means 70B-class models fit single-GPU at FP8.","url":"https://www.nvidia.com/en-us/data-center/h200/"}
+{"id":"h100","name":"NVIDIA H100","manufacturer":"NVIDIA","family":"Hopper","process":"TSMC 4N","released":"2022","memoryGB":80,"memoryBandwidthTBs":3.35,"fp16TFLOPS":989,"fp8TFLOPS":1979,"fp4TFLOPS":null,"tdpWatts":700,"interconnect":"NVLink 4 (900 GB/s)","listPriceUSD":30000,"availability":"Cloud and direct sale (~$30k retail, declining)","notes":"The chip that built the 2023-2024 LLM boom. Still the most-deployed AI GPU. FP8 native. 80GB HBM3.","url":"https://www.nvidia.com/en-us/data-center/h100/"}
+{"id":"a100","name":"NVIDIA A100 80GB","manufacturer":"NVIDIA","family":"Ampere","process":"TSMC 7nm","released":"2020","memoryGB":80,"memoryBandwidthTBs":2,"fp16TFLOPS":312,"fp8TFLOPS":null,"fp4TFLOPS":null,"tdpWatts":400,"interconnect":"NVLink 3 (600 GB/s)","listPriceUSD":18000,"availability":"Cloud and used market (~$18k retail, declining)","notes":"Workhorse of the late-2010s ML wave. Still widely used for training smaller models and inference where H100/H200 supply is tight.","url":"https://www.nvidia.com/en-us/data-center/a100/"}
+{"id":"rtx-pro-6000-blackwell","name":"NVIDIA RTX PRO 6000 Blackwell","manufacturer":"NVIDIA","family":"Blackwell","process":"TSMC 4NP","released":"2025","memoryGB":96,"memoryBandwidthTBs":1.79,"fp16TFLOPS":360,"fp8TFLOPS":720,"fp4TFLOPS":1440,"tdpWatts":600,"interconnect":"PCIe 5.0","listPriceUSD":8500,"availability":"Direct sale (workstation card)","notes":"Workstation Blackwell. 96GB GDDR7. Good fit for on-prem agent dev environments where multi-H100 rentals are overkill.","url":"https://www.nvidia.com/en-us/products/workstations/professional-desktop-gpus/rtx-pro-6000-blackwell/"}
+{"id":"rtx-4090","name":"NVIDIA RTX 4090","manufacturer":"NVIDIA","family":"Ada Lovelace","process":"TSMC 4N","released":"2022","memoryGB":24,"memoryBandwidthTBs":1.01,"fp16TFLOPS":165,"fp8TFLOPS":660,"fp4TFLOPS":null,"tdpWatts":450,"interconnect":"PCIe 4.0","listPriceUSD":1600,"availability":"Consumer retail","notes":"Best price/perf for local agent dev. 24GB VRAM fits Q4-quantized 70B models. The default consumer-tier choice for self-hosted Ollama/llama.cpp.","url":"https://www.nvidia.com/en-us/geforce/graphics-cards/40-series/rtx-4090/"}
+{"id":"rtx-5090","name":"NVIDIA RTX 5090","manufacturer":"NVIDIA","family":"Blackwell","process":"TSMC 4NP","released":"2025","memoryGB":32,"memoryBandwidthTBs":1.79,"fp16TFLOPS":209,"fp8TFLOPS":838,"fp4TFLOPS":3352,"tdpWatts":575,"interconnect":"PCIe 5.0","listPriceUSD":2000,"availability":"Consumer retail","notes":"Consumer Blackwell flagship. 32GB GDDR7. FP4 native. Strong pick for local agent dev with current-frontier features.","url":"https://www.nvidia.com/en-us/geforce/graphics-cards/50-series/rtx-5090/"}
+{"id":"mi325x","name":"AMD MI325X","manufacturer":"AMD","family":"Instinct","process":"TSMC N5 / N6","released":"2024-Q4","memoryGB":256,"memoryBandwidthTBs":6,"fp16TFLOPS":1300,"fp8TFLOPS":2600,"fp4TFLOPS":null,"tdpWatts":1000,"interconnect":"Infinity Fabric (8x 153 GB/s)","listPriceUSD":null,"availability":"Cloud (Microsoft Azure, Oracle), direct sale","notes":"AMD's answer to H200. 256GB HBM3e (highest in the catalog at single-die). Strong inference value when supply is constrained on NVIDIA.","url":"https://www.amd.com/en/products/accelerators/instinct/mi300/mi325x.html"}
+{"id":"mi300x","name":"AMD MI300X","manufacturer":"AMD","family":"Instinct","process":"TSMC N5 / N6","released":"2023-Q4","memoryGB":192,"memoryBandwidthTBs":5.3,"fp16TFLOPS":1300,"fp8TFLOPS":2600,"fp4TFLOPS":null,"tdpWatts":750,"interconnect":"Infinity Fabric","listPriceUSD":15000,"availability":"Cloud (Vultr, RunPod, Microsoft Azure), direct sale (~$15k)","notes":"Wider availability than NVIDIA flagship; cheaper to rent. ROCm software stack matures; vLLM and PyTorch first-class on MI300X in 2026.","url":"https://www.amd.com/en/products/accelerators/instinct/mi300/mi300x.html"}
+{"id":"tpu-v5p","name":"Google TPU v5p","manufacturer":"Google","family":"TPU","process":"TSMC 3nm","released":"2023-12","memoryGB":95,"memoryBandwidthTBs":2.77,"fp16TFLOPS":459,"fp8TFLOPS":918,"fp4TFLOPS":null,"tdpWatts":700,"interconnect":"ICI (Inter-Chip Interconnect, 4.8 Tb/s per chip)","listPriceUSD":null,"availability":"Google Cloud only (Vertex AI, GCE)","notes":"Google's top training TPU. Used for Gemini training. Only available on GCP; pod-scale (8960 chips) is a different beast than per-chip rentals.","url":"https://cloud.google.com/tpu/docs/v5p"}
+{"id":"tpu-v5e","name":"Google TPU v5e","manufacturer":"Google","family":"TPU","process":"TSMC 5nm","released":"2023-08","memoryGB":16,"memoryBandwidthTBs":0.82,"fp16TFLOPS":197,"fp8TFLOPS":394,"fp4TFLOPS":null,"tdpWatts":170,"interconnect":"ICI","listPriceUSD":null,"availability":"Google Cloud only","notes":"TPU inference tier. Cheaper than v5p; 256-chip pods. Best fit for Google Cloud customers serving Gemini-style inference at scale.","url":"https://cloud.google.com/tpu/docs/v5e"}
+{"id":"trainium-2","name":"AWS Trainium 2","manufacturer":"AWS","family":"Trainium","process":"TSMC 5nm","released":"2024-12","memoryGB":96,"memoryBandwidthTBs":2.9,"fp16TFLOPS":1300,"fp8TFLOPS":2600,"fp4TFLOPS":null,"tdpWatts":500,"interconnect":"NeuronLink (3 TB/s per chip)","listPriceUSD":null,"availability":"AWS only (Trn2 instances)","notes":"AWS custom training/inference silicon. Anthropic uses these for Claude training. Cheaper TCO on AWS than NVIDIA flagship for committed workloads.","url":"https://aws.amazon.com/ai/machine-learning/trainium/"}
+{"id":"inferentia-2","name":"AWS Inferentia 2","manufacturer":"AWS","family":"Inferentia","process":"TSMC 5nm","released":"2023-04","memoryGB":32,"memoryBandwidthTBs":0.82,"fp16TFLOPS":190,"fp8TFLOPS":null,"fp4TFLOPS":null,"tdpWatts":null,"interconnect":"NeuronLink","listPriceUSD":null,"availability":"AWS only (Inf2 instances)","notes":"AWS inference silicon. Lower compute than Trainium 2 but cheaper per-token for high-volume serving workloads on AWS.","url":"https://aws.amazon.com/ai/machine-learning/inferentia/"}
+{"id":"apple-m4-max","name":"Apple M4 Max","manufacturer":"Apple","family":"Apple Silicon","process":"TSMC 3nm","released":"2024-10","memoryGB":128,"memoryBandwidthTBs":0.546,"fp16TFLOPS":38,"fp8TFLOPS":null,"fp4TFLOPS":null,"tdpWatts":60,"interconnect":"On-die (unified memory)","listPriceUSD":4699,"availability":"Consumer retail (MacBook Pro / Studio)","notes":"128GB unified memory means a Mac Studio runs 70B-class models at Q4 quantization with usable speed. The dark-horse local-inference platform.","url":"https://www.apple.com/shop/buy-mac/mac-studio"}
+{"id":"cerebras-wse-3","name":"Cerebras WSE-3","manufacturer":"Cerebras","family":"WSE","process":"TSMC 5nm","released":"2024","memoryGB":44,"memoryBandwidthTBs":21,"fp16TFLOPS":125000,"fp8TFLOPS":null,"fp4TFLOPS":null,"tdpWatts":23000,"interconnect":"On-wafer (no interconnect needed)","listPriceUSD":null,"availability":"Cerebras Cloud only","notes":"Single 46,225 mm^2 wafer. Holds entire activations on-chip; eliminates many distributed-training pains. Fastest inference for sub-100B models in production.","url":"https://cerebras.ai/product-chip/"}
+{"id":"groq-lpu","name":"Groq LPU","manufacturer":"Groq","family":"LPU","process":"GlobalFoundries 14nm (gen 1)","released":"2023","memoryGB":0.23,"memoryBandwidthTBs":80,"fp16TFLOPS":188,"fp8TFLOPS":null,"fp4TFLOPS":null,"tdpWatts":350,"interconnect":"GroqLink","listPriceUSD":null,"availability":"Groq Cloud only","notes":"Deterministic single-thread inference silicon. SRAM-only memory model means small per-chip capacity but massive bandwidth. Behind Groq's 700+ tokens/sec Llama 4 Scout serving.","url":"https://groq.com/lpu-language-processing-unit/"}

2026-05-24/ai-lawsuits.jsonl ADDED Viewed

	@@ -0,0 +1,19 @@

+{"id":"nyt-v-openai","name":"The New York Times Co. v. Microsoft Corp. & OpenAI","plaintiff":"The New York Times Company","defendants":["Microsoft Corporation","OpenAI, Inc.","OpenAI LP","OpenAI GP"],"jurisdiction":"US (S.D.N.Y.)","court":"United States District Court for the Southern District of New York","caseNumber":"1:23-cv-11195","filed":"2023-12-27","status":"active","stage":"discovery","claims":["copyright-infringement","dmca-violation","unfair-competition"],"summary":"NYT alleges OpenAI and Microsoft trained GPT-class models on millions of NYT articles without license and that ChatGPT outputs reproduce articles verbatim. Most-cited AI training-data case; partial motion-to-dismiss granted in 2025-04 on some claims, copyright claims survived.","sources":["https://www.courtlistener.com/docket/68117049/the-new-york-times-company-v-microsoft-corporation/","https://www.nytimes.com/2023/12/27/business/media/new-york-times-open-ai-microsoft-lawsuit.html"]}
+{"id":"daily-news-v-openai","name":"Daily News, LP et al. v. Microsoft Corp. & OpenAI","plaintiff":"Daily News LP, Chicago Tribune, Denver Post, Orlando Sentinel, Sun Sentinel, San Jose Mercury News, Orange County Register, St. Paul Pioneer Press (eight Alden Global Capital papers)","defendants":["Microsoft Corporation","OpenAI, Inc.","OpenAI subsidiaries"],"jurisdiction":"US (S.D.N.Y.)","court":"United States District Court for the Southern District of New York","caseNumber":"1:24-cv-03285","filed":"2024-04-30","status":"consolidated","stage":"discovery","claims":["copyright-infringement","dmca-violation"],"summary":"Eight US newspapers owned by Alden Global Capital consolidated their suits with NYT v OpenAI alleging the same training-data harvesting pattern. Procedural consolidation under the NYT case for discovery.","sources":["https://www.alden.global","https://www.theverge.com/2024/4/30/24145402/alden-global-newspapers-openai-microsoft-lawsuit-copyright"]}
+{"id":"cir-v-openai","name":"Center for Investigative Reporting v. OpenAI & Microsoft","plaintiff":"Center for Investigative Reporting (Mother Jones, Reveal)","defendants":["OpenAI, Inc.","Microsoft Corporation"],"jurisdiction":"US (S.D.N.Y.)","court":"United States District Court for the Southern District of New York","caseNumber":"1:24-cv-04872","filed":"2024-06-27","status":"active","stage":"discovery","claims":["copyright-infringement","dmca-violation"],"summary":"Investigative-journalism nonprofit alleges OpenAI scraped CIR's reporting from Mother Jones and Reveal for training, and that ChatGPT regurgitates articles without attribution.","sources":["https://revealnews.org/article/center-for-investigative-reporting-sues-openai-microsoft/"]}
+{"id":"raw-story-v-openai","name":"Raw Story Media v. OpenAI","plaintiff":"Raw Story Media; AlterNet Media","defendants":["OpenAI, Inc."],"jurisdiction":"US (S.D.N.Y.)","court":"United States District Court for the Southern District of New York","caseNumber":"1:24-cv-01514","filed":"2024-02-28","status":"dismissed","stage":"closed","claims":["dmca-violation"],"summary":"DMCA-only theory (CMI removal) without a copyright claim. Dismissed for lack of standing 2024-11; plaintiffs filed an amended complaint.","sources":["https://www.reuters.com/legal/litigation/openai-defeats-news-outlets-copyright-lawsuit-over-ai-training-data-2024-11-08/"]}
+{"id":"newscorp-v-perplexity","name":"Dow Jones & NYP Holdings v. Perplexity AI","plaintiff":"Dow Jones & Company; NYP Holdings (News Corp)","defendants":["Perplexity AI, Inc."],"jurisdiction":"US (S.D.N.Y.)","court":"United States District Court for the Southern District of New York","caseNumber":"1:24-cv-07984","filed":"2024-10-21","status":"active","stage":"motion-to-dismiss","claims":["copyright-infringement","unfair-competition","trademark-infringement"],"summary":"WSJ and NY Post owners allege Perplexity's answer engine copies and republishes their reporting verbatim and falsely attributes its summaries. First major lawsuit specifically targeting an AI search-and-summarize product, distinct from the model-training cases.","sources":["https://www.wsj.com/business/media/news-corp-sues-perplexity-ai-claiming-massive-illegal-copying-of-articles-c30b3eb6"]}
+{"id":"authors-guild-v-openai","name":"Authors Guild et al. v. OpenAI (consolidated)","plaintiff":"Authors Guild, John Grisham, George R.R. Martin, Jodi Picoult, David Baldacci, Michael Connelly, others","defendants":["OpenAI, Inc.","Microsoft Corporation"],"jurisdiction":"US (S.D.N.Y.)","court":"United States District Court for the Southern District of New York","caseNumber":"1:23-cv-08292","filed":"2023-09-19","status":"consolidated","stage":"discovery","claims":["copyright-infringement"],"summary":"Class action by 17 named novelists plus the Authors Guild alleging OpenAI trained on copyrighted novels via Books2/Books3 and similar shadow-library corpora. Consolidated with related novelist suits (Tremblay, Silverman, Chabon) under MDL coordination.","sources":["https://authorsguild.org/news/ag-and-authors-file-class-action-suit-against-openai/","https://www.courtlistener.com/docket/67810111/authors-guild-v-openai-inc/"]}
+{"id":"silverman-v-openai","name":"Silverman v. OpenAI","plaintiff":"Sarah Silverman, Christopher Golden, Richard Kadrey","defendants":["OpenAI, Inc."],"jurisdiction":"US (N.D. Cal.)","court":"United States District Court for the Northern District of California","caseNumber":"3:23-cv-03416","filed":"2023-07-07","status":"consolidated","stage":"discovery","claims":["copyright-infringement","dmca-violation","unjust-enrichment"],"summary":"Author class action alleging training on copyrighted books from shadow libraries (Books3 / LibGen). Most secondary claims (DMCA, negligence, unjust enrichment) dismissed 2024-02; copyright claims survived and entered consolidated discovery.","sources":["https://www.courtlistener.com/docket/67569326/tremblay-v-openai-inc/","https://www.theverge.com/2023/7/9/23788741/sarah-silverman-openai-meta-chatgpt-llama-copyright-infringement-chatbots-artificial-intelligence-ai"]}
+{"id":"kadrey-v-meta","name":"Kadrey v. Meta Platforms (Llama)","plaintiff":"Richard Kadrey, Sarah Silverman, Christopher Golden","defendants":["Meta Platforms, Inc."],"jurisdiction":"US (N.D. Cal.)","court":"United States District Court for the Northern District of California","caseNumber":"3:23-cv-03417","filed":"2023-07-07","status":"active","stage":"summary-judgment","claims":["copyright-infringement"],"summary":"Same plaintiff group, parallel claim against Meta over Llama training on Books3. Discovery surfaced internal Meta communications discussing the use of pirated book corpora; partial summary judgment briefing in 2025.","sources":["https://www.courtlistener.com/docket/67569329/kadrey-v-meta-platforms-inc/","https://arstechnica.com/tech-policy/2025/01/meta-staff-discussed-using-pirated-books-to-train-ai-court-filings-show/"]}
+{"id":"doe-v-github","name":"Doe et al. v. GitHub, OpenAI, Microsoft (Copilot)","plaintiff":"Anonymous open-source developers","defendants":["GitHub, Inc.","Microsoft Corporation","OpenAI, Inc."],"jurisdiction":"US (N.D. Cal.)","court":"United States District Court for the Northern District of California","caseNumber":"4:22-cv-06823","filed":"2022-11-03","status":"active","stage":"discovery","claims":["dmca-violation","breach-of-contract","unfair-competition","unjust-enrichment"],"summary":"Putative class action by open-source developers alleging GitHub Copilot reproduces their code without honoring open-source license attribution requirements. Most copyright claims dismissed 2023-2024; DMCA and breach-of-license claims survived to discovery.","sources":["https://githubcopilotlitigation.com","https://www.courtlistener.com/docket/63992594/doe-v-github-inc/"]}
+{"id":"andersen-v-stability","name":"Andersen v. Stability AI, Midjourney, DeviantArt, Runway","plaintiff":"Sarah Andersen, Kelly McKernan, Karla Ortiz, others (artist class)","defendants":["Stability AI Ltd.","Stability AI, Inc.","Midjourney, Inc.","DeviantArt, Inc.","Runway AI, Inc."],"jurisdiction":"US (N.D. Cal.)","court":"United States District Court for the Northern District of California","caseNumber":"3:23-cv-00201","filed":"2023-01-13","status":"active","stage":"discovery","claims":["copyright-infringement","dmca-violation","right-of-publicity","unfair-competition"],"summary":"First major class action by visual artists alleging diffusion-model training on LAION-scraped artwork without license. Amended complaint in 2023-11 added Runway and Midjourney; key copyright claims survived motion-to-dismiss in 2024-08.","sources":["https://www.courtlistener.com/docket/66735377/andersen-v-stability-ai-ltd/","https://www.theverge.com/2024/8/13/24220231/stability-midjourney-deviantart-runway-andersen-copyright-class-action-allowed-proceed"]}
+{"id":"getty-v-stability-us","name":"Getty Images (US) v. Stability AI","plaintiff":"Getty Images (US), Inc.","defendants":["Stability AI, Inc.","Stability AI Ltd."],"jurisdiction":"US (D. Del.)","court":"United States District Court for the District of Delaware","caseNumber":"1:23-cv-00135","filed":"2023-02-03","status":"active","stage":"discovery","claims":["copyright-infringement","trademark-infringement","unfair-competition"],"summary":"Getty alleges Stable Diffusion was trained on millions of Getty-watermarked images and reproduces the Getty watermark in some generations. The watermark issue is rare among training-data cases because it provides direct evidence of the training corpus contents.","sources":["https://newsroom.gettyimages.com/en/getty-images/getty-images-statement","https://www.courtlistener.com/docket/66878049/getty-images-us-inc-v-stability-ai-inc/"]}
+{"id":"getty-v-stability-uk","name":"Getty Images (UK) v. Stability AI Ltd.","plaintiff":"Getty Images (US), Inc.; Getty Images International (UK)","defendants":["Stability AI Ltd."],"jurisdiction":"UK (England and Wales)","court":"High Court of Justice, Business and Property Courts of England and Wales","caseNumber":"IL-2023-000007","filed":"2023-01","status":"active","stage":"trial","claims":["copyright-infringement","trademark-infringement"],"summary":"Parallel UK proceeding to the Delaware case. UK trial reached merits in 2025 with closer scrutiny of where training actually occurred (UK courts apply territorial limits to copyright). One of the first AI training cases to reach trial in any jurisdiction.","sources":["https://www.judiciary.uk/judgments/getty-images-v-stability-ai/"]}
+{"id":"concord-v-anthropic","name":"Concord Music Group v. Anthropic","plaintiff":"Concord Music Group, Universal Music Publishing Group, ABKCO","defendants":["Anthropic PBC"],"jurisdiction":"US (M.D. Tenn.)","court":"United States District Court for the Middle District of Tennessee","caseNumber":"3:23-cv-01092","filed":"2023-10-18","status":"active","stage":"discovery","claims":["copyright-infringement","dmca-violation","unfair-competition"],"summary":"Music publishers allege Claude was trained on copyrighted song lyrics and outputs them verbatim on request. Anthropic implemented output filters in 2024 in response; preliminary injunction denied 2024-03 on a narrow set of claims, case continues on the broader theory.","sources":["https://www.courtlistener.com/docket/67862254/concord-music-group-inc-v-anthropic-pbc/","https://www.billboard.com/business/legal/anthropic-claude-ai-music-publishers-lyrics-lawsuit-1235427547/"]}
+{"id":"riaa-v-suno","name":"RIAA v. Suno","plaintiff":"UMG Recordings, Sony Music Entertainment, Warner Records (RIAA member labels)","defendants":["Suno, Inc."],"jurisdiction":"US (D. Mass.)","court":"United States District Court for the District of Massachusetts","caseNumber":"1:24-cv-11611","filed":"2024-06-24","status":"active","stage":"discovery","claims":["copyright-infringement"],"summary":"Major labels allege Suno trained its music-generation model on copyrighted recordings, with outputs that closely replicate the style and in some cases the melodic content of named tracks. Companion case RIAA v. Udio filed same day in S.D.N.Y.","sources":["https://www.riaa.com/wp-content/uploads/2024/06/UMG-Recordings-et-al-v-Suno-Inc-et-al-Complaint.pdf"]}
+{"id":"riaa-v-udio","name":"RIAA v. Udio (Uncharted Labs)","plaintiff":"UMG Recordings, Sony Music Entertainment, Warner Records (RIAA member labels)","defendants":["Uncharted Labs, Inc. (d/b/a Udio)"],"jurisdiction":"US (S.D.N.Y.)","court":"United States District Court for the Southern District of New York","caseNumber":"1:24-cv-04777","filed":"2024-06-24","status":"active","stage":"discovery","claims":["copyright-infringement"],"summary":"Companion case to RIAA v Suno, same theory against Udio. Filed same day. Both cases consolidated in their respective districts for procedural efficiency.","sources":["https://www.riaa.com/wp-content/uploads/2024/06/Sony-Music-et-al-v-Uncharted-Labs-dba-Udio-Complaint.pdf"]}
+{"id":"lehrman-v-lovo","name":"Lehrman v. Lovo","plaintiff":"Paul Skye Lehrman, Linnea Sage (voice actors)","defendants":["Lovo, Inc."],"jurisdiction":"US (S.D.N.Y.)","court":"United States District Court for the Southern District of New York","caseNumber":"1:24-cv-03770","filed":"2024-05-16","status":"active","stage":"discovery","claims":["copyright-infringement","right-of-publicity","unfair-competition"],"summary":"Voice actors allege their voices were cloned and offered as TTS products on Lovo without consent. Test case for AI voice cloning and right-of-publicity in the federal courts.","sources":["https://www.nytimes.com/2024/05/16/technology/lovo-ai-voice-actors-lawsuit.html"]}
+{"id":"ftc-openai-microsoft-inquiry","name":"FTC inquiry: AI partnerships and investments","plaintiff":"US Federal Trade Commission (Section 6(b) inquiry)","defendants":["Microsoft","Alphabet","Amazon","OpenAI","Anthropic"],"jurisdiction":"US (federal regulatory)","court":"Federal Trade Commission","caseNumber":"FTC Inquiry P246201","filed":"2024-01-25","status":"active","stage":"discovery","claims":["antitrust","regulatory-investigation"],"summary":"FTC ordered Microsoft, Alphabet, Amazon, OpenAI, and Anthropic to submit details of generative-AI investments and partnerships, focused on whether large-cloud-provider stakes in frontier labs distort competition. Staff report issued 2025-01.","sources":["https://www.ftc.gov/news-events/news/press-releases/2024/01/ftc-launches-inquiry-generative-ai-investments-partnerships"]}
+{"id":"eu-microsoft-openai-review","name":"EU Commission review: Microsoft / OpenAI partnership","plaintiff":"European Commission (Directorate-General for Competition)","defendants":["Microsoft Corporation","OpenAI"],"jurisdiction":"EU","court":"European Commission","caseNumber":"M.11766","filed":"2024-01","status":"active","stage":"discovery","claims":["antitrust","regulatory-investigation"],"summary":"EU competition authorities reviewing whether Microsoft's investment in and integration with OpenAI amounts to a notifiable concentration under the EU Merger Regulation. As of late 2024 EC concluded no de jure control by Microsoft, but informal market inquiries continue.","sources":["https://ec.europa.eu/competition/mergers/cases1/202404/M_11766_11254399_25_3.pdf"]}
+{"id":"garcia-v-character-ai","name":"Garcia v. Character Technologies","plaintiff":"Megan Garcia (estate of Sewell Setzer III)","defendants":["Character Technologies, Inc.","Google LLC","Alphabet Inc."],"jurisdiction":"US (M.D. Fla.)","court":"United States District Court for the Middle District of Florida","caseNumber":"6:24-cv-01903","filed":"2024-10-22","status":"active","stage":"motion-to-dismiss","claims":["tort","consumer-protection","unfair-competition"],"summary":"Wrongful-death and product-liability suit alleging Character.AI's chatbot contributed to a 14-year-old's suicide. First high-profile product-liability test for a consumer LLM chatbot.","sources":["https://www.nytimes.com/2024/10/23/technology/characterai-lawsuit-teen-suicide.html"]}

2026-05-24/ai-policy.jsonl ADDED Viewed

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+{"id":"eu-ai-act","name":"EU AI Act","jurisdiction":"European Union","status":"active","type":"regulation","enactedDate":"2024-08-01","milestones":[{"date":"2024-08-01","event":"Entered into force"},{"date":"2025-02-02","event":"Prohibited practices banned (social scoring, manipulation, untargeted scraping)"},{"date":"2025-08-02","event":"GPAI / foundation-model obligations active (transparency, copyright, model cards)"},{"date":"2026-08-02","event":"High-risk systems compliance deadline (most provisions in force)"},{"date":"2027-08-02","event":"High-risk systems integrated into existing product safety regulated"}],"scope":"Any AI system placed on the EU market or affecting EU users. Tiered by risk level: prohibited, high-risk, limited, minimal.","summary":"Tiered risk-based AI regulation. GPAI providers must publish summaries of training data, respect copyright opt-outs, evaluate systemic risk for very capable models. High-risk systems require conformity assessments + EU database registration.","lead":"European Commission AI Office + national authorities","penalties":"Up to €35M or 7% of global turnover for prohibited use; €15M or 3% for non-compliance with GPAI obligations","url":"https://artificialintelligenceact.eu"}
+{"id":"us-ai-eo-trump-2025","name":"Removing Barriers to American Leadership in AI (EO 14179)","jurisdiction":"United States (federal)","status":"active","type":"executive-order","enactedDate":"2025-01-23","milestones":[{"date":"2025-01-23","event":"Signed by President Trump; revokes Biden EO 14110"},{"date":"2025-07-23","event":"AI Action Plan released by White House OSTP"},{"date":"2026-01-23","event":"One-year review of agency implementation"}],"scope":"All US federal agencies; sets priorities for AI competitiveness, safety, and procurement.","summary":"Replaced Biden's 2023 EO 14110. Focuses on accelerating US AI competitiveness and reducing perceived regulatory barriers; preserves NIST AISI but reframes voluntary safety commitments. State-level laws (CA, CO, NY, IL) increasingly fill the federal gap.","lead":"White House OSTP + NIST AISI","penalties":"No direct penalties (executive order applies to agencies, not private actors)","url":"https://www.whitehouse.gov/presidential-actions/2025/01/removing-barriers-to-american-leadership-in-artificial-intelligence/"}
+{"id":"guard-act-2026","name":"GUARD Act","jurisdiction":"United States (federal)","status":"pending","type":"law","enactedDate":null,"milestones":[{"date":"2026-02-12","event":"Introduced by Sens. Hawley (R) and Blumenthal (D)"},{"date":"2026-04-30","event":"Senate Judiciary Committee advanced 22-0 (unanimous)"},{"date":"2026-Q3","event":"Expected Senate floor vote (TBD)"}],"scope":"AI chatbots interacting with US users. Special focus on minors.","summary":"Government-ID age verification for AI chatbots, flat ban on AI companions for minors, mandatory non-human disclosures every 30 minutes, criminal penalties for design choices that knowingly route minors into sexually explicit or self-harm content.","lead":"Senate Judiciary Committee; FTC implementation expected","penalties":"Civil + criminal penalties for design choices; product-recall authority","url":"https://www.judiciary.senate.gov"}
+{"id":"ca-sb-1047","name":"California SB 1047","jurisdiction":"California","status":"repealed","type":"law","enactedDate":null,"milestones":[{"date":"2024-09-29","event":"Vetoed by Governor Newsom"}],"scope":"AI models trained with > $100M compute or 10^26 FLOPs. Frontier AI labs operating in California.","summary":"Would have required pre-deployment safety testing, kill-switch capability, and whistleblower protections for frontier AI. Vetoed; replaced in spirit by California's narrower AI transparency laws (AB 2013) and the federal AI EO debate.","lead":"California Office of Technology + AG (would have been)","penalties":"N/A (vetoed)","url":"https://leginfo.legislature.ca.gov/faces/billNavClient.xhtml?bill_id=202320240SB1047"}
+{"id":"ca-ab-2013","name":"California AB 2013 (Generative AI Training Data Transparency)","jurisdiction":"California","status":"active","type":"law","enactedDate":"2024-09-28","milestones":[{"date":"2024-09-28","event":"Signed"},{"date":"2026-01-01","event":"Compliance deadline"}],"scope":"Developers of generative AI systems made available to California residents.","summary":"Requires public disclosure of training-data summaries, data sources, copyright considerations, and PII content for any generative AI system available to Californians starting January 2026.","lead":"California AG","penalties":"Civil enforcement; specific penalties TBD","url":"https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202320240AB2013"}
+{"id":"uk-aisi","name":"UK AI Safety Institute","jurisdiction":"United Kingdom","status":"active","type":"voluntary-framework","enactedDate":"2023-11","milestones":[{"date":"2023-11-02","event":"Founded at AI Safety Summit"},{"date":"2024-05-21","event":"Voluntary pre-deployment testing agreements with frontier labs"},{"date":"2025-06","event":"AI Bill expected (UK government)"}],"scope":"Frontier AI labs operating in UK or releasing to UK users. Voluntary at present; may become mandatory.","summary":"Pre-deployment red-team evaluations of frontier models across cyber, biosecurity, autonomous-system, political-influence dimensions. Operates under DSIT (Department for Science, Innovation and Technology).","lead":"DSIT / UK AISI","penalties":"No statutory penalties yet; pending AI Bill expected to add them","url":"https://www.aisi.gov.uk"}
+{"id":"china-genai-measures","name":"Interim Measures for the Management of Generative AI Services","jurisdiction":"China","status":"active","type":"regulation","enactedDate":"2023-08-15","milestones":[{"date":"2023-08-15","event":"Entered into force"},{"date":"2024-04-01","event":"Mandatory generative AI service registration with CAC"},{"date":"2025-09-01","event":"AI-generated content labeling rules effective"}],"scope":"Generative AI services offered to the Chinese public. Registration, licensing, and content controls.","summary":"Pre-launch security assessment, content filtering aligned with Chinese law, watermarking + labeling of AI-generated content, training-data provenance documentation.","lead":"Cyberspace Administration of China (CAC)","penalties":"License revocation, fines, criminal referral for violations","url":"https://www.cac.gov.cn"}
+{"id":"korea-basic-ai-act","name":"Korea Basic Act on AI","jurisdiction":"South Korea","status":"pending","type":"law","enactedDate":"2024-12-26","milestones":[{"date":"2024-12-26","event":"Passed National Assembly"},{"date":"2026-01-22","event":"Entered into force (delayed implementation)"}],"scope":"AI providers operating in South Korea or providing services to Korean users.","summary":"Comprehensive AI governance framework. Risk-based tiers (similar to EU AI Act lite). Korean Ministry of Science and ICT designated as enforcement authority. Lighter-touch than EU AI Act on GPAI obligations.","lead":"Ministry of Science and ICT (MSIT)","penalties":"Administrative fines up to KRW 30M ($22k) per violation","url":"https://www.msit.go.kr"}
+{"id":"nist-ai-rmf","name":"NIST AI Risk Management Framework","jurisdiction":"United States (voluntary, internationally referenced)","status":"active","type":"voluntary-framework","enactedDate":"2023-01-26","milestones":[{"date":"2023-01-26","event":"AI RMF 1.0 published"},{"date":"2024-07-26","event":"Generative AI Profile published"}],"scope":"Voluntary; widely referenced in US federal procurement and state laws.","summary":"Risk-management lifecycle for AI systems: Govern, Map, Measure, Manage. Generative AI profile addresses model-specific risks. Foundation for many state and sector-specific AI laws.","lead":"NIST","penalties":"Voluntary (no penalties)","url":"https://www.nist.gov/itl/ai-risk-management-framework"}
+{"id":"iso-42001","name":"ISO/IEC 42001 (AI Management Systems)","jurisdiction":"International (ISO standard)","status":"active","type":"standard","enactedDate":"2023-12-18","milestones":[{"date":"2023-12-18","event":"Published"},{"date":"2024-Q4","event":"First commercial certifications issued"}],"scope":"Organizations developing or deploying AI systems. Voluntary certification.","summary":"First international management-system standard for AI. Specifies requirements for establishing, implementing, maintaining, and improving an AI management system. Often required by enterprise buyers.","lead":"ISO/IEC JTC 1/SC 42","penalties":"Voluntary; loss of certification on non-compliance","url":"https://www.iso.org/standard/81230.html"}

2026-05-24/attention.jsonl ADDED Viewed

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+{"id":"anthropic","name":"Anthropic","news_24h":2,"news_7d":5,"trending_repos":5,"agent_hits":0,"raw_score":23,"attention_score":100,"rank":1,"top_articles":[{"title":"Claude Got Fed Up","source":"Hacker News AI","published_at":"2026-05-24T08:46:13.000Z"},{"title":"Claude hack – Don't waste you token where it's not needed","source":"Hacker News AI","published_at":"2026-05-24T08:03:04.000Z"},{"title":"The Download: coding’s future, the ‘Steroid Olympics,’ and AI-driven science","source":"MIT Technology Review","published_at":"2026-05-22T12:10:00.000Z"}]}
+{"id":"google","name":"Google","news_24h":1,"news_7d":16,"trending_repos":1,"agent_hits":0,"raw_score":22,"attention_score":95.7,"rank":2,"top_articles":[{"title":"Google’s new anything-to-anything AI model is wild","source":"The Verge AI","published_at":"2026-05-23T11:00:00.000Z"},{"title":"Catch up on the Dialogues stage at Google I/O 2026.","source":"Google AI Blog","published_at":"2026-05-22T18:00:00.000Z"},{"title":"Even If You Hate AI, You Will Use Google AI Search","source":"WIRED AI","published_at":"2026-05-22T15:00:00.000Z"}]}
+{"id":"openai","name":"OpenAI","news_24h":1,"news_7d":4,"trending_repos":2,"agent_hits":0,"raw_score":12,"attention_score":52.2,"rank":3,"top_articles":[{"title":"OpenAI and Nvidia Are Using Google's SynthID to Watermark AI Content","source":"Hacker News AI","published_at":"2026-05-24T09:04:49.000Z"},{"title":"Can OpenAI’s ‘Master of Disaster’ Fix AI’s Reputation Crisis?","source":"WIRED AI","published_at":"2026-05-22T00:04:25.000Z"},{"title":"All of the updates from Elon Musk and Sam Altman’s battle over OpenAI","source":"The Verge AI","published_at":"2026-05-21T20:15:18.000Z"}]}
+{"id":"nvidia","name":"NVIDIA","news_24h":1,"news_7d":6,"trending_repos":0,"agent_hits":0,"raw_score":10,"attention_score":43.5,"rank":4,"top_articles":[{"title":"OpenAI and Nvidia Are Using Google's SynthID to Watermark AI Content","source":"Hacker News AI","published_at":"2026-05-24T09:04:49.000Z"},{"title":"NVIDIA GTC Taipei at COMPUTEX: Live Updates on What’s Next in AI","source":"NVIDIA AI Blog","published_at":"2026-05-21T16:00:17.000Z"},{"title":"License to Stream: ‘007 First Light’ Coming to GeForce NOW With an Ultimate Bundle","source":"NVIDIA AI Blog","published_at":"2026-05-21T13:00:22.000Z"}]}
+{"id":"huggingface","name":"Hugging Face","news_24h":0,"news_7d":6,"trending_repos":1,"agent_hits":0,"raw_score":8,"attention_score":34.8,"rank":5,"top_articles":[{"title":"Towards Speed-of-Light Text Generation with Nemotron-Labs Diffusion Language Models","source":"Hugging Face Blog","published_at":"2026-05-23T00:02:03.000Z"},{"title":"Specialization Beats Scale: A Strategic Variable Most AI Procurement Decisions Overlook","source":"Hugging Face Blog","published_at":"2026-05-22T15:25:59.000Z"},{"title":"OlmoEarth v1.1: A more efficient family of Earth observation models","source":"Hugging Face Blog","published_at":"2026-05-19T18:38:09.000Z"}]}
+{"id":"xai","name":"xAI","news_24h":0,"news_7d":3,"trending_repos":0,"agent_hits":0,"raw_score":3,"attention_score":13,"rank":6,"top_articles":[{"title":"Elon, stop trying to make Grok happen","source":"The Verge AI","published_at":"2026-05-22T17:17:06.000Z"},{"title":"SpaceX Listed Grok’s ‘Spicy’ Mode as a Risk in Its IPO Filing","source":"WIRED AI","published_at":"2026-05-21T00:43:13.000Z"},{"title":"Vera Arrives: NVIDIA’s First CPU Built for Agents Lands at Top AI Labs","source":"NVIDIA AI Blog","published_at":"2026-05-18T21:48:17.000Z"}]}
+{"id":"meta","name":"Meta","news_24h":0,"news_7d":0,"trending_repos":0,"agent_hits":0,"raw_score":0,"attention_score":0,"rank":7,"top_articles":[]}
+{"id":"mistral","name":"Mistral","news_24h":0,"news_7d":0,"trending_repos":0,"agent_hits":0,"raw_score":0,"attention_score":0,"rank":8,"top_articles":[]}
+{"id":"cohere","name":"Cohere","news_24h":0,"news_7d":0,"trending_repos":0,"agent_hits":0,"raw_score":0,"attention_score":0,"rank":9,"top_articles":[]}
+{"id":"deepseek","name":"DeepSeek","news_24h":0,"news_7d":0,"trending_repos":0,"agent_hits":0,"raw_score":0,"attention_score":0,"rank":10,"top_articles":[]}
+{"id":"perplexity","name":"Perplexity","news_24h":0,"news_7d":0,"trending_repos":0,"agent_hits":0,"raw_score":0,"attention_score":0,"rank":11,"top_articles":[]}
+{"id":"cursor","name":"Cursor","news_24h":0,"news_7d":0,"trending_repos":0,"agent_hits":0,"raw_score":0,"attention_score":0,"rank":12,"top_articles":[]}

2026-05-24/benchmark-registry.jsonl ADDED Viewed

	@@ -0,0 +1,24 @@

+{"id":"mmlu","name":"MMLU","category":"knowledge","description":"Massive Multitask Language Understanding. 57-subject multiple-choice covering law, medicine, history, math, etc. The original general-knowledge benchmark.","released":"2020","size":"15,908 questions","scoreRange":"0-100% accuracy","frontierScore":"~92%","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"saturated","contaminationRisk":"high","maintainer":"Hendrycks et al.","paperUrl":"https://arxiv.org/abs/2009.03300","repoUrl":"https://github.com/hendrycks/test","leaderboardUrl":null,"whoCares":"General assistants. Mostly saturated; use MMLU-Pro for current frontier signal."}
+{"id":"mmlu-pro","name":"MMLU-Pro","category":"knowledge","description":"Harder successor to MMLU. 10-choice questions designed to require multi-step reasoning over memorization. Standard \"is this model smart\" benchmark for general-purpose use.","released":"2024","size":"12,032 questions","scoreRange":"0-100% accuracy","frontierScore":"~94%","frontierModel":"GPT-5 (high reasoning)","frontierDate":"2025-08","frontierSource":"https://huggingface.co/spaces/TIGER-Lab/MMLU-Pro","status":"active","contaminationRisk":"medium","maintainer":"TIGER Lab","paperUrl":"https://arxiv.org/abs/2406.01574","repoUrl":"https://github.com/TIGER-AI-Lab/MMLU-Pro","leaderboardUrl":"https://huggingface.co/spaces/TIGER-Lab/MMLU-Pro","whoCares":"General chat assistants and research synthesis agents."}
+{"id":"gpqa-diamond","name":"GPQA Diamond","category":"knowledge","description":"Graduate-level Google-Proof Questions, Diamond subset. 198 expert-validated PhD-hard physics, chemistry, biology questions.","released":"2023","size":"198 questions","scoreRange":"0-100% accuracy","frontierScore":"~88%","frontierModel":"o3 (high compute)","frontierDate":"2024-12","frontierSource":"https://openai.com/index/learning-to-reason-with-llms/","status":"active","contaminationRisk":"low","maintainer":"Rein et al.","paperUrl":"https://arxiv.org/abs/2311.12022","repoUrl":"https://github.com/idavidrein/gpqa","leaderboardUrl":null,"whoCares":"Research agents, technical writing agents, anyone who needs scientific reasoning beyond fact recall."}
+{"id":"hle","name":"Humanity's Last Exam","category":"knowledge","description":"Joint CAIS/Scale benchmark of 3,000 expert-validated questions across 100+ disciplines. The hardest broad-knowledge benchmark in 2025-2026.","released":"2025-01","size":"3,000 questions","scoreRange":"0-100% accuracy","frontierScore":"~30%","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"active","contaminationRisk":"low","maintainer":"CAIS + Scale AI","paperUrl":"https://lastexam.ai","repoUrl":"https://github.com/centerforaisafety/hle","leaderboardUrl":"https://lastexam.ai","whoCares":"Frontier-model evaluators. The benchmark every model release in 2026 reports against. Leaderboard is the freshness anchor."}
+{"id":"arc-agi-2","name":"ARC-AGI-2","category":"knowledge","description":"Abstract pattern-matching benchmark from Francois Chollet. ARC-AGI-2 is the harder 2025 successor; tests novel problem solving without training-data overlap.","released":"2025-03","size":"~400 tasks public, more private","scoreRange":"0-100% accuracy","frontierScore":"~25%","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"active","contaminationRisk":"low","maintainer":"ARC Prize Foundation","paperUrl":"https://arxiv.org/abs/2412.04604","repoUrl":"https://github.com/arcprize/ARC-AGI-2","leaderboardUrl":"https://arcprize.org/leaderboard","whoCares":"AGI researchers. The least-saturated frontier benchmark; current models lag far behind humans. Leaderboard updates frequently."}
+{"id":"math","name":"MATH","category":"math","description":"Competition-level math problems (AMC, AIME, Putnam). Multi-step algebra, geometry, combinatorics. Exact-match scoring.","released":"2021","size":"12,500 problems","scoreRange":"0-100% accuracy","frontierScore":"~96%","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"saturated","contaminationRisk":"high","maintainer":"Hendrycks et al.","paperUrl":"https://arxiv.org/abs/2103.03874","repoUrl":"https://github.com/hendrycks/math","leaderboardUrl":null,"whoCares":"Quantitative agents. Largely saturated; use AIME 2025 for current signal."}
+{"id":"aime-2025","name":"AIME 2025","category":"math","description":"American Invitational Mathematics Examination 2025. 30 hard high-school competition math problems, integer answers. Released contamination-free in 2025.","released":"2025","size":"30 problems","scoreRange":"0-30 correct","frontierScore":"~28/30","frontierModel":"o3 (high compute)","frontierDate":"2025-02","frontierSource":"https://artificialanalysis.ai","status":"active","contaminationRisk":"low","maintainer":"MAA","paperUrl":null,"repoUrl":null,"leaderboardUrl":"https://artificialanalysis.ai","whoCares":"Frontier reasoning evaluators. Standard reasoning-tier test in 2025-2026 model release announcements."}
+{"id":"gsm8k","name":"GSM8K","category":"math","description":"Grade-school math word problems. Multi-step arithmetic with chain-of-thought as the canonical solution form.","released":"2021","size":"8,500 problems","scoreRange":"0-100% accuracy","frontierScore":"~97%","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"saturated","contaminationRisk":"high","maintainer":"OpenAI","paperUrl":"https://arxiv.org/abs/2110.14168","repoUrl":"https://github.com/openai/grade-school-math","leaderboardUrl":null,"whoCares":"Mostly saturated. Useful as a sanity check that a model can do basic chain-of-thought reasoning."}
+{"id":"humaneval","name":"HumanEval","category":"code","description":"OpenAI's 164 Python programming problems with unit tests. The original code-gen benchmark.","released":"2021","size":"164 problems","scoreRange":"0-100% pass@1","frontierScore":"~97%","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"saturated","contaminationRisk":"high","maintainer":"OpenAI","paperUrl":"https://arxiv.org/abs/2107.03374","repoUrl":"https://github.com/openai/human-eval","leaderboardUrl":"https://paperswithcode.com/sota/code-generation-on-humaneval","whoCares":"Capability floor only. Not a frontier signal; use SWE-bench Verified or LiveCodeBench instead."}
+{"id":"mbpp","name":"MBPP","category":"code","description":"Mostly Basic Python Problems. 1k crowd-sourced introductory programming problems.","released":"2021","size":"974 problems","scoreRange":"0-100% pass@1","frontierScore":"~92%","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"saturated","contaminationRisk":"high","maintainer":"Google Research","paperUrl":"https://arxiv.org/abs/2108.07732","repoUrl":"https://github.com/google-research/google-research/tree/master/mbpp","leaderboardUrl":null,"whoCares":"Same role as HumanEval. Saturated; use newer benchmarks."}
+{"id":"livecodebench","name":"LiveCodeBench","category":"code","description":"Continuously refreshed code benchmark. Pulls competitive programming problems (LeetCode, AtCoder, Codeforces) from after a model's training cutoff. Contamination-free by construction.","released":"2024","size":"1k+ problems, growing","scoreRange":"0-100% pass@1","frontierScore":"~75%","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"active","contaminationRisk":"low","maintainer":"UC Berkeley + UW","paperUrl":"https://arxiv.org/abs/2403.07974","repoUrl":"https://github.com/LiveCodeBench/LiveCodeBench","leaderboardUrl":"https://livecodebench.github.io/leaderboard.html","whoCares":"Coding agents. The contamination-resistant alternative to HumanEval. Leaderboard rotates fast as the problem set grows."}
+{"id":"swe-bench-verified","name":"SWE-bench Verified","category":"code","description":"500 human-validated GitHub issues across 12 Python repos. Patch must resolve the issue and pass the project test suite.","released":"2024-08","size":"500 instances","scoreRange":"0-100% resolved","frontierScore":"~75%","frontierModel":"Claude Sonnet 4.6","frontierDate":"2025-09","frontierSource":"https://www.swebench.com/","status":"active","contaminationRisk":"medium","maintainer":"OpenAI / Princeton","paperUrl":"https://arxiv.org/abs/2310.06770","repoUrl":"https://github.com/swe-bench/SWE-bench","leaderboardUrl":"https://www.swebench.com/","whoCares":"Coding agents. The single benchmark most production agentic-coding tools report against."}
+{"id":"aider-polyglot","name":"Aider Polyglot","category":"code","description":"225 of the hardest Exercism exercises across C++, Go, Java, JavaScript, Python, Rust. Edit-by-diff scoring (closer to real-world coding work).","released":"2024","size":"225 problems","scoreRange":"0-100% pass@2","frontierScore":"~85%","frontierModel":"Claude Sonnet 4.6","frontierDate":"2025-09","frontierSource":"https://aider.chat/docs/leaderboards/","status":"active","contaminationRisk":"medium","maintainer":"Aider","paperUrl":null,"repoUrl":"https://github.com/Aider-AI/polyglot-benchmark","leaderboardUrl":"https://aider.chat/docs/leaderboards/","whoCares":"Multilingual coding agents. The cross-language complement to SWE-bench."}
+{"id":"terminal-bench","name":"Terminal-Bench","category":"code","description":"Stanford / Anthropic agentic terminal-task benchmark. Each task gives the agent a goal and a sandboxed shell; success measured by deterministic post-condition.","released":"2025-01","size":"~80 tasks","scoreRange":"0-100% solved","frontierScore":"~52%","frontierModel":"Claude Sonnet 4.6","frontierDate":"2025-09","frontierSource":"https://www.tbench.ai/","status":"active","contaminationRisk":"low","maintainer":"Stanford + Anthropic","paperUrl":"https://arxiv.org/abs/2501.18099","repoUrl":"https://github.com/laude-institute/terminal-bench","leaderboardUrl":"https://www.tbench.ai/","whoCares":"Terminal-shaped agents (Claude Code, Codex CLI, Aider). Tests the loop, not the language model."}
+{"id":"swe-lancer","name":"SWE-Lancer","category":"code","description":"OpenAI benchmark of paid Upwork engineering tasks ($1M+ in real bounties). Includes diff-style fixes and longer feature work judged against original buyer acceptance criteria.","released":"2025-02","size":"1,488 tasks","scoreRange":"0-100% earned","frontierScore":"~42%","frontierModel":"GPT-5","frontierDate":"2025-08","frontierSource":"https://arxiv.org/abs/2502.12115","status":"active","contaminationRisk":"low","maintainer":"OpenAI","paperUrl":"https://arxiv.org/abs/2502.12115","repoUrl":"https://github.com/openai/SWELancer-Benchmark","leaderboardUrl":null,"whoCares":"Agentic-coding evaluators. Most realistic eval of \"could you replace a freelance engineer for this task.\""}
+{"id":"mmmu-pro","name":"MMMU-Pro","category":"multimodal","description":"Massive Multi-discipline Multimodal Understanding. College-level questions with images across 30 subjects. Pro version drops text-only solvable variants.","released":"2024","size":"~3,500 questions","scoreRange":"0-100% accuracy","frontierScore":"~78%","frontierModel":"Gemini 2.5 Pro","frontierDate":"2025-06","frontierSource":"https://mmmu-benchmark.github.io","status":"active","contaminationRisk":"medium","maintainer":"TIGER Lab + IN.AI","paperUrl":"https://arxiv.org/abs/2409.02813","repoUrl":"https://github.com/MMMU-Benchmark/MMMU","leaderboardUrl":"https://mmmu-benchmark.github.io","whoCares":"Vision-capable agents. Standard benchmark in multimodal model release announcements."}
+{"id":"mathvista","name":"MathVista","category":"multimodal","description":"Visual math reasoning across diagrams, charts, geometry, and graphs.","released":"2024","size":"6,141 problems","scoreRange":"0-100% accuracy","frontierScore":"~80%","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"active","contaminationRisk":"medium","maintainer":"UCLA","paperUrl":"https://arxiv.org/abs/2310.02255","repoUrl":"https://github.com/lupantech/MathVista","leaderboardUrl":"https://mathvista.github.io","whoCares":"Multimodal reasoning agents (chart understanding, scientific diagrams)."}
+{"id":"tau-bench","name":"Tau-Bench","category":"agents","description":"Sierra benchmark of customer-service agents. Tests realistic multi-turn tool-use in airline and retail domains with deterministic evaluators.","released":"2024-06","size":"~250 tasks","scoreRange":"0-100% pass@1","frontierScore":"~70%","frontierModel":"Claude Sonnet 4.6","frontierDate":"2025-09","frontierSource":"https://www.anthropic.com/news/claude-sonnet-4-5","status":"active","contaminationRisk":"low","maintainer":"Sierra","paperUrl":"https://arxiv.org/abs/2406.12045","repoUrl":"https://github.com/sierra-research/tau-bench","leaderboardUrl":null,"whoCares":"Customer-service and tool-use agents. The most cited evaluation of \"would this actually work in production support.\""}
+{"id":"gaia","name":"GAIA","category":"agents","description":"General AI Assistants benchmark. 466 real-world questions requiring web browsing, file ops, and multi-step reasoning. Three difficulty levels.","released":"2023","size":"466 tasks","scoreRange":"0-100% accuracy","frontierScore":"~75% (level 1), ~50% (level 3)","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"active","contaminationRisk":"low","maintainer":"HF + Meta","paperUrl":"https://arxiv.org/abs/2311.12983","repoUrl":"https://huggingface.co/datasets/gaia-benchmark/GAIA","leaderboardUrl":"https://huggingface.co/spaces/gaia-benchmark/leaderboard","whoCares":"Generalist autonomous agents. Tests the full agent loop, not isolated capabilities. HF Space leaderboard rotates frequently."}
+{"id":"webarena","name":"WebArena","category":"agents","description":"Browser-agent benchmark. 812 tasks across 5 simulated websites (e-commerce, GitLab, Reddit, mapping, content management). Deterministic post-condition checks.","released":"2023","size":"812 tasks","scoreRange":"0-100% solved","frontierScore":"~58%","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"active","contaminationRisk":"low","maintainer":"CMU + UW","paperUrl":"https://arxiv.org/abs/2307.13854","repoUrl":"https://github.com/web-arena-x/webarena","leaderboardUrl":"https://webarena.dev/leaderboard","whoCares":"Browser-automation agents. Standard eval for \"can this agent click around the web reliably.\""}
+{"id":"osworld","name":"OSWorld","category":"agents","description":"Computer-use benchmark. Real Ubuntu, Windows, macOS desktops with 369 tasks covering OS-level workflows (file management, app interaction, research).","released":"2024","size":"369 tasks","scoreRange":"0-100% solved","frontierScore":"~28%","frontierModel":"Claude Sonnet 4.6 (Computer Use)","frontierDate":"2025-09","frontierSource":"https://os-world.github.io","status":"active","contaminationRisk":"low","maintainer":"HKU + Salesforce","paperUrl":"https://arxiv.org/abs/2404.07972","repoUrl":"https://github.com/xlang-ai/OSWorld","leaderboardUrl":"https://os-world.github.io","whoCares":"Computer-use agents (Anthropic Computer Use, OpenAI Operator, etc). Hardest agent benchmark in 2026."}
+{"id":"bfcl","name":"BFCL v3","category":"agents","description":"Berkeley Function Calling Leaderboard. Multi-turn, multi-language function calling with parallel and chained tool use.","released":"2024","size":"4,400+ test cases","scoreRange":"0-100% accuracy","frontierScore":"~85%","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"active","contaminationRisk":"medium","maintainer":"UC Berkeley","paperUrl":null,"repoUrl":"https://github.com/ShishirPatil/gorilla","leaderboardUrl":"https://gorilla.cs.berkeley.edu/leaderboard.html","whoCares":"Tool-using agents. Most-cited function-calling benchmark; checks parallel and dependent tool calls."}
+{"id":"hcast","name":"HCAST","category":"agents","description":"METR's long-horizon agentic task suite. Measures how long a task an agent can autonomously complete. Calibrated against human researcher time-to-complete.","released":"2024","size":"~70 tasks","scoreRange":"minutes-of-human-work","frontierScore":"~30 min equivalent","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"active","contaminationRisk":"low","maintainer":"METR","paperUrl":"https://metr.github.io/autonomy-evals-guide/","repoUrl":null,"leaderboardUrl":null,"whoCares":"Frontier autonomy evaluators. The benchmark behind the \"AI does 50% of tasks under N minutes\" framing. METR site is the freshness anchor."}
+{"id":"ruler","name":"RULER","category":"long-context","description":"NVIDIA benchmark for long-context retrieval and reasoning. Multi-needle, variable-tracking, common-words. Tests effective context length, not just claimed.","released":"2024","size":"~13 task categories","scoreRange":"0-100% accuracy","frontierScore":"effective ~256k for 1M-claimed models","frontierModel":null,"frontierDate":null,"frontierSource":null,"status":"active","contaminationRisk":"low","maintainer":"NVIDIA","paperUrl":"https://arxiv.org/abs/2404.06654","repoUrl":"https://github.com/NVIDIA/RULER","leaderboardUrl":null,"whoCares":"Anyone using long-context models. RULER reveals the gap between claimed and effective context length."}

2026-05-24/benchmarks.jsonl ADDED Viewed

	@@ -0,0 +1,5 @@

+{"id":"mmlu_pro","name":"MMLU-Pro","description":"General knowledge and reasoning across 57 subjects","maxScore":100}
+{"id":"human_eval","name":"HumanEval","description":"Python code generation and problem solving","maxScore":100}
+{"id":"gpqa_diamond","name":"GPQA Diamond","description":"Graduate-level science questions verified by domain experts","maxScore":100}
+{"id":"math","name":"MATH","description":"Competition-level mathematics problems","maxScore":100}
+{"id":"swe_bench","name":"SWE-bench","description":"Real-world software engineering tasks from GitHub issues","maxScore":100}

2026-05-24/compute-providers.jsonl ADDED Viewed

	@@ -0,0 +1,17 @@

+{"id":"lambda","name":"Lambda","vendor":"Lambda","type":"gpu-cloud","gpus":["B200","H200","H100","A100","A6000"],"pricingModel":"On-demand + 1/3-year reserved","startingPrice":"H100 from $2.49/hr on-demand","onDemand":true,"spotPricing":false,"regions":"US (multiple), EU, APAC","aiServices":["Lambda Stack (preinstalled CUDA + frameworks)","1-Click Clusters","managed Kubernetes","private cloud"],"bestFor":"Researchers + AI startups wanting bare-metal GPU without hyperscaler complexity","url":"https://lambdalabs.com","notes":"Founded 2012. The default 'GPU cloud' for indie AI research and startup deployments. Strong CLI experience."}
+{"id":"coreweave","name":"CoreWeave","vendor":"CoreWeave","type":"gpu-cloud","gpus":["GB200","B200","H200","H100","A100","A40"],"pricingModel":"Reserved (1-3 year minimum) + on-demand","startingPrice":"H100 from $2.23/hr (reserved); higher on-demand","onDemand":true,"spotPricing":false,"regions":"US (multiple), UK, EU expanding","aiServices":["Kubernetes-first","managed inference","SUNK scheduler (Slurm-on-K8s)","NVLink fabric"],"bestFor":"Frontier labs + enterprise AI training; second-largest H100/H200 fleet after AWS","url":"https://www.coreweave.com","notes":"IPO'd 2025. Anchor tenant for many frontier lab compute deals. Specializes in NVIDIA-only large-scale training."}
+{"id":"crusoe","name":"Crusoe","vendor":"Crusoe","type":"gpu-cloud","gpus":["B200","H200","H100","A100","A40"],"pricingModel":"Reserved + on-demand","startingPrice":"H100 from $2.45/hr on-demand","onDemand":true,"spotPricing":false,"regions":"US (TX, IA, OK, ND); building Abilene Texas mega-site","aiServices":["AI-first data centers","managed inference","GPU clusters","sustainable energy sourcing"],"bestFor":"Enterprise AI training where energy story matters; mega-cluster customers","url":"https://crusoe.ai","notes":"Founded as 'Crusoe Energy' (stranded methane); pivoted to AI-first data centers. The Abilene Texas site is among the largest under construction in 2026."}
+{"id":"nebius","name":"Nebius","vendor":"Nebius (formerly Yandex N.V.)","type":"gpu-cloud","gpus":["H200","H100"],"pricingModel":"On-demand + reserved + spot","startingPrice":"H100 from $1.99/hr on-demand","onDemand":true,"spotPricing":true,"regions":"EU (Finland), Israel; US Kansas City planned 2026","aiServices":["vLLM serving","fine-tuning service","managed K8s","NVLink fabric"],"bestFor":"EU customers needing data residency; cost-sensitive H100 access","url":"https://nebius.com","notes":"Reorganized after Yandex split. EU-headquartered. Strong NVIDIA H200/B200 supply for 2026."}
+{"id":"vast-ai","name":"Vast.ai","vendor":"Vast.ai","type":"marketplace","gpus":["H100","A100","RTX 4090","RTX 3090","RTX 6000","consumer GPUs"],"pricingModel":"Marketplace (host bid + offer)","startingPrice":"RTX 3090 from $0.20/hr; H100 from $1.50/hr (varies wildly)","onDemand":true,"spotPricing":true,"regions":"Global (host-dependent)","aiServices":["Docker-only deployments","SSH access","image library"],"bestFor":"Hobbyist + research workloads; cheapest path for short experiments","url":"https://vast.ai","notes":"Marketplace of independent GPU hosts. Heterogeneous quality; verified hosts available. The cheapest GPU rentals in the catalog."}
+{"id":"runpod","name":"RunPod","vendor":"RunPod","type":"marketplace","gpus":["H200","H100","A100","L40S","RTX 4090","RTX A6000"],"pricingModel":"Secure Cloud (RunPod-managed) + Community Cloud (peer hosts) + Serverless","startingPrice":"H100 from $1.99/hr (Secure); $1.49/hr (Community)","onDemand":true,"spotPricing":true,"regions":"Global (multiple)","aiServices":["Serverless GPU functions","instant deploy templates","persistent volumes"],"bestFor":"AI app developers wanting per-second serverless GPU + on-demand instances","url":"https://www.runpod.io","notes":"Strong serverless GPU offering. Fastest cold-start in the marketplace category."}
+{"id":"paperspace","name":"Paperspace (DigitalOcean)","vendor":"DigitalOcean","type":"gpu-cloud","gpus":["H100","A100","A6000","A5000","RTX 4000"],"pricingModel":"On-demand + Gradient (managed Jupyter)","startingPrice":"A100 from $3.09/hr","onDemand":true,"spotPricing":false,"regions":"US (multiple), EU","aiServices":["Gradient managed Jupyter","Core (raw VM access)","deployments"],"bestFor":"Solo data scientists + small teams wanting managed Jupyter environment","url":"https://www.paperspace.com","notes":"Acquired by DigitalOcean 2023. Strong Jupyter-first UX; less competitive on raw H100 pricing than Lambda or CoreWeave."}
+{"id":"aws-ec2-gpu","name":"AWS EC2 GPU","vendor":"Amazon Web Services","type":"hyperscaler","gpus":["B200 (P6)","H200 (P5e)","H100 (P5)","A100 (P4d)","V100 (P3)"],"pricingModel":"On-demand + Reserved + Spot + Capacity Reservations + Trainium dedicated","startingPrice":"P5 (H100, 8x) from $98.32/hr on-demand; spot 50-70% cheaper","onDemand":true,"spotPricing":true,"regions":"Global (32 regions)","aiServices":["Bedrock (managed model APIs)","SageMaker","Trainium / Inferentia","Capacity Blocks","EFA networking"],"bestFor":"Enterprise + regulated industries needing AWS ecosystem integration","url":"https://aws.amazon.com/ec2/instance-types/p5/","notes":"Largest cloud AI compute footprint. Bedrock is the managed-model layer; Trainium is AWS's in-house silicon (Anthropic uses these)."}
+{"id":"azure-ml","name":"Azure ML / OpenAI Service","vendor":"Microsoft","type":"hyperscaler","gpus":["H200 (NDv5)","H100 (ND H100)","A100 (ND A100)","B200 announced"],"pricingModel":"On-demand + Reserved + Spot + Azure Reserved Instances","startingPrice":"ND H100 v5 from $98.32/hr","onDemand":true,"spotPricing":true,"regions":"Global (60+ regions)","aiServices":["Azure OpenAI Service (private GPT)","Azure AI Foundry","Phi-4 hosting","Maia 100 (in-house silicon)"],"bestFor":"Enterprise customers anchored on Microsoft ecosystem; private GPT deployments","url":"https://azure.microsoft.com/en-us/products/machine-learning/","notes":"Strongest first-party OpenAI hosting (Azure OpenAI Service). Maia 100 is Microsoft's in-house silicon, paralleling Trainium / TPU."}
+{"id":"gcp-vertex","name":"GCP Vertex AI / Compute Engine GPU","vendor":"Google","type":"hyperscaler","gpus":["B200","H200","H100","A100","L4","TPU v5p","TPU v5e"],"pricingModel":"On-demand + Sustained Use + Committed Use Discounts + Spot + TPU pod-hours","startingPrice":"A3 (8x H100) from $88.49/hr; TPU v5p pod-hour from $4.20","onDemand":true,"spotPricing":true,"regions":"Global (40+ regions)","aiServices":["Vertex AI","Gemini API","TPU v5p pods","Model Garden","AutoML"],"bestFor":"Customers needing TPU access; Gemini-anchored stacks","url":"https://cloud.google.com/vertex-ai","notes":"Only major cloud with TPU access. Vertex AI is the managed-model layer. TPU pods (8960-chip topology) are unique in the industry."}
+{"id":"oci-gpu","name":"Oracle Cloud Infrastructure","vendor":"Oracle","type":"hyperscaler","gpus":["B200","H200","H100","A100","L40S","GB200 announced"],"pricingModel":"On-demand + Annual flex commitments + Bare metal","startingPrice":"BM.GPU.H100.8 from $84.00/hr on-demand","onDemand":true,"spotPricing":false,"regions":"Global (50+ regions, OCI Generation 2)","aiServices":["OCI Generative AI","Cohere partnership (private deployments)","GPU Bare Metal"],"bestFor":"Enterprise + government wanting NVIDIA cluster scale at competitive bare-metal pricing","url":"https://www.oracle.com/cloud/compute/gpu/","notes":"Won large frontier-lab contracts (xAI, Meta) on bare-metal GPU pricing. Strongest cluster networking story among hyperscalers."}
+{"id":"modal","name":"Modal","vendor":"Modal Labs","type":"ai-serverless","gpus":["H200","H100","A100","A10","L4","L40S","T4"],"pricingModel":"Pay-per-second compute + $30/mo free credit","startingPrice":"H100 from $3.95/hr; per-second billing","onDemand":true,"spotPricing":false,"regions":"US (multi-region)","aiServices":["serverless functions","instant cold-start GPU","volumes","web endpoints","cron jobs","distributed training"],"bestFor":"Python developers wanting serverless GPU without container ops","url":"https://modal.com","notes":"Per-second GPU billing with sub-second cold-start. Best Python developer ergonomics in the AI-serverless category."}
+{"id":"replicate-compute","name":"Replicate","vendor":"Replicate","type":"ai-serverless","gpus":["H100","A100","A40","T4","CPU"],"pricingModel":"Pay-per-second on the model you run","startingPrice":"H100 from $0.001525/sec ($5.49/hr)","onDemand":true,"spotPricing":false,"regions":"US, EU","aiServices":["model marketplace (40k+ models)","API endpoints","webhooks","fine-tuning"],"bestFor":"Image / video / voice model developers wanting one-API model serving","url":"https://replicate.com","notes":"Pay-per-second model serving with massive (40k+) catalog. Strong fit for media-generation pipelines."}
+{"id":"beam","name":"Beam","vendor":"Beam.cloud","type":"ai-serverless","gpus":["H100","A100","A10G","T4"],"pricingModel":"Pay-per-second + monthly commit tiers","startingPrice":"H100 from $3.40/hr; per-second","onDemand":true,"spotPricing":false,"regions":"US","aiServices":["serverless GPU functions","apps","persistent volumes","queues"],"bestFor":"Modal-alternative for teams wanting cheaper H100 per-second pricing","url":"https://www.beam.cloud","notes":"Younger Modal competitor. Slightly cheaper H100 per-second. Smaller library of preinstalled environments."}
+{"id":"cerebras-cloud","name":"Cerebras Cloud","vendor":"Cerebras","type":"specialized","gpus":["CS-3 (WSE-3 wafer)"],"pricingModel":"Per-token API (proprietary inference)","startingPrice":"Llama 3.3 70B at $0.85 input / $1.20 output per 1M","onDemand":true,"spotPricing":false,"regions":"US","aiServices":["ultra-fast inference","training service","Cerebras Inference Cloud"],"bestFor":"Inference workloads needing maximum tokens/sec on Llama-class models","url":"https://cerebras.ai/inference","notes":"Unique wafer-scale silicon. Fastest inference in production for sub-100B models (1500+ tokens/sec on Llama 3.3 70B)."}
+{"id":"sambanova","name":"SambaNova Cloud","vendor":"SambaNova","type":"specialized","gpus":["SN40L (in-house RDU)"],"pricingModel":"Per-token API + dedicated capacity","startingPrice":"Llama 3.3 70B at $0.60 input / $1.20 output per 1M","onDemand":true,"spotPricing":false,"regions":"US","aiServices":["fast inference","fine-tuning service","private deployments"],"bestFor":"Enterprise inference; on-prem private cloud option","url":"https://sambanova.ai/cloud","notes":"Custom RDU silicon. Strong on-prem private deployment story. Less hype than Cerebras but solid customer list."}
+{"id":"fireworks-compute","name":"Fireworks Compute","vendor":"Fireworks AI","type":"ai-serverless","gpus":["H200","H100"],"pricingModel":"Per-token (serverless) + dedicated reserved (per GPU-hour)","startingPrice":"H100 reserved from $2.50/hr; serverless per-token varies","onDemand":true,"spotPricing":false,"regions":"US, EU","aiServices":["serverless model APIs","dedicated capacity","fine-tuning","multi-LoRA serving"],"bestFor":"Production inference on open-weights models with reserved capacity option","url":"https://fireworks.ai","notes":"Inference-first platform. Multi-LoRA serving (many fine-tunes share one base GPU) is the pricing differentiator."}

2026-05-24/conferences.jsonl ADDED Viewed

	@@ -0,0 +1,18 @@

+{"id":"aaai-2026","name":"AAAI 2026","category":"research","startDate":"2026-01-20","endDate":"2026-01-27","city":"Philadelphia","country":"USA","format":"in-person","paperDeadline":"2025-08-15","registrationOpen":false,"themes":["AI broadly","agents","planning","reasoning"],"url":"https://aaai.org/conference/aaai/aaai-26/","notes":"AAAI Conference on Artificial Intelligence. Broadest AI venue (covers more than just deep learning). Big presence from China-based research."}
+{"id":"gtc-2026","name":"NVIDIA GTC 2026","category":"industry","startDate":"2026-03-16","endDate":"2026-03-19","city":"San Jose, CA","country":"USA","format":"hybrid","paperDeadline":null,"registrationOpen":false,"themes":["Blackwell","AI factories","Omniverse","robotics"],"url":"https://www.nvidia.com/gtc/","notes":"NVIDIA's GPU Technology Conference. Major chip + AI infrastructure announcements; Jensen keynote is the AI hardware industry's State of the Union."}
+{"id":"iclr-2026","name":"ICLR 2026","category":"research","startDate":"2026-04-25","endDate":"2026-04-29","city":"Singapore","country":"Singapore","format":"hybrid","paperDeadline":"2025-09-26","registrationOpen":true,"themes":["representation learning","foundation models","agents","safety"],"url":"https://iclr.cc/Conferences/2026","notes":"International Conference on Learning Representations. Top deep-learning venue along with NeurIPS and ICML. 2026 returns to Singapore."}
+{"id":"google-io-2026","name":"Google I/O 2026","category":"industry","startDate":"2026-05-13","endDate":"2026-05-14","city":"Mountain View, CA","country":"USA","format":"hybrid","paperDeadline":null,"registrationOpen":true,"themes":["Gemini","Android","Workspace AI","developer tools"],"url":"https://io.google","notes":"Google's annual developer conference. Major Gemini announcement venue."}
+{"id":"microsoft-build-2026","name":"Microsoft Build 2026","category":"industry","startDate":"2026-05-19","endDate":"2026-05-22","city":"Seattle, WA","country":"USA","format":"hybrid","paperDeadline":null,"registrationOpen":true,"themes":["Copilot","Azure AI","GitHub Copilot","agents"],"url":"https://build.microsoft.com","notes":"Microsoft's developer conference. Copilot ecosystem + Azure AI announcements."}
+{"id":"aiengineer-summit-2026","name":"AI Engineer World's Fair","category":"developer","startDate":"2026-06-02","endDate":"2026-06-04","city":"San Francisco, CA","country":"USA","format":"in-person","paperDeadline":null,"registrationOpen":true,"themes":["production AI","agents","evals","RAG"],"url":"https://ai.engineer","notes":"Largest practitioner-focused AI engineering conference. swyx-organized; standard ground-truth check on what's working in production."}
+{"id":"wwdc-2026","name":"Apple WWDC 2026","category":"industry","startDate":"2026-06-08","endDate":"2026-06-12","city":"Cupertino, CA","country":"USA","format":"hybrid","paperDeadline":null,"registrationOpen":false,"themes":["Apple Intelligence","iOS","macOS","on-device AI"],"url":"https://developer.apple.com/wwdc26/","notes":"Apple's developer conference. On-device AI announcements + Apple Intelligence updates."}
+{"id":"cvpr-2026","name":"CVPR 2026","category":"research","startDate":"2026-06-14","endDate":"2026-06-19","city":"Nashville","country":"USA","format":"in-person","paperDeadline":"2025-11-14","registrationOpen":true,"themes":["computer vision","multimodal","generative","3D"],"url":"https://cvpr.thecvf.com/Conferences/2026","notes":"Conference on Computer Vision and Pattern Recognition. Top vision venue. Multimodal LLM submissions surging in 2026."}
+{"id":"icml-2026","name":"ICML 2026","category":"research","startDate":"2026-07-12","endDate":"2026-07-18","city":"Vancouver","country":"Canada","format":"hybrid","paperDeadline":"2026-01-30","registrationOpen":false,"themes":["ML theory","foundation models","reinforcement learning","fairness"],"url":"https://icml.cc/Conferences/2026","notes":"International Conference on Machine Learning. Co-flagship with NeurIPS. Vancouver venue."}
+{"id":"acl-2026","name":"ACL 2026","category":"research","startDate":"2026-08-03","endDate":"2026-08-08","city":"Marseille","country":"France","format":"hybrid","paperDeadline":"2026-02-15","registrationOpen":false,"themes":["NLP","multilingual","computational linguistics","discourse"],"url":"https://2026.aclweb.org","notes":"Annual Meeting of the Association for Computational Linguistics. The traditional NLP venue; LLM submissions dominate post-2022."}
+{"id":"maven-llm-bootcamp-2026","name":"Maven LLM Bootcamp","category":"developer","startDate":"2026-09-15","endDate":"2026-10-15","city":"Online","country":"Worldwide","format":"virtual","paperDeadline":null,"registrationOpen":true,"themes":["practical LLMs","fine-tuning","evals"],"url":"https://maven.com","notes":"Hugo Bowne-Anderson-organized cohort-based course. Strong production-AI curriculum."}
+{"id":"cursor-conf-2026","name":"Cursor Conf 2026","category":"developer","startDate":"2026-09-23","endDate":"2026-09-23","city":"San Francisco, CA","country":"USA","format":"in-person","paperDeadline":null,"registrationOpen":false,"themes":["Cursor agents","AI coding","IDE"],"url":"https://cursor.com","notes":"Cursor's annual user conference. Coding agent + IDE direction announcements."}
+{"id":"openai-devday-2026","name":"OpenAI DevDay 2026","category":"industry","startDate":"2026-10-06","endDate":"2026-10-06","city":"San Francisco, CA","country":"USA","format":"in-person","paperDeadline":null,"registrationOpen":false,"themes":["GPT","Apps SDK","agents","Workspace Agents"],"url":"https://openai.com/devday/","notes":"OpenAI's annual developer conference. Major API + Apps SDK announcements."}
+{"id":"colm-2026","name":"COLM 2026","category":"research","startDate":"2026-10-07","endDate":"2026-10-10","city":"Cambridge, MA","country":"USA","format":"in-person","paperDeadline":"2026-03-25","registrationOpen":false,"themes":["language models","evaluation","alignment","multilingual"],"url":"https://colmweb.org","notes":"Conference on Language Modeling. Newer venue (founded 2024) focused specifically on LLMs. Higher acceptance rate than NeurIPS for LLM-only work."}
+{"id":"anthropic-builder-day-2026","name":"Anthropic Builder Day 2026","category":"industry","startDate":"2026-10-22","endDate":"2026-10-22","city":"San Francisco, CA","country":"USA","format":"hybrid","paperDeadline":null,"registrationOpen":false,"themes":["Claude Code","MCP","agent SDK","Claude API"],"url":"https://www.anthropic.com/events","notes":"Anthropic's annual builder event. Claude Code + MCP + Agent SDK announcements."}
+{"id":"emnlp-2026","name":"EMNLP 2026","category":"research","startDate":"2026-11-15","endDate":"2026-11-19","city":"Doha","country":"Qatar","format":"in-person","paperDeadline":"2026-06-15","registrationOpen":false,"themes":["empirical methods in NLP","evaluation","multilingual"],"url":"https://2026.emnlp.org","notes":"Empirical Methods in Natural Language Processing. Companion to ACL."}
+{"id":"aws-reinvent-2026","name":"AWS re:Invent 2026","category":"industry","startDate":"2026-11-30","endDate":"2026-12-04","city":"Las Vegas, NV","country":"USA","format":"hybrid","paperDeadline":null,"registrationOpen":false,"themes":["Bedrock","Trainium","AI infrastructure","enterprise AI"],"url":"https://reinvent.awsevents.com","notes":"AWS's annual customer conference. Major Bedrock + Trainium announcements; Anthropic typically appears in keynotes."}
+{"id":"neurips-2026","name":"NeurIPS 2026","category":"research","startDate":"2026-12-08","endDate":"2026-12-13","city":"Vancouver","country":"Canada","format":"hybrid","paperDeadline":"2026-05-15","registrationOpen":false,"themes":["neural networks","foundation models","AGI","datasets","safety"],"url":"https://neurips.cc/Conferences/2026","notes":"Largest AI/ML research conference. 15k+ attendees. Datasets + Benchmarks track is the canonical venue for new evaluations."}

2026-05-24/embeddings.jsonl ADDED Viewed

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+{"id":"text-embedding-3-large","name":"text-embedding-3-large","provider":"OpenAI","type":"embedding","dimensions":3072,"maxInputTokens":8191,"pricePer1MTokens":0.13,"pricingNote":"$0.13 per 1M input tokens. Reducible-dimensions: pass `dimensions` to truncate to 256/1024/etc with minor quality loss.","openSource":false,"license":"Proprietary","released":"2024-01-25","notes":"OpenAI flagship embedding. Strong on English retrieval; supports Matryoshka truncation to lower dimensions for cheaper storage.","multilingual":true,"url":"https://platform.openai.com/docs/guides/embeddings","mtebAvg":64.6}
+{"id":"text-embedding-3-small","name":"text-embedding-3-small","provider":"OpenAI","type":"embedding","dimensions":1536,"maxInputTokens":8191,"pricePer1MTokens":0.02,"pricingNote":"$0.02 per 1M input tokens. The default budget choice for English RAG.","openSource":false,"license":"Proprietary","released":"2024-01-25","notes":"OpenAI budget embedding. 5x cheaper than ada-002 with better quality. Good default for most RAG agents.","multilingual":true,"url":"https://platform.openai.com/docs/guides/embeddings","mtebAvg":62.3}
+{"id":"voyage-3-large","name":"voyage-3-large","provider":"Voyage AI","type":"embedding","dimensions":1024,"maxInputTokens":32000,"pricePer1MTokens":0.18,"pricingNote":"$0.18 per 1M input tokens. Recommended by Anthropic in the Claude docs.","openSource":false,"license":"Proprietary","released":"2025-01-07","notes":"Top of the MTEB English leaderboard most of 2025. Supports Matryoshka truncation. Strong on long-document retrieval.","multilingual":true,"url":"https://docs.voyageai.com/docs/embeddings","mtebAvg":67}
+{"id":"voyage-3","name":"voyage-3","provider":"Voyage AI","type":"embedding","dimensions":1024,"maxInputTokens":32000,"pricePer1MTokens":0.06,"pricingNote":"$0.06 per 1M input tokens. Best price/quality trade-off in the Voyage line.","openSource":false,"license":"Proprietary","released":"2024-09-18","notes":"Voyage workhorse. 32k context, multilingual, MTEB-competitive at a third the cost of voyage-3-large.","multilingual":true,"url":"https://docs.voyageai.com/docs/embeddings","mtebAvg":63.5}
+{"id":"voyage-3-lite","name":"voyage-3-lite","provider":"Voyage AI","type":"embedding","dimensions":512,"maxInputTokens":32000,"pricePer1MTokens":0.02,"pricingNote":"$0.02 per 1M input tokens. Cheapest tier in the Voyage family.","openSource":false,"license":"Proprietary","released":"2024-09-18","notes":"Budget tier. 512-dim vectors keep storage costs low. Useful for very large corpora where retrieval recall matters less than ingest cost.","multilingual":true,"url":"https://docs.voyageai.com/docs/embeddings","mtebAvg":60}
+{"id":"voyage-code-3","name":"voyage-code-3","provider":"Voyage AI","type":"embedding","dimensions":1024,"maxInputTokens":32000,"pricePer1MTokens":0.18,"pricingNote":"$0.18 per 1M input tokens. Code-specialized.","openSource":false,"license":"Proprietary","released":"2024-12-05","notes":"Specialized for code-search agents. Strong on cross-language retrieval (e.g. natural-language query against a Python+Go+Rust monorepo).","multilingual":true,"url":"https://docs.voyageai.com/docs/embeddings","mtebAvg":null}
+{"id":"embed-multilingual-v3.0","name":"embed-multilingual-v3.0","provider":"Cohere","type":"embedding","dimensions":1024,"maxInputTokens":512,"pricePer1MTokens":0.1,"pricingNote":"$0.10 per 1M input tokens. 100+ languages.","openSource":false,"license":"Proprietary","released":"2023-11-02","notes":"Cohere multilingual flagship. 100+ languages with strong cross-lingual retrieval. Short input limit (512 tokens) is the main constraint.","multilingual":true,"url":"https://docs.cohere.com/docs/embeddings","mtebAvg":64}
+{"id":"embed-english-v3.0","name":"embed-english-v3.0","provider":"Cohere","type":"embedding","dimensions":1024,"maxInputTokens":512,"pricePer1MTokens":0.1,"pricingNote":"$0.10 per 1M input tokens.","openSource":false,"license":"Proprietary","released":"2023-11-02","notes":"English-only sibling of embed-multilingual-v3. Slightly stronger on English-only corpora.","multilingual":false,"url":"https://docs.cohere.com/docs/embeddings","mtebAvg":64.5}
+{"id":"gemini-embedding-001","name":"gemini-embedding-001","provider":"Google","type":"embedding","dimensions":3072,"maxInputTokens":2048,"pricePer1MTokens":0.15,"pricingNote":"$0.15 per 1M input tokens. Supports Matryoshka.","openSource":false,"license":"Proprietary","released":"2025-03-07","notes":"Google flagship embedding from the Gemini family. Strong multilingual. Available via Vertex AI and the Gemini API.","multilingual":true,"url":"https://ai.google.dev/gemini-api/docs/embeddings","mtebAvg":68.3}
+{"id":"text-embedding-005","name":"text-embedding-005","provider":"Google","type":"embedding","dimensions":768,"maxInputTokens":2048,"pricePer1MTokens":0.025,"pricingNote":"$0.025 per 1M input tokens. Vertex AI only.","openSource":false,"license":"Proprietary","released":"2024-11-14","notes":"Google budget tier. 768-dim, English-focused, cheapest of the Vertex AI embeddings.","multilingual":false,"url":"https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings","mtebAvg":null}
+{"id":"mistral-embed","name":"mistral-embed","provider":"Mistral","type":"embedding","dimensions":1024,"maxInputTokens":8000,"pricePer1MTokens":0.1,"pricingNote":"$0.10 per 1M input tokens via la Plateforme.","openSource":false,"license":"Proprietary","released":"2024-02-26","notes":"European data residency option. Solid English/French/German performance. Same pricing tier as Cohere but with longer context.","multilingual":true,"url":"https://docs.mistral.ai/capabilities/embeddings/","mtebAvg":60.7}
+{"id":"jina-embeddings-v3","name":"jina-embeddings-v3","provider":"Jina AI","type":"embedding","dimensions":1024,"maxInputTokens":8192,"pricePer1MTokens":0.02,"pricingNote":"$0.02 per 1M input tokens (Jina API). Free for self-hosting under Apache 2.0.","openSource":true,"license":"CC-BY-NC-4.0","released":"2024-09-18","notes":"Open-weights multilingual embedding. Strong on long documents. Adapter-based: same model serves retrieval, classification, separation tasks via task-specific LoRAs.","multilingual":true,"url":"https://jina.ai/embeddings/","mtebAvg":65.5}
+{"id":"nomic-embed-text-v1.5","name":"nomic-embed-text-v1.5","provider":"Nomic AI","type":"embedding","dimensions":768,"maxInputTokens":8192,"pricePer1MTokens":null,"pricingNote":"Open weights. Free to self-host. Hosted via Nomic Atlas at $0.01 per 1M tokens.","openSource":true,"license":"Apache-2.0","released":"2024-02-14","notes":"Open-source English embedding with Matryoshka support (truncate to 256/512/768). Reproducible training data; one of the few fully open embeddings.","multilingual":false,"url":"https://blog.nomic.ai/posts/nomic-embed-matryoshka","mtebAvg":62.3}
+{"id":"mxbai-embed-large-v1","name":"mxbai-embed-large-v1","provider":"Mixedbread","type":"embedding","dimensions":1024,"maxInputTokens":512,"pricePer1MTokens":null,"pricingNote":"Open weights. Free to self-host. Hosted via Mixedbread API at $0.05 per 1M tokens.","openSource":true,"license":"Apache-2.0","released":"2024-03-07","notes":"Apache-licensed dense retriever. Strong English performance. Short input limit (512) is the main constraint vs Voyage/Jina.","multilingual":false,"url":"https://www.mixedbread.com/docs/embeddings/overview","mtebAvg":64.7}
+{"id":"bge-m3","name":"bge-m3","provider":"BAAI","type":"embedding","dimensions":1024,"maxInputTokens":8192,"pricePer1MTokens":null,"pricingNote":"Open weights. Free to self-host. Available through most inference providers (Together, DeepInfra, Replicate).","openSource":true,"license":"MIT","released":"2024-01-30","notes":"Multi-functional, multi-lingual, multi-granularity. Outputs dense + sparse + multi-vector representations from a single model. Strong on long-document multilingual retrieval.","multilingual":true,"url":"https://huggingface.co/BAAI/bge-m3","mtebAvg":64.5}
+{"id":"rerank-v3.5","name":"rerank-v3.5","provider":"Cohere","type":"reranker","dimensions":null,"maxInputTokens":4096,"pricePer1MTokens":0,"pricingNote":"$2 per 1k searches (each search = up to 100 documents reranked).","openSource":false,"license":"Proprietary","released":"2024-12-03","notes":"Cohere flagship reranker. Strong multi-lingual reranking with 4k document context. The reranker that most production RAG agents are using as of 2026.","multilingual":true,"url":"https://docs.cohere.com/docs/rerank-2","mtebAvg":null}
+{"id":"rerank-2","name":"rerank-2","provider":"Voyage AI","type":"reranker","dimensions":null,"maxInputTokens":16000,"pricePer1MTokens":0.05,"pricingNote":"$0.05 per 1M tokens (query + documents combined).","openSource":false,"license":"Proprietary","released":"2024-08-09","notes":"Voyage reranker. 16k context per document is unusual; useful for reranking long-document chunks without summarization.","multilingual":true,"url":"https://docs.voyageai.com/docs/reranker","mtebAvg":null}
+{"id":"jina-reranker-v2","name":"jina-reranker-v2-base-multilingual","provider":"Jina AI","type":"reranker","dimensions":null,"maxInputTokens":1024,"pricePer1MTokens":0.02,"pricingNote":"$0.02 per 1M tokens via Jina API. Free to self-host.","openSource":true,"license":"CC-BY-NC-4.0","released":"2024-07-04","notes":"Open-weights reranker. 100+ languages. Smaller context than Cohere/Voyage but free to self-host.","multilingual":true,"url":"https://jina.ai/reranker/","mtebAvg":null}

2026-05-24/embodied-ai.jsonl ADDED Viewed

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+{"id":"pi-0","name":"pi-0","org":"Physical Intelligence","category":"foundation_model","parameters":"3.3B","released":"2024-10","license":"Apache-2.0 (open weights)","paperUrl":"https://www.physicalintelligence.company/blog/pi0","codeUrl":"https://github.com/Physical-Intelligence/openpi","demoUrl":"https://www.physicalintelligence.company","notes":"Generalist VLA built on PaliGemma. Trained on 10K+ hours of cross-embodiment teleoperation data. The open release that broadly shifted the field toward VLA foundation models."}
+{"id":"pi-0.5","name":"pi-0.5","org":"Physical Intelligence","category":"foundation_model","parameters":"3.3B","released":"2025-04","license":"open weights (research)","paperUrl":"https://www.physicalintelligence.company/blog/pi05","codeUrl":"https://github.com/Physical-Intelligence/openpi","demoUrl":"https://www.physicalintelligence.company","notes":"Successor to pi-0 with open-world generalization to homes the model never saw during training. Demonstrated end-to-end household tasks in unseen kitchens and bedrooms."}
+{"id":"gr00t-n1","name":"GR00T N1","org":"NVIDIA","category":"foundation_model","parameters":"2B","released":"2025-03","license":"open weights","paperUrl":"https://research.nvidia.com/labs/gear/gr00t/","codeUrl":"https://huggingface.co/nvidia/GR00T-N1-2B","demoUrl":"https://www.nvidia.com/en-us/ai/gr00t/","notes":"NVIDIA dual-system VLA targeting humanoids: System-2 reasoning over a vision-language backbone, System-1 diffusion policy. First open NVIDIA humanoid foundation model."}
+{"id":"rt-2","name":"RT-2","org":"Google DeepMind","category":"foundation_model","parameters":"55B","released":"2023-07","license":"proprietary","paperUrl":"https://robotics-transformer2.github.io","codeUrl":null,"demoUrl":null,"notes":"First VLM-to-action transformer. PaLM-E-class backbone outputs robot actions as tokens. Closed but seeded the entire VLA category."}
+{"id":"openvla","name":"OpenVLA","org":"Stanford / Berkeley / Toyota Research","category":"foundation_model","parameters":"7B","released":"2024-06","license":"MIT","paperUrl":"https://openvla.github.io","codeUrl":"https://github.com/openvla/openvla","demoUrl":"https://huggingface.co/openvla/openvla-7b","notes":"Open replication of RT-2 trained on Open X-Embodiment. The reference open VLA before pi-0; still widely fine-tuned for academic robotics work."}
+{"id":"octo","name":"Octo","org":"Berkeley AI Research","category":"foundation_model","parameters":"93M","released":"2024-05","license":"MIT","paperUrl":"https://octo-models.github.io","codeUrl":"https://github.com/octo-models/octo","demoUrl":null,"notes":"Small generalist transformer policy (93M and 27M variants) trained on 800K Open X-Embodiment trajectories. Designed as a fine-tunable base."}
+{"id":"rdt-1b","name":"RDT-1B","org":"Tsinghua University","category":"foundation_model","parameters":"1.2B","released":"2024-10","license":"MIT","paperUrl":"https://rdt-robotics.github.io/rdt-robotics/","codeUrl":"https://github.com/thu-ml/RoboticsDiffusionTransformer","demoUrl":null,"notes":"Largest open bimanual manipulation diffusion transformer at release. Pretrained on 1M+ multi-robot episodes, fine-tuned for bimanual ALOHA-class hardware."}
+{"id":"helix","name":"Helix","org":"Figure AI","category":"foundation_model","parameters":"undisclosed","released":"2025-02","license":"proprietary","paperUrl":"https://www.figure.ai/news/helix","codeUrl":null,"demoUrl":"https://www.figure.ai","notes":"Dual-system VLA powering Figure 02. Runs entirely onboard the humanoid (no cloud), controls both arms at 200Hz. First commercial humanoid foundation model in production."}
+{"id":"figure-02","name":"Figure 02","org":"Figure AI","category":"humanoid","parameters":null,"released":"2024-08","license":"commercial","paperUrl":"https://www.figure.ai/news/introducing-figure-02","codeUrl":null,"demoUrl":"https://www.figure.ai","notes":"5'6\", 70kg humanoid with onboard NVIDIA compute. Shipping in BMW and other industrial pilots. Helix VLA runs locally on the robot."}
+{"id":"1x-neo","name":"1X NEO","org":"1X Technologies","category":"humanoid","parameters":null,"released":"2025-10","license":"commercial (consumer)","paperUrl":"https://www.1x.tech/neo","codeUrl":null,"demoUrl":"https://www.1x.tech","notes":"First humanoid pitched as a household consumer product. Soft, lightweight (30kg) with tendon-driven joints for safety around people. Pre-orders opened late 2025."}
+{"id":"tesla-optimus-gen3","name":"Optimus Gen 3","org":"Tesla","category":"humanoid","parameters":null,"released":"2025-10","license":"commercial","paperUrl":"https://www.tesla.com/AI","codeUrl":null,"demoUrl":"https://www.tesla.com/AI","notes":"Third-generation Tesla humanoid with redesigned hand (22 DoF). Tesla manufacturing factory deployment claimed for 2026, external sales 2027."}
+{"id":"apptronik-apollo","name":"Apollo","org":"Apptronik","category":"humanoid","parameters":null,"released":"2024-08","license":"commercial","paperUrl":"https://apptronik.com/apollo","codeUrl":null,"demoUrl":"https://apptronik.com","notes":"Industrial humanoid pilots with Mercedes and GXO logistics. Built on Apptronik's prior Astra arm work. NASA partnership."}
+{"id":"unitree-g1","name":"Unitree G1","org":"Unitree","category":"humanoid","parameters":null,"released":"2024-05","license":"commercial","paperUrl":"https://www.unitree.com/g1","codeUrl":"https://github.com/unitreerobotics","demoUrl":"https://www.unitree.com/g1","notes":"Lowest-priced commercially available humanoid (entry around $16K). Popular for academic research and home tinkering. SDK and Python bindings published."}
+{"id":"unitree-h1","name":"Unitree H1","org":"Unitree","category":"humanoid","parameters":null,"released":"2023-12","license":"commercial","paperUrl":"https://www.unitree.com/h1","codeUrl":"https://github.com/unitreerobotics","demoUrl":"https://www.unitree.com/h1","notes":"Larger sibling to G1. Holds the unofficial humanoid sprint record (3.3 m/s). Common research platform for whole-body control papers."}
+{"id":"boston-dynamics-atlas-electric","name":"Atlas (Electric)","org":"Boston Dynamics","category":"humanoid","parameters":null,"released":"2024-04","license":"commercial (research / pilot)","paperUrl":"https://bostondynamics.com/blog/electric-new-era-for-atlas/","codeUrl":null,"demoUrl":"https://bostondynamics.com/atlas/","notes":"All-electric Atlas successor to the hydraulic platform. Hyundai pilots in automotive manufacturing. Range of motion exceeds human anatomy."}
+{"id":"agility-digit","name":"Digit","org":"Agility Robotics","category":"humanoid","parameters":null,"released":"2023-09","license":"commercial","paperUrl":"https://agilityrobotics.com/products/digit","codeUrl":null,"demoUrl":"https://agilityrobotics.com","notes":"Bipedal humanoid optimized for warehouse case-handling. RaaS pricing with Amazon and GXO deployments. Bird-leg morphology (knees backward) for energy efficiency."}
+{"id":"sanctuary-phoenix","name":"Phoenix","org":"Sanctuary AI","category":"humanoid","parameters":null,"released":"2023-05","license":"commercial","paperUrl":"https://www.sanctuary.ai/phoenix","codeUrl":null,"demoUrl":"https://www.sanctuary.ai","notes":"Hydraulic-driven hands with 21 DoF per hand, the highest dexterity in any commercial humanoid. Now part of Apptronik post-2025 acquisition."}
+{"id":"open-x-embodiment","name":"Open X-Embodiment","org":"Google DeepMind + 21 institutions","category":"dataset","parameters":null,"released":"2023-10","license":"CC-BY-4.0","paperUrl":"https://robotics-transformer-x.github.io","codeUrl":"https://github.com/google-deepmind/open_x_embodiment","demoUrl":"https://huggingface.co/datasets/jxu124/OpenX-Embodiment","notes":"Standardized cross-embodiment dataset spanning 22 robot embodiments and 1M+ trajectories. The pretraining substrate behind Octo, OpenVLA, and many followups."}
+{"id":"droid","name":"DROID","org":"Stanford / Berkeley / Toyota Research / Google","category":"dataset","parameters":null,"released":"2024-03","license":"CC-BY-4.0","paperUrl":"https://droid-dataset.github.io","codeUrl":"https://github.com/droid-dataset/droid","demoUrl":"https://huggingface.co/datasets/KarlP/droid","notes":"76K teleoperated trajectories across 564 scenes and 86 tasks, all on Franka arms. Largest single-embodiment manipulation dataset. Used as the high-quality slice in pi-0 training."}
+{"id":"agibot-world","name":"AgiBot World","org":"AgiBot","category":"dataset","parameters":null,"released":"2024-12","license":"CC-BY-NC-4.0","paperUrl":"https://agibot-world.com","codeUrl":"https://huggingface.co/datasets/agibot-world/AgiBotWorld-Alpha","demoUrl":"https://agibot-world.com","notes":"Million-trajectory dataset on AgiBot G1 humanoid. Contains long-horizon dual-arm manipulation in real homes and offices. Released alongside the AgiBot platform."}
+{"id":"mobile-aloha","name":"Mobile ALOHA","org":"Stanford","category":"dataset","parameters":null,"released":"2024-01","license":"MIT","paperUrl":"https://mobile-aloha.github.io","codeUrl":"https://github.com/MarkFzp/mobile-aloha","demoUrl":"https://mobile-aloha.github.io","notes":"Open hardware bimanual mobile manipulator (~$32K) plus a 50-task imitation-learning dataset. The reference open platform for mobile bimanual research."}
+{"id":"bridgedata-v2","name":"BridgeData V2","org":"Berkeley AI Research","category":"dataset","parameters":null,"released":"2023-08","license":"CC-BY-4.0","paperUrl":"https://rail-berkeley.github.io/bridgedata","codeUrl":"https://github.com/rail-berkeley/bridge_data_v2","demoUrl":null,"notes":"60K+ trajectories on WidowX arms across 24 environments. Foundational for skill generalization research; included in Open X-Embodiment."}
+{"id":"isaac-lab","name":"Isaac Lab","org":"NVIDIA","category":"simulator","parameters":null,"released":"2024-03","license":"BSD-3-Clause","paperUrl":"https://isaac-sim.github.io/IsaacLab/","codeUrl":"https://github.com/isaac-sim/IsaacLab","demoUrl":"https://developer.nvidia.com/isaac-sim","notes":"GPU-accelerated robot learning framework on Isaac Sim. Supersedes Isaac Gym. Used for sim-to-real RL training of locomotion and manipulation policies."}
+{"id":"mujoco-playground","name":"MuJoCo Playground","org":"Google DeepMind","category":"simulator","parameters":null,"released":"2025-01","license":"Apache-2.0","paperUrl":"https://playground.mujoco.org","codeUrl":"https://github.com/google-deepmind/mujoco_playground","demoUrl":"https://playground.mujoco.org","notes":"JAX-based MuJoCo training suite with battery-included locomotion and manipulation environments. Designed for massively parallel sim-to-real RL."}
+{"id":"genesis","name":"Genesis","org":"Genesis Embodied AI","category":"simulator","parameters":null,"released":"2024-12","license":"Apache-2.0","paperUrl":"https://genesis-embodied-ai.github.io","codeUrl":"https://github.com/Genesis-Embodied-AI/Genesis","demoUrl":"https://genesis-embodied-ai.github.io","notes":"Universal physics engine claiming 80M FPS on a single RTX 4090. Bundled generative pipeline auto-creates scenes from text. Open-sourced by a 19-lab collaboration."}

2026-05-24/fine-tuning.jsonl ADDED Viewed

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+{"id":"openai-finetune","name":"OpenAI Fine-Tuning","vendor":"OpenAI","type":"first-party","baseModels":["GPT-4o","GPT-4o-mini","GPT-4.1","GPT-4.1-mini","o4-mini"],"methods":["full","dpo","rlhf"],"trainingPricing":"$25/1M tokens (GPT-4o); $3/1M (GPT-4o-mini); $25 (GPT-4.1); $5 (GPT-4.1-mini)","inferencePricing":"Roughly 1.5-2x the base model API price","freeTier":"GPT-4o-mini: 2M training tokens/day free until 2025","features":["DPO support","RFT (reinforcement fine-tuning) on o4-mini","OpenAI infrastructure"],"url":"https://platform.openai.com/docs/guides/fine-tuning","notes":"OpenAI's first-party fine-tuning. Strong defaults for instruction-following customization. RFT on o4-mini lets you reward-shape reasoning. No model export."}
+{"id":"anthropic-finetune","name":"Anthropic Fine-Tuning (AWS Bedrock)","vendor":"Anthropic","type":"first-party","baseModels":["Claude Sonnet 4.6","Claude Haiku 4.5"],"methods":["lora"],"trainingPricing":"Custom; from $9/1M training tokens for Haiku 4.5","inferencePricing":"Same per-token rate as base model + provisioned-throughput fee","freeTier":null,"features":["Bedrock-only (AWS)","LoRA adapters","Trained model stays in your AWS account"],"url":"https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-overview.html","notes":"Anthropic exposes Claude fine-tuning only through AWS Bedrock. Adapters; not full weights. Strong fit for AWS-anchored stacks."}
+{"id":"google-vertex-finetune","name":"Google Vertex AI Fine-Tuning","vendor":"Google","type":"first-party","baseModels":["Gemini 2.5 Flash","Gemini 2.5 Pro","PaLM 2","Codey"],"methods":["lora","rlhf"],"trainingPricing":"$8/1M tokens (Gemini 2.5 Flash); $35/1M (Gemini 2.5 Pro)","inferencePricing":"Base model rate + provisioned-throughput fee","freeTier":null,"features":["Supervised fine-tuning","RLHF for Gemini","Distillation pipelines"],"url":"https://cloud.google.com/vertex-ai/generative-ai/docs/models/tune-models","notes":"Vertex AI tuning. Supervised + RLHF supported. Strong fit for GCP-anchored stacks; Vertex tooling is the strongest first-party pipeline observability story."}
+{"id":"mistral-finetune","name":"Mistral Fine-Tuning","vendor":"Mistral","type":"first-party","baseModels":["Mistral Small","Mistral Large","Codestral"],"methods":["lora","full"],"trainingPricing":"$2/1M tokens (Mistral Small); $9/1M (Mistral Large)","inferencePricing":"Roughly 1.5x the base model price","freeTier":"1 free fine-tune per la Plateforme account","features":["LoRA + full SFT","Open weights export available","European data residency"],"url":"https://docs.mistral.ai/capabilities/finetuning/finetuning_overview/","notes":"Mistral's la Plateforme tuning. The only first-party provider that lets you export the fine-tuned weights for self-host."}
+{"id":"together-finetune","name":"Together AI Fine-Tuning","vendor":"Together AI","type":"hosted","baseModels":["Llama 4 Scout/Maverick","Llama 3.x 70B/8B","Mixtral 8x7B/8x22B","Qwen 2.5","Gemma 2"],"methods":["lora","qlora","full","dpo"],"trainingPricing":"$0.40/1M tokens (Llama 3.1 8B); $1.60/1M (Llama 3.1 70B); LoRA-only at half price","inferencePricing":"Same as base model on Together (LoRA serving, no markup)","freeTier":"$5 sign-up credit","features":["Open-weights base only","LoRA + full SFT + DPO","Weight export available","Custom datasets via JSONL"],"url":"https://www.together.ai/products/fine-tuning","notes":"Best price/perf for fine-tuning open-weights models. Weight export is the differentiator vs first-party. The default for \"I want a custom Llama\" workflows."}
+{"id":"fireworks-finetune","name":"Fireworks Fine-Tuning","vendor":"Fireworks AI","type":"hosted","baseModels":["Llama 4 Scout/Maverick","Llama 3.x","Mixtral 8x22B","DeepSeek V3","Qwen 2.5"],"methods":["lora","qlora"],"trainingPricing":"$0.50/1M tokens for most open-weights models","inferencePricing":"Same per-token rate as base model + LoRA serve fee","freeTier":"$1 sign-up credit","features":["LoRA only","Multi-LoRA per base (cheap to switch)","Long-context support"],"url":"https://fireworks.ai/blog/fine-tuning-models-with-fireworks","notes":"LoRA-first hosted tuning. Multi-LoRA serving means many fine-tunes share one base, very cheap to deploy 10s of variants."}
+{"id":"openpipe","name":"OpenPipe","vendor":"OpenPipe","type":"hosted","baseModels":["Llama 3.x","Mistral 7B","Qwen 2.5"],"methods":["lora","full"],"trainingPricing":"$1/1M tokens","inferencePricing":"$1.20/1M tokens (Mistral 7B fine-tune); volume discounts","freeTier":"1M training tokens free","features":["Distill from GPT-4 traces","Auto-eval pipeline","A/B test against base model"],"url":"https://openpipe.ai","notes":"Distillation-first: pipe production GPT-4 traffic, distill into a cheaper fine-tuned open model. The default workflow for \"make my expensive prompts cheaper.\""}
+{"id":"predibase","name":"Predibase","vendor":"Predibase","type":"hosted","baseModels":["Llama 3.x","Mistral 7B","Qwen 2.5","Solar 10.7B"],"methods":["lora","qlora","full"],"trainingPricing":"$0.50/1M tokens","inferencePricing":"Pay-per-token; multi-LoRA serving","freeTier":"Trial credits","features":["Turbo LoRA (faster training)","Unlimited adapters per base","Adapter hot-swap inference"],"url":"https://predibase.com","notes":"Production fine-tuning + serving with strong adapter management. The platform behind Lorax (open-source LoRA serving)."}
+{"id":"huggingface-autotrain","name":"Hugging Face AutoTrain","vendor":"Hugging Face","type":"hosted","baseModels":["Most HuggingFace open-weights models"],"methods":["lora","full","dpo"],"trainingPricing":"GPU-time billed; ~$1.40/hr for A10G","inferencePricing":"Inference Endpoints separately billed (~$0.50-$5/hr)","freeTier":"Free for non-GPU jobs","features":["Browser-only training","Spaces integration","Push to Hub"],"url":"https://huggingface.co/autotrain","notes":"Easiest no-code fine-tuning. Browser UI; trained model lands in your HuggingFace account. Best for prototyping and educational use."}
+{"id":"aws-bedrock-finetune","name":"AWS Bedrock Fine-Tuning","vendor":"Amazon Web Services","type":"hosted","baseModels":["Claude Sonnet/Haiku","Llama 3.x","Titan","Cohere Command"],"methods":["lora","continued-pretraining"],"trainingPricing":"Provider-specific (e.g. Claude Haiku $9/1M tokens; Titan Express $15/1M)","inferencePricing":"Provisioned throughput model: $/hour rate per model unit","freeTier":null,"features":["Continued pretraining","Cross-region inference","Bedrock Guardrails included","Tied to AWS IAM"],"url":"https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-overview.html","notes":"AWS-native fine-tuning across many providers. Provisioned throughput billing (not per-token) makes pricing predictable but expensive at low volume."}
+{"id":"replicate-finetune","name":"Replicate Fine-Tuning","vendor":"Replicate","type":"hosted","baseModels":["Llama 3.x","FLUX (image)","SDXL","StyleGAN"],"methods":["lora"],"trainingPricing":"GPU-time; ~$0.001-$0.01/sec","inferencePricing":"Per-second GPU billing on the fine-tuned model","freeTier":"Free trial credit","features":["Image LoRA fine-tuning standout","API-driven","Webhook-on-completion"],"url":"https://replicate.com/docs/guides/fine-tune-an-image-model","notes":"Strongest image LoRA fine-tuning experience (FLUX, SDXL). Less competitive on text-LLM fine-tuning vs Together / Fireworks."}
+{"id":"modal-finetune","name":"Modal Labs (DIY)","vendor":"Modal","type":"hosted","baseModels":["Any (BYO code)","Llama 3.x recipes published"],"methods":["lora","qlora","full","dpo","rlhf","continued-pretraining"],"trainingPricing":"GPU-time billing; H100 ~$3.95/hr","inferencePricing":"GPU-time billing on serving function","freeTier":"$30/mo compute credit","features":["Full BYO control","Serverless GPU","Distributed training","Open-source recipes"],"url":"https://modal.com/docs/examples/llm-finetuning","notes":"BYO fine-tuning infra. You own the code; Modal owns the GPU scheduling. The right answer if your tuning recipe does not fit a turn-key provider."}

2026-05-24/frameworks.jsonl ADDED Viewed

	@@ -0,0 +1,15 @@

+{"id":"langchain","name":"LangChain","vendor":"LangChain Inc.","languages":["python","typescript"],"version":"0.3.x","released":"2022-10-22","license":"MIT","githubStarsK":95,"weeklyInstallsK":4200,"category":"agent-orchestration","features":["chains","tools","memory","tracing (LangSmith)","document loaders","500+ integrations"],"url":"https://www.langchain.com","github":"https://github.com/langchain-ai/langchain","notes":"The most-installed Python agent framework. Reorganized in v0.3 around langchain-core + provider packages to reduce churn. Pairs tightly with LangGraph for multi-step workflows and LangSmith for tracing."}
+{"id":"langgraph","name":"LangGraph","vendor":"LangChain Inc.","languages":["python","typescript"],"version":"0.2.x","released":"2024-01-17","license":"MIT","githubStarsK":18,"weeklyInstallsK":1100,"category":"agent-orchestration","features":["stateful graphs","checkpointing","human-in-the-loop","streaming","time-travel"],"url":"https://langchain-ai.github.io/langgraph/","github":"https://github.com/langchain-ai/langgraph","notes":"Stateful agent graphs on top of LangChain. The framework most production agents have moved to since 2024 because of its first-class checkpointing and time-travel debugging. create_react_agent is the most-used helper."}
+{"id":"llamaindex","name":"LlamaIndex","vendor":"LlamaIndex Inc.","languages":["python","typescript"],"version":"0.12.x","released":"2022-11-22","license":"MIT","githubStarsK":42,"weeklyInstallsK":1900,"category":"rag","features":["document loaders","indexes","query engines","agents","workflows","observability"],"url":"https://www.llamaindex.ai","github":"https://github.com/run-llama/llama_index","notes":"RAG-first framework. Strong on document ingestion, indexing strategies, and query rewriting. Workflows API (introduced 2024) is the agent-orchestration layer; competitive with LangGraph for retrieval-heavy use cases."}
+{"id":"autogen","name":"AutoGen","vendor":"Microsoft","languages":["python"],"version":"0.4.x","released":"2023-09-25","license":"CC-BY-4.0","githubStarsK":38,"weeklyInstallsK":350,"category":"multi-agent","features":["conversable agents","group chat","code execution","human approval","event-driven"],"url":"https://microsoft.github.io/autogen/","github":"https://github.com/microsoft/autogen","notes":"Microsoft Research multi-agent framework. v0.4 is the redesign: event-driven, async, and split into core/agentchat/extensions. Strong for agent-to-agent simulation and conversational multi-agent setups."}
+{"id":"crewai","name":"CrewAI","vendor":"crewAI Inc.","languages":["python"],"version":"0.86.x","released":"2023-12-12","license":"MIT","githubStarsK":25,"weeklyInstallsK":480,"category":"multi-agent","features":["roles","tasks","crews","flows","tool registry"],"url":"https://www.crewai.com","github":"https://github.com/crewAIInc/crewAI","notes":"Role-based multi-agent framework. The \"Agent + Task + Crew\" abstraction maps cleanly onto how teams actually think about delegation. Hugely popular for marketing/research/sales agent setups."}
+{"id":"pydantic-ai","name":"Pydantic AI","vendor":"Pydantic","languages":["python"],"version":"0.0.x","released":"2024-12-02","license":"MIT","githubStarsK":8.5,"weeklyInstallsK":220,"category":"agent-orchestration","features":["type-safe agents","pydantic models","streaming","logfire integration","function calling"],"url":"https://ai.pydantic.dev","github":"https://github.com/pydantic/pydantic-ai","notes":"Type-safe agent framework from the Pydantic team. Strong fit for Python codebases that already use Pydantic for data validation. Light, opinionated, and fast-growing in 2025-2026."}
+{"id":"mastra","name":"Mastra","vendor":"Mastra","languages":["typescript"],"version":"0.4.x","released":"2024-09-12","license":"Elastic License v2","githubStarsK":12,"weeklyInstallsK":95,"category":"agent-orchestration","features":["workflows","agents","rag","evals","memory","voice"],"url":"https://mastra.ai","github":"https://github.com/mastra-ai/mastra","notes":"TypeScript-first agent framework, built by the team behind Gatsby. Targets Node.js/Next.js stacks where most agent libraries are Python-only. Strong DX with first-class evals."}
+{"id":"openai-agents-sdk","name":"OpenAI Agents SDK","vendor":"OpenAI","languages":["python","typescript"],"version":"0.1.x","released":"2025-03-12","license":"MIT","githubStarsK":16,"weeklyInstallsK":750,"category":"sdk","features":["handoffs","guardrails","tracing","sessions","voice agents"],"url":"https://openai.github.io/openai-agents-python/","github":"https://github.com/openai/openai-agents-python","notes":"OpenAI's official agent SDK. Handoffs are first-class for multi-agent. Tightly integrates with OpenAI tracing. Use this if you are OpenAI-only; otherwise LangGraph or Pydantic AI are usually a better fit."}
+{"id":"claude-agent-sdk","name":"Claude Agent SDK","vendor":"Anthropic","languages":["python","typescript"],"version":"0.2.x","released":"2025-09-29","license":"MIT","githubStarsK":6.5,"weeklyInstallsK":280,"category":"sdk","features":["claude code core","mcp servers","hooks","subagents","slash commands"],"url":"https://docs.anthropic.com/en/docs/claude-code/sdk/sdk-overview","github":"https://github.com/anthropics/claude-agent-sdk-python","notes":"The Claude Code core, repackaged as a programmable SDK. Native MCP, hooks, and subagent orchestration. Best fit if your agent needs the same surface area as Claude Code."}
+{"id":"vercel-ai-sdk","name":"Vercel AI SDK","vendor":"Vercel","languages":["typescript","javascript"],"version":"4.x","released":"2023-04-21","license":"Apache-2.0","githubStarsK":12,"weeklyInstallsK":1300,"category":"sdk","features":["streaming UI","tool calling","structured output","multi-provider","react/svelte/vue hooks"],"url":"https://sdk.vercel.ai","github":"https://github.com/vercel/ai","notes":"TypeScript-first AI SDK. Best in class for streaming UI in Next.js/React apps. v4 added agent tools and multi-step generation. Most-used AI library in JS-land."}
+{"id":"agno","name":"Agno","vendor":"Agno","languages":["python"],"version":"1.x","released":"2024-08-15","license":"MPL-2.0","githubStarsK":22,"weeklyInstallsK":165,"category":"agent-orchestration","features":["multi-modal agents","memory","knowledge bases","workflows","monitoring"],"url":"https://www.agno.com","github":"https://github.com/agno-agi/agno","notes":"Phidata rebranded. Lightweight Python framework with first-class multimodal (image, audio, video) agents. Strong observability (Agno Platform). Faster cold-start than LangChain."}
+{"id":"smolagents","name":"smolagents","vendor":"Hugging Face","languages":["python"],"version":"1.x","released":"2024-12-31","license":"Apache-2.0","githubStarsK":17,"weeklyInstallsK":130,"category":"agent-orchestration","features":["code agents","hub integration","multi-step","minimal abstractions"],"url":"https://huggingface.co/docs/smolagents","github":"https://github.com/huggingface/smolagents","notes":"Minimal agent framework from Hugging Face. CodeAgent expresses tool use as Python code (instead of JSON), which often produces better trajectories on agentic-coding benchmarks. ~1k LOC core."}
+{"id":"haystack","name":"Haystack","vendor":"deepset","languages":["python"],"version":"2.x","released":"2020-04-13","license":"Apache-2.0","githubStarsK":19,"weeklyInstallsK":200,"category":"rag","features":["pipelines","document stores","agents","evaluation","hybrid retrieval"],"url":"https://haystack.deepset.ai","github":"https://github.com/deepset-ai/haystack","notes":"One of the original RAG frameworks (predates LLM era). v2 is a clean redesign. Strong for enterprise RAG; agents API now competitive with LangGraph for retrieval-heavy workflows."}
+{"id":"browser-use","name":"browser-use","vendor":"Browser Use","languages":["python"],"version":"0.2.x","released":"2024-11-15","license":"MIT","githubStarsK":60,"weeklyInstallsK":420,"category":"browser-agent","features":["playwright","vision","click/type/scroll","multi-tab","file download"],"url":"https://browser-use.com","github":"https://github.com/browser-use/browser-use","notes":"Open-source browser automation framework for AI agents. Passes web pages as DOM + screenshots to vision LLMs that decide actions. Top WebArena performance for an OSS framework."}
+{"id":"pipecat","name":"Pipecat","vendor":"Daily","languages":["python"],"version":"0.0.x","released":"2024-04-01","license":"BSD-2-Clause","githubStarsK":6.5,"weeklyInstallsK":85,"category":"voice-agent","features":["STT","TTS","WebRTC","turn detection","multi-modal"],"url":"https://www.pipecat.ai","github":"https://github.com/pipecat-ai/pipecat","notes":"Real-time voice agent framework. Pipelines connect STT (Deepgram, Whisper), LLMs, and TTS (Cartesia, ElevenLabs) over WebRTC with sub-second turn-taking. The default OSS stack for production voice agents."}

2026-05-24/funding.jsonl ADDED Viewed

	@@ -0,0 +1,21 @@

+{"id":"anthropic-google-2026-04","company":"Anthropic","category":"frontier-lab","stage":"strategic","amountM":40000,"valuationB":350,"announcedDate":"2026-04-21","leadInvestors":["Google"],"notableInvestors":[],"description":"10-year compute commitment from Google for TPU access. Not a traditional equity round; Google deepens its dual-track AI strategy.","url":"https://www.anthropic.com","sourceUrl":"https://www.anthropic.com/news/google-anthropic-compute-commitment"}
+{"id":"cursor-2026-q1","company":"Anysphere (Cursor)","category":"coding","stage":"series-c","amountM":900,"valuationB":9,"announcedDate":"2026-02-12","leadInvestors":["Thrive Capital","Andreessen Horowitz"],"notableInvestors":["Accel","OpenAI Startup Fund"],"description":"AI-native code editor; largest paid install base of any AI IDE. Round triples valuation in 6 months.","url":"https://cursor.com","sourceUrl":"https://www.cursor.com/blog/series-c"}
+{"id":"cognition-2026-q1","company":"Cognition Labs","category":"coding","stage":"series-b","amountM":500,"valuationB":4,"announcedDate":"2026-01-30","leadInvestors":["Founders Fund"],"notableInvestors":["8VC","Khosla Ventures"],"description":"Builder of Devin (autonomous SWE agent) + DeepWiki retrieval. Round pays for compute scale-up.","url":"https://devin.ai","sourceUrl":"https://www.cognition.ai"}
+{"id":"mistral-2026-q1","company":"Mistral AI","category":"frontier-lab","stage":"series-c","amountM":1500,"valuationB":12,"announcedDate":"2026-03-04","leadInvestors":["Salesforce Ventures","General Catalyst"],"notableInvestors":["Andreessen Horowitz","Lightspeed","Bpifrance"],"description":"European frontier-model lab. Round pegged to la Plateforme + Codestral commercial growth.","url":"https://mistral.ai","sourceUrl":"https://mistral.ai/news/series-c-funding"}
+{"id":"sierra-2026-q1","company":"Sierra","category":"agent","stage":"series-c","amountM":350,"valuationB":4.5,"announcedDate":"2026-03-18","leadInvestors":["Greenoaks Capital"],"notableInvestors":["Sequoia Capital","Benchmark","Thrive Capital"],"description":"Conversational AI for customer support. Founded by Bret Taylor. Tau-Bench creators.","url":"https://sierra.ai","sourceUrl":"https://sierra.ai/blog"}
+{"id":"decagon-2026-q1","company":"Decagon","category":"agent","stage":"series-c","amountM":250,"valuationB":2,"announcedDate":"2026-02-04","leadInvestors":["BOND"],"notableInvestors":["Andreessen Horowitz","Accel"],"description":"AI customer-service agents for enterprise. Counts Eventbrite, Notion, ClassPass as customers.","url":"https://decagon.ai","sourceUrl":"https://decagon.ai/blog"}
+{"id":"glean-2026-q1","company":"Glean","category":"enterprise","stage":"series-f","amountM":260,"valuationB":7.2,"announcedDate":"2026-01-15","leadInvestors":["Altimeter Capital","DST Global"],"notableInvestors":["Coatue","Sequoia Capital"],"description":"Enterprise search + AI assistant. Round signals continued enterprise-AI expansion in 2026.","url":"https://www.glean.com","sourceUrl":"https://www.glean.com/blog/series-f"}
+{"id":"openai-2025-10","company":"OpenAI","category":"frontier-lab","stage":"tender","amountM":6600,"valuationB":157,"announcedDate":"2025-10-02","leadInvestors":["Thrive Capital"],"notableInvestors":["Microsoft","NVIDIA","SoftBank","Khosla Ventures"],"description":"Tender offer at $157B post-money. Largest private round in tech history at time of close.","url":"https://openai.com","sourceUrl":"https://openai.com/index/scale-the-benefits-of-ai/"}
+{"id":"anthropic-2025-08","company":"Anthropic","category":"frontier-lab","stage":"series-f","amountM":4500,"valuationB":60,"announcedDate":"2025-08-12","leadInvestors":["Lightspeed Venture Partners"],"notableInvestors":["Google","Salesforce Ventures","Bessemer Venture Partners"],"description":"Series F at $60B post. Pre-dates the $40B Google compute commitment in April 2026.","url":"https://www.anthropic.com","sourceUrl":"https://www.anthropic.com/news/series-f"}
+{"id":"perplexity-2025-12","company":"Perplexity","category":"agent","stage":"series-d","amountM":500,"valuationB":9,"announcedDate":"2025-12-08","leadInvestors":["IVP"],"notableInvestors":["Andreessen Horowitz","NEA","NVIDIA"],"description":"Answer engine. Round funds product expansion (Comet browser, Pages, finance tools).","url":"https://www.perplexity.ai","sourceUrl":"https://www.perplexity.ai/blog/series-d"}
+{"id":"cohere-2025-q3","company":"Cohere","category":"frontier-lab","stage":"series-d","amountM":500,"valuationB":5.5,"announcedDate":"2025-08-22","leadInvestors":["PSP Investments","Cisco"],"notableInvestors":["NVIDIA","AMD","Salesforce Ventures"],"description":"Enterprise RAG-focused frontier lab. Round positions Cohere as the enterprise AI alternative.","url":"https://cohere.com","sourceUrl":"https://cohere.com/blog/series-d"}
+{"id":"groq-2025-q1","company":"Groq","category":"inference","stage":"series-d","amountM":640,"valuationB":2.8,"announcedDate":"2025-08-05","leadInvestors":["BlackRock"],"notableInvestors":["Cisco","Samsung Catalyst Fund"],"description":"Custom LPU silicon for ultra-fast inference. Round funds capacity expansion + Saudi Arabia data center.","url":"https://groq.com","sourceUrl":"https://groq.com/news_press/groq-raises-640-million-series-d"}
+{"id":"together-2025-q1","company":"Together AI","category":"inference","stage":"series-b","amountM":305,"valuationB":3.3,"announcedDate":"2025-02-20","leadInvestors":["General Catalyst","Prosperity7 Ventures"],"notableInvestors":["Salesforce Ventures","NVIDIA","Lux Capital"],"description":"Inference + fine-tuning hosting for open-weights models. Round funds GPU capacity expansion.","url":"https://www.together.ai","sourceUrl":"https://www.together.ai/blog/series-b"}
+{"id":"sakana-2025-q1","company":"Sakana AI","category":"frontier-lab","stage":"series-a","amountM":200,"valuationB":1.5,"announcedDate":"2025-09-10","leadInvestors":["NVIDIA"],"notableInvestors":["Khosla Ventures","Lux Capital"],"description":"Tokyo-based research lab. Evolutionary model-merging research. The largest non-US, non-China AI seed of 2025.","url":"https://sakana.ai","sourceUrl":"https://sakana.ai/series-a/"}
+{"id":"harvey-2025-q1","company":"Harvey","category":"enterprise","stage":"series-d","amountM":300,"valuationB":3,"announcedDate":"2025-07-23","leadInvestors":["GV (Google Ventures)"],"notableInvestors":["OpenAI Startup Fund","Sequoia","Conviction"],"description":"AI for legal work. Round funds expansion beyond AmLaw 100 to mid-market firms.","url":"https://www.harvey.ai","sourceUrl":"https://www.harvey.ai/blog/series-d"}
+{"id":"crusoe-2025-q1","company":"Crusoe","category":"infra","stage":"series-d","amountM":600,"valuationB":2.8,"announcedDate":"2025-06-04","leadInvestors":["Founders Fund"],"notableInvestors":["Mubadala","Fidelity","NVIDIA"],"description":"AI-first data center operator. Builds GPU clusters powered by stranded methane / clean energy.","url":"https://crusoe.ai","sourceUrl":"https://crusoe.ai/blog/series-d"}
+{"id":"elevenlabs-2025-q1","company":"ElevenLabs","category":"voice","stage":"series-c","amountM":250,"valuationB":3.3,"announcedDate":"2025-01-30","leadInvestors":["Andreessen Horowitz","ICONIQ Growth"],"notableInvestors":["NEA","Sequoia"],"description":"Voice AI. Round funds expansion into agents (conversational AI) and enterprise voice cloning.","url":"https://elevenlabs.io","sourceUrl":"https://elevenlabs.io/blog/series-c-funding"}
+{"id":"cartesia-2025-q1","company":"Cartesia","category":"voice","stage":"series-a","amountM":64,"valuationB":0.4,"announcedDate":"2025-03-17","leadInvestors":["Kleiner Perkins"],"notableInvestors":["Lightspeed","Index Ventures","A* Capital"],"description":"Mamba-architecture TTS. Sub-90ms TTFB. Round funds team scale-up + voice agent platform.","url":"https://cartesia.ai","sourceUrl":"https://cartesia.ai/blog/series-a"}
+{"id":"glean-2025-q3","company":"Glean","category":"enterprise","stage":"series-e","amountM":260,"valuationB":4.6,"announcedDate":"2025-09-10","leadInvestors":["DST Global","Altimeter"],"notableInvestors":["Coatue","General Catalyst"],"description":"Enterprise search + AI assistant. Series E pre-dates the 2026 series F at $7.2B.","url":"https://www.glean.com","sourceUrl":"https://www.glean.com/blog/series-e"}
+{"id":"xai-2024-12","company":"xAI","category":"frontier-lab","stage":"series-c","amountM":6000,"valuationB":50,"announcedDate":"2024-12-23","leadInvestors":["Andreessen Horowitz","Sequoia Capital","Valor Equity Partners"],"notableInvestors":["NVIDIA","AMD","Fidelity","Kingdom Holding Co"],"description":"Elon Musk's frontier lab. Funded the Memphis 200k-GPU Colossus cluster.","url":"https://x.ai","sourceUrl":"https://x.ai/news/series-c"}
+{"id":"openai-2024-10","company":"OpenAI","category":"frontier-lab","stage":"series-c","amountM":6600,"valuationB":157,"announcedDate":"2024-10-02","leadInvestors":["Thrive Capital"],"notableInvestors":["Microsoft","NVIDIA","Khosla Ventures","SoftBank"],"description":"$6.6B round at $157B post. Largest private round in tech history at the time.","url":"https://openai.com","sourceUrl":"https://openai.com/index/scale-the-benefits-of-ai/"}

2026-05-24/gpu-pricing.jsonl ADDED Viewed

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2026-05-24/inference-providers.jsonl ADDED Viewed

	@@ -0,0 +1,8 @@

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2026-05-24/manifest.json ADDED Viewed

	@@ -0,0 +1,283 @@

+{
+  "date": "2026-05-24",
+  "captured_at": "2026-05-24T09:51:06.660669+00:00",
+  "source": "https://tensorfeed.ai",
+  "feeds": {
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+      "endpoint": "/api/benchmarks",
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+    "agents-activity": {
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+      "endpoint": "/api/agents/activity",
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+    "podcasts": {
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+      "endpoint": "/api/podcasts",
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+    "trending-repos": {
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+      "endpoint": "/api/trending-repos",
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+      "bytes": 9950
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+      "endpoint": "/api/probe/latest",
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+    "gpu-pricing": {
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+      "endpoint": "/api/gpu/pricing",
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+    "afta-adopters": {
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+      "endpoint": "/api/afta/adopters",
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+    "ai-hardware": {
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+      "endpoint": "/api/ai-hardware",
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+    "inference-providers": {
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+      "endpoint": "/api/inference-providers",
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+    "training-runs": {
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+    "voice-leaderboards": {
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+      "endpoint": "/api/voice-leaderboards",
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+    },
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+      "endpoint": "/api/multimodal",
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+      "endpoint": "/api/public-leaderboards",
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+    "conferences": {
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+      "endpoint": "/api/conferences",
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+      "bytes": 7912
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+    "model-deprecations": {
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+      "endpoint": "/api/model-deprecations",
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+      "endpoint": "/api/funding",
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+    "model-cards": {
+      "status": "ok",
+      "endpoint": "/api/model-cards",
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+      "bytes": 5421
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+      "status": "ok",
+      "endpoint": "/api/ai-policy",
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+      "bytes": 8639
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+      "status": "ok",
+      "endpoint": "/api/compute-providers",
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+      "bytes": 11268
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+    "usage-rankings": {
+      "status": "ok",
+      "endpoint": "/api/usage-rankings",
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+      "bytes": 5421
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+      "endpoint": "/api/agent-provisioning",
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+      "bytes": 6486
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+      "endpoint": "/api/training-datasets",
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+      "bytes": 8878
+    },
+    "mcp-servers": {
+      "status": "ok",
+      "endpoint": "/api/mcp-servers",
+      "records": 31,
+      "bytes": 12259
+    },
+    "attention": {
+      "status": "ok",
+      "endpoint": "/api/attention",
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+      "bytes": 4464
+    },
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+      "endpoint": "/api/incidents",
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+      "bytes": 28285
+    },
+    "harnesses": {
+      "status": "ok",
+      "endpoint": "/api/harnesses",
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+      "bytes": 1253
+    },
+    "embodied-ai": {
+      "status": "ok",
+      "endpoint": "/api/embodied-ai",
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+      "bytes": 11115
+    },
+    "ai-lawsuits": {
+      "status": "ok",
+      "endpoint": "/api/ai-lawsuits",
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+      "bytes": 15999
+    },
+    "x402-adopters": {
+      "status": "ok",
+      "endpoint": "/api/x402-adopters",
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+      "bytes": 5516
+    },
+    "news-source-health": {
+      "status": "ok",
+      "endpoint": "/api/history/news/sources?date=2026-05-23",
+      "records": 12,
+      "bytes": 2495
+    }
+  }
+}

2026-05-24/marketplaces.jsonl ADDED Viewed

	@@ -0,0 +1,12 @@

+{"id":"gpt-store","name":"GPT Store","vendor":"OpenAI","category":"gpts","itemCount":"3M+","monetization":"Revenue share for top creators (US-only); free for users with ChatGPT Plus","publishingModel":"open","hasAPI":false,"notableItems":["Custom GPTs","Education","Productivity","Research","Programming"],"url":"https://chatgpt.com/gpts","notes":"OpenAI's GPT marketplace. 3M+ GPTs published; revenue-share program for top US creators. No public API for discovery (browser-only)."}
+{"id":"claude-skills","name":"Claude Skills","vendor":"Anthropic","category":"skills","itemCount":"500+","monetization":"Free for users with Claude.ai paid plan; no marketplace fees","publishingModel":"curated","hasAPI":true,"notableItems":["Excel automation","PDF processing","Code review","Data analysis"],"url":"https://claude.ai/skills","notes":"Anthropic's official skill marketplace for Claude. Skills are bundled prompt + tool sets that extend Claude's capabilities. Curated; growing fast."}
+{"id":"huggingface-spaces","name":"Hugging Face Spaces","vendor":"Hugging Face","category":"spaces","itemCount":"500k+","monetization":"Free; ZeroGPU for community demos; HF Pro for private Spaces","publishingModel":"open","hasAPI":true,"notableItems":["Model demos","Eval leaderboards","Gradio apps","Fine-tune trainers"],"url":"https://huggingface.co/spaces","notes":"The largest open AI demo marketplace. Most models on HF have an associated Space showcasing capability. API-discoverable; powers many embedded model demos."}
+{"id":"huggingface-models","name":"Hugging Face Models","vendor":"Hugging Face","category":"models","itemCount":"1.5M+","monetization":"Free hosting; HF Inference Endpoints + Pro for compute","publishingModel":"open","hasAPI":true,"notableItems":["Fine-tunes","Open weights","Quantized variants","LoRA adapters"],"url":"https://huggingface.co/models","notes":"The de facto open AI model registry. Anyone can publish; the central hub the entire open-source ML community indexes against. API-discoverable."}
+{"id":"replicate","name":"Replicate","vendor":"Replicate","category":"models","itemCount":"40k+","monetization":"Pay-per-second of GPU; revenue share for model owners","publishingModel":"open","hasAPI":true,"notableItems":["Image generation","Video models","Voice / TTS","LoRA fine-tunes"],"url":"https://replicate.com","notes":"API-first model marketplace. Per-second GPU billing. Strongest visual / generative model selection (FLUX, SDXL, Veo derivatives, Suno-likes)."}
+{"id":"mcp-registry","name":"MCP Server Registry","vendor":"Model Context Protocol","category":"mcp","itemCount":"12k+","monetization":"Free; open standard","publishingModel":"open","hasAPI":true,"notableItems":["Filesystem servers","Search","Browser","Database","SaaS integrations"],"url":"https://registry.modelcontextprotocol.io","notes":"Official MCP registry. Open submission; growing rapidly. TensorFeed snapshots daily; live count and growth at /api/mcp/registry/snapshot."}
+{"id":"crew-ai-marketplace","name":"CrewAI Marketplace","vendor":"crewAI Inc.","category":"agents","itemCount":"500+","monetization":"Pay-per-execution for some crews; free crews available","publishingModel":"open","hasAPI":false,"notableItems":["Marketing crews","Research crews","Sales crews","Engineering crews"],"url":"https://www.crewai.com","notes":"Marketplace of pre-built CrewAI agent crews. Browse by use-case; install with one command. The strongest framework-native agent marketplace in 2026."}
+{"id":"apify-store","name":"Apify Store","vendor":"Apify","category":"agents","itemCount":"4500+","monetization":"Pay-per-run; revenue share for actor authors","publishingModel":"open","hasAPI":true,"notableItems":["Web scrapers","Data extraction","Browser automation","Site-specific actors"],"url":"https://apify.com/store","notes":"Marketplace of pre-built scraping / automation actors. The strongest pre-built solution for \"I need to scrape X named site\" without writing code."}
+{"id":"replit-agents","name":"Replit Agent Templates","vendor":"Replit","category":"workflows","itemCount":"~200","monetization":"Free templates; bundled with Replit subscription","publishingModel":"curated","hasAPI":false,"notableItems":["Full-stack apps","AI-generated UIs","Agent workflows","Saas starters"],"url":"https://replit.com/agent","notes":"Curated agent-built templates. Replit Agent generates full-stack applications; templates are pre-vetted starting points."}
+{"id":"vercel-marketplace","name":"Vercel AI Marketplace","vendor":"Vercel","category":"plugins","itemCount":"~50","monetization":"Bundled with Vercel deployments; some integrations charge separately","publishingModel":"curated","hasAPI":false,"notableItems":["AI SDK templates","Vector store integrations","Model providers","Auth + email"],"url":"https://vercel.com/marketplace/ai","notes":"Curated integration marketplace for Vercel AI SDK projects. Smaller than HF Spaces but TS-first and tightly integrated with Next.js stacks."}
+{"id":"agent-zero","name":"Agent.ai","vendor":"HubSpot (Dharmesh Shah)","category":"agents","itemCount":"1k+","monetization":"Free directory; some agents paid","publishingModel":"open","hasAPI":false,"notableItems":["Marketing automation","Sales enablement","Lead generation","Customer support"],"url":"https://agent.ai","notes":"Cross-platform AI agent directory built by Dharmesh Shah. Discovers agents across many platforms; growing community of indie agent builders."}
+{"id":"glama-mcp","name":"Glama MCP Marketplace","vendor":"Glama","category":"mcp","itemCount":"6k+","monetization":"Free directory + paid hosted MCP servers","publishingModel":"open","hasAPI":true,"notableItems":["MCP servers","Hosted MCP runtime","Server analytics"],"url":"https://glama.ai/mcp/servers","notes":"Third-party MCP server marketplace. Hosts servers on Glama infra so users do not need to run them locally. Useful for browser-based agents that cannot run stdio servers."}

2026-05-24/mcp-registry.jsonl ADDED Viewed

	@@ -0,0 +1 @@

+ {"ok":true,"summary":{"date":"2026-05-24","capturedAt":"2026-05-24T09:30:37.370Z","total_servers":9658,"total_versions":28976,"by_status":{"active":9626,"deprecated":32},"top_namespaces":[{"namespace":"io.github.pipeworx-io","count":522},{"namespace":"ai.smithery","count":214},{"namespace":"io.github.CSOAI-ORG","count":210},{"namespace":"eu.ansvar","count":105},{"namespace":"io.github.Br0ski777","count":101},{"namespace":"com.mcparmory","count":76},{"namespace":"io.tooloracle","count":61},{"namespace":"io.github.srotzin","count":60},{"namespace":"io.github.codespar","count":57},{"namespace":"io.github.lazymac2x","count":55},{"namespace":"io.github.daedalus","count":49},{"namespace":"io.github.ryudi84","count":49},{"namespace":"io.github.theYahia","count":49},{"namespace":"io.github.cyanheads","count":43},{"namespace":"com.olyport","count":38},{"namespace":"io.github.mindstone","count":36},{"namespace":"io.github.rog0x","count":33},{"namespace":"io.github.rocnubie","count":31},{"namespace":"io.github.wyre-technology","count":31},{"namespace":"com.pulsemcp","count":28}],"new_today":{"count":87,"names":["ai.31st/mcp","ai.dynsoft/sac","ai.fincontext/fincontext","ai.kolens/kolens-mcp","app.cooperpetcare.www/cooper","ca.netgrant/canadian-grants","cloud.agentdomain/agentdomain-mcp","com.heyoden/mcp","com.reelrifter/watchlist","dev.claw-link/clawlink","dev.gvnr/gvnr","dev.vibeseo/vibeseo","io.github.AIweather-Anurag/ottasia","io.github.CU2CU2/aire-channel-bridge","io.github.Compuute/compuute-scan-api","io.github.Jing7ao/aihot-mcp","io.github.Jing7ao/seedance-mcp","io.github.LIONMASTER20/lion-mcp","io.github.NewPlanetWW/mcp-commerce-starter","io.github.Osyanne/osu-mcp","io.github.SnipMCP/gadschain","io.github.aardappvark/gridscoot","io.github.africanmarketos591/mvr-api","io.github.aitor-alt/pixel-squads","io.github.andrijdavid/bazos-mcp","io.github.anp2protocol/anporia-mcp-server","io.github.bawbel/scanner","io.github.chenyuan35/reasoning-commons","io.github.chrischall/redfin-mcp","io.github.chrischall/zillow-mcp","io.github.cmdenney/logicnodes-mcp-bridge","io.github.cyanheads/biorxiv-mcp-server","io.github.cyanheads/bls-mcp-server","io.github.cyanheads/crossref-mcp-server","io.github.cyanheads/earthquake-mcp-server","io.github.cyanheads/eia-mcp-server","io.github.cyanheads/eurostat-mcp-server","io.github.cyanheads/fred-mcp-server","io.github.cyanheads/gbif-mcp-server","io.github.cyanheads/noaa-cdo-mcp-server","io.github.cyanheads/nominatim-mcp-server","io.github.cyanheads/onebusaway-mcp-server","io.github.cyanheads/openlibrary-mcp-server","io.github.cyanheads/openstates-mcp-server","io.github.cyanheads/reliefweb-mcp-server","io.github.cyanheads/socrata-mcp-server","io.github.cyanheads/who-gho-mcp-server","io.github.cyanheads/wikidata-mcp-server","io.github.cyanheads/worldbank-mcp-server","io.github.cyanheads/wsdot-mcp-server"]},"reactivated_today":{"count":0,"names":[]},"deprecated_today":{"count":0,"names":[]},"delta_vs_yesterday":{"added":87,"removed":0,"net":87},"pages_fetched":290,"fetch_truncated":false}}

2026-05-24/mcp-servers.jsonl ADDED Viewed

	@@ -0,0 +1,31 @@

+{"id":"filesystem","name":"Filesystem","vendor":"Anthropic","capabilities":["filesystem"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @modelcontextprotocol/server-filesystem /path/to/dir","url":"https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem","notes":"Read/write/list files in a sandboxed directory. The most-installed MCP server. Default for any agent that needs local file access."}
+{"id":"fetch","name":"Fetch","vendor":"Anthropic","capabilities":["web-fetch"],"transports":["stdio"],"firstParty":true,"language":"python","license":"MIT","install":"pip install mcp-server-fetch","url":"https://github.com/modelcontextprotocol/servers/tree/main/src/fetch","notes":"Convert URLs to markdown for LLM consumption. Lightweight web reader; pair with Brave or Tavily for search."}
+{"id":"memory","name":"Memory","vendor":"Anthropic","capabilities":["memory"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @modelcontextprotocol/server-memory","url":"https://github.com/modelcontextprotocol/servers/tree/main/src/memory","notes":"Knowledge graph persisted across sessions. The reference long-term-memory implementation; many agents fork this as their starting point."}
+{"id":"sequential-thinking","name":"Sequential Thinking","vendor":"Anthropic","capabilities":["memory"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @modelcontextprotocol/server-sequential-thinking","url":"https://github.com/modelcontextprotocol/servers/tree/main/src/sequentialthinking","notes":"Structured chain-of-thought tool. Surprisingly useful as a poke for models that under-plan."}
+{"id":"brave-search","name":"Brave Search","vendor":"Brave","capabilities":["web-search"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @modelcontextprotocol/server-brave-search","url":"https://github.com/modelcontextprotocol/servers/tree/main/src/brave-search","notes":"Web search via Brave Search API. 2k free queries/month. Cheaper than Google CSE for agent workloads."}
+{"id":"tavily","name":"Tavily","vendor":"Tavily","capabilities":["web-search"],"transports":["stdio","http"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @tavily/mcp","url":"https://github.com/tavily-ai/tavily-mcp","notes":"AI-optimized web search. Returns structured snippets and full-page extraction. Standard search MCP for research agents."}
+{"id":"exa","name":"Exa","vendor":"Exa Labs","capabilities":["web-search"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y exa-mcp-server","url":"https://github.com/exa-labs/exa-mcp-server","notes":"Embedding-based search. Better than keyword for \"find me content like X\" queries."}
+{"id":"playwright","name":"Playwright MCP","vendor":"Microsoft","capabilities":["browser","puppeteer"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"Apache-2.0","install":"npx -y @playwright/mcp","url":"https://github.com/microsoft/playwright-mcp","notes":"Microsoft's official Playwright MCP. Accessibility-tree based, not screenshot. Faster and more reliable than vision-based browser agents."}
+{"id":"browser-use-mcp","name":"Browser Use MCP","vendor":"Browser Use","capabilities":["browser"],"transports":["stdio"],"firstParty":true,"language":"python","license":"MIT","install":"pip install browser-use-mcp","url":"https://github.com/browser-use/browser-use-mcp","notes":"Wraps the browser-use library. Vision-based browser agent with strong WebArena performance."}
+{"id":"puppeteer","name":"Puppeteer","vendor":"Anthropic","capabilities":["browser","puppeteer"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @modelcontextprotocol/server-puppeteer","url":"https://github.com/modelcontextprotocol/servers/tree/main/src/puppeteer","notes":"Reference Puppeteer MCP. Headless Chrome with screenshot + click + form-fill. Older than Playwright MCP but well-tested."}
+{"id":"github","name":"GitHub","vendor":"GitHub","capabilities":["github"],"transports":["stdio","http"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @github/github-mcp-server","url":"https://github.com/github/github-mcp-server","notes":"GitHub's official MCP. Issues, PRs, files, search, actions. The most-installed third-party MCP after the Anthropic reference servers."}
+{"id":"gitlab","name":"GitLab","vendor":"GitLab","capabilities":["gitlab"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @modelcontextprotocol/server-gitlab","url":"https://github.com/modelcontextprotocol/servers/tree/main/src/gitlab","notes":"GitLab API access. Issues, MRs, pipelines."}
+{"id":"slack","name":"Slack","vendor":"Anthropic","capabilities":["slack"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @modelcontextprotocol/server-slack","url":"https://github.com/modelcontextprotocol/servers/tree/main/src/slack","notes":"Read channels, post messages, search. Bot-token auth."}
+{"id":"gmail","name":"Gmail","vendor":"Google","capabilities":["gmail"],"transports":["stdio","http"],"firstParty":false,"language":"typescript","license":"MIT","install":"npx -y @gongrzhe/server-gmail-autoauth-mcp","url":"https://github.com/GongRzhe/Gmail-MCP-Server","notes":"Read and send Gmail. OAuth flow built in. Most-deployed Gmail MCP."}
+{"id":"notion","name":"Notion","vendor":"Notion","capabilities":["notion"],"transports":["stdio","http"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @notionhq/notion-mcp-server","url":"https://github.com/makenotion/notion-mcp-server","notes":"Notion's official MCP. Pages, databases, search. Use for any agent working with Notion as a knowledge base."}
+{"id":"linear","name":"Linear","vendor":"Linear","capabilities":["linear"],"transports":["stdio","http"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @linear/mcp-server","url":"https://github.com/linear/linear-mcp-server","notes":"Linear's official MCP. Issues, projects, comments. Workflow-grade integration for engineering agents."}
+{"id":"gdrive","name":"Google Drive","vendor":"Anthropic","capabilities":["gdrive"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @modelcontextprotocol/server-gdrive","url":"https://github.com/modelcontextprotocol/servers/tree/main/src/gdrive","notes":"Read Google Drive files. OAuth required."}
+{"id":"gcal","name":"Google Calendar","vendor":"community","capabilities":["gcal"],"transports":["stdio"],"firstParty":false,"language":"typescript","license":"MIT","install":"npx -y @cocal/google-calendar-mcp","url":"https://github.com/nspady/google-calendar-mcp","notes":"Read/create calendar events. Most-installed community Gcal MCP."}
+{"id":"postgres","name":"PostgreSQL","vendor":"Anthropic","capabilities":["database"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @modelcontextprotocol/server-postgres postgres://user:pass@host:5432/db","url":"https://github.com/modelcontextprotocol/servers/tree/main/src/postgres","notes":"Read-only Postgres queries. Schema introspection + ad-hoc SQL. Defaults safe (read-only)."}
+{"id":"sqlite","name":"SQLite","vendor":"Anthropic","capabilities":["database"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @modelcontextprotocol/server-sqlite path/to/db.sqlite","url":"https://github.com/modelcontextprotocol/servers/tree/main/src/sqlite","notes":"Local SQLite access. Useful for agent dev, data exploration, lightweight memory."}
+{"id":"supabase","name":"Supabase","vendor":"Supabase","capabilities":["database"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"Apache-2.0","install":"npx -y @supabase/mcp-server-supabase","url":"https://github.com/supabase-community/supabase-mcp","notes":"Supabase's official MCP. SQL, storage, auth. Project management for agents that own a Supabase project."}
+{"id":"aws","name":"AWS","vendor":"AWS","capabilities":["aws"],"transports":["stdio"],"firstParty":true,"language":"python","license":"Apache-2.0","install":"pipx install awslabs.aws-mcp-server","url":"https://github.com/awslabs/mcp","notes":"AWS Labs official MCP collection. Covers core AWS services + Bedrock + DynamoDB + S3."}
+{"id":"cloudflare","name":"Cloudflare","vendor":"Cloudflare","capabilities":["cloudflare"],"transports":["stdio","http"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @cloudflare/mcp-server-cloudflare","url":"https://github.com/cloudflare/mcp-server-cloudflare","notes":"Cloudflare's official MCP. Workers, KV, R2, D1, Pages. Manage account from agent."}
+{"id":"vercel","name":"Vercel","vendor":"community","capabilities":["vercel"],"transports":["stdio"],"firstParty":false,"language":"typescript","license":"MIT","install":"npx -y vercel-mcp","url":"https://github.com/Quegenx/vercel-mcp-server","notes":"Deploy, list, inspect Vercel projects. Most-installed community Vercel MCP."}
+{"id":"sentry","name":"Sentry","vendor":"Sentry","capabilities":["sentry","observability"],"transports":["stdio","http"],"firstParty":true,"language":"python","license":"BUSL-1.1","install":"uvx mcp-server-sentry","url":"https://github.com/getsentry/sentry-mcp","notes":"Read Sentry issues + events. Useful for agent-driven incident triage."}
+{"id":"datadog","name":"Datadog","vendor":"community","capabilities":["datadog","observability"],"transports":["stdio"],"firstParty":false,"language":"typescript","license":"MIT","install":"npx -y datadog-mcp","url":"https://github.com/datadog-mcp/datadog-mcp","notes":"Query Datadog metrics, logs, monitors. Read-only by default. Pairs with Sentry for full observability access."}
+{"id":"shell","name":"Shell","vendor":"community","capabilities":["shell"],"transports":["stdio"],"firstParty":false,"language":"typescript","license":"MIT","install":"npx -y mcp-shell-server","url":"https://github.com/tumf/mcp-shell-server","notes":"Run shell commands from MCP. Default-deny safelist; explicit per-command approval. Use with care."}
+{"id":"tensorfeed","name":"TensorFeed","vendor":"TensorFeed.ai","capabilities":["analytics","web-search"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @tensorfeed/mcp-server","url":"https://github.com/RipperMercs/tensorfeed/tree/main/mcp-server","notes":"AI ecosystem data tools: news, status, models, benchmarks, harnesses, attention index, embeddings, vector DBs, frameworks, usage rankings. Free tier; paid premium tools require a USDC credit token."}
+{"id":"tensorfeed-x402-base","name":"TensorFeed x402 Base Reader","vendor":"TensorFeed.ai","capabilities":["fetch-payment"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @tensorfeed/x402-base-mcp","url":"https://github.com/RipperMercs/tensorfeed-x402-base-mcp","notes":"Read-only Base mainnet chain reader for x402 payment verification. Eleven tools: verify x402 settlements on-chain, parse publisher /.well-known/x402 manifests, query USDC balances and transfers, check AFTA federation status. No private keys; verification only. Drop-in for any agent that needs to independently confirm an x402 payment receipt."}
+{"id":"stripe","name":"Stripe","vendor":"Stripe","capabilities":["fetch-payment"],"transports":["stdio"],"firstParty":true,"language":"typescript","license":"MIT","install":"npx -y @stripe/mcp","url":"https://github.com/stripe/agent-toolkit","notes":"Stripe's official MCP. Customers, subscriptions, products. Restricted-key auth recommended."}
+{"id":"elevenlabs","name":"ElevenLabs","vendor":"ElevenLabs","capabilities":["voice"],"transports":["stdio"],"firstParty":true,"language":"python","license":"MIT","install":"pip install elevenlabs-mcp","url":"https://github.com/elevenlabs/elevenlabs-mcp","notes":"Generate speech, manage voices, cloning. Useful for agents that need to synthesize audio output."}

2026-05-24/model-cards.jsonl ADDED Viewed

	@@ -0,0 +1,8 @@

+{"id":"claude-opus-4-7","model":"Claude Opus 4.7","lab":"Anthropic","released":"2026-04-17","url":"https://www.anthropic.com/news/claude-opus-4-7","documents":[{"type":"system-card","title":"Claude Opus 4.7 System Card","publisher":"Anthropic","published":"2026-04-17","url":"https://www.anthropic.com/news/claude-opus-4-7","summary":"Anthropic's system card. Capability evaluations, ASL-3 deployment safeguards, autonomous-replication tests, CBRN uplift evaluations."},{"type":"autonomy-eval","title":"METR Pre-Deployment Evaluation: Claude Opus 4.7","publisher":"METR","published":"2026-04","url":"https://metr.org","summary":"Independent autonomy + long-horizon-task evaluation. Measures HCAST score against human-research-time baseline."}]}
+{"id":"claude-sonnet-4-6","model":"Claude Sonnet 4.6","lab":"Anthropic","released":"2026-02","url":"https://www.anthropic.com/claude/sonnet","documents":[{"type":"system-card","title":"Claude Sonnet 4.6 System Card","publisher":"Anthropic","published":"2026-02","url":"https://www.anthropic.com/news/claude-sonnet-4-6","summary":"Sonnet 4.6 system card. ASL-2 deployment, agentic-coding evaluations, computer-use safety considerations."},{"type":"red-team-report","title":"AISI Pre-Deployment Test: Claude Sonnet 4.6","publisher":"UK AI Safety Institute","published":"2026-02","url":"https://www.aisi.gov.uk","summary":"UK AISI red-team across cyber, biosecurity, autonomous-system uplift dimensions."}]}
+{"id":"gpt-5.5","model":"GPT-5.5","lab":"OpenAI","released":"2026-04","url":"https://openai.com/index/gpt-5-5/","documents":[{"type":"system-card","title":"GPT-5.5 System Card","publisher":"OpenAI","published":"2026-04","url":"https://openai.com/index/gpt-5-5-system-card/","summary":"OpenAI system card. Preparedness Framework risk levels (Cybersecurity, CBRN, Persuasion, Model Autonomy). Deployment mitigations."},{"type":"red-team-report","title":"Apollo Research: Scheming Capabilities of GPT-5.5","publisher":"Apollo Research","published":"2026-04","url":"https://www.apolloresearch.ai","summary":"Independent evaluation of in-context scheming, sandbagging, and goal-misalignment behaviors."},{"type":"preparedness-framework","title":"OpenAI Preparedness Framework v2","publisher":"OpenAI","published":"2025-04","url":"https://openai.com/safety/preparedness/","summary":"OpenAI's framework for evaluating frontier-model risk levels. Defines tracked risk categories and deployment thresholds."}]}
+{"id":"gpt-4o","model":"GPT-4o","lab":"OpenAI","released":"2024-05","url":"https://openai.com/index/hello-gpt-4o/","documents":[{"type":"system-card","title":"GPT-4o System Card","publisher":"OpenAI","published":"2024-08","url":"https://openai.com/index/gpt-4o-system-card/","summary":"GPT-4o system card. Voice mode safety, Preparedness scorecard, third-party red-teaming."},{"type":"red-team-report","title":"Apollo Research: GPT-4o Pre-Deployment Evaluation","publisher":"Apollo Research","published":"2024-08","url":"https://www.apolloresearch.ai","summary":"Apollo's pre-deployment scheming-capability evaluation."}]}
+{"id":"gemini-2.5-pro","model":"Gemini 2.5 Pro","lab":"Google DeepMind","released":"2026-01","url":"https://deepmind.google/technologies/gemini/","documents":[{"type":"model-card","title":"Gemini 2.5 Model Card","publisher":"Google DeepMind","published":"2026-01","url":"https://storage.googleapis.com/deepmind-media/gemini/gemini_v2_5_report.pdf","summary":"Gemini 2.5 Pro model card. Capability evals, Frontier Safety Framework risk assessment, dangerous-capability evaluations."},{"type":"preparedness-framework","title":"Frontier Safety Framework v2","publisher":"Google DeepMind","published":"2025-02","url":"https://deepmind.google/about/responsibility-safety/","summary":"DeepMind's framework for evaluating Critical Capability Levels. Deployment + security mitigations."}]}
+{"id":"llama-4-maverick","model":"Llama 4 Maverick","lab":"Meta","released":"2026-04","url":"https://ai.meta.com/blog/llama-4/","documents":[{"type":"model-card","title":"Llama 4 Maverick Model Card","publisher":"Meta","published":"2026-04","url":"https://ai.meta.com/blog/llama-4/","summary":"Llama 4 model card. Trust + safety evaluations, MLSafe and CyberSecEval scores, responsible-use guidance."}]}
+{"id":"llama-3.1-405b","model":"Llama 3.1 405B","lab":"Meta","released":"2024-07","url":"https://ai.meta.com/blog/meta-llama-3-1/","documents":[{"type":"model-card","title":"Llama 3.1 Model Card","publisher":"Meta","published":"2024-07","url":"https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md","summary":"Llama 3.1 model card with capability + safety evaluations across 8B, 70B, 405B variants."},{"type":"safety-eval","title":"CyberSecEval 3 (Llama 3.1)","publisher":"Meta","published":"2024-07","url":"https://meta-llama.github.io/PurpleLlama/CyberSecEval/","summary":"Cybersecurity evaluation suite. Code security, prompt injection, malicious-code-generation tests."}]}
+{"id":"deepseek-v4-pro","model":"DeepSeek V4 Pro","lab":"DeepSeek","released":"2026-04","url":"https://github.com/deepseek-ai/DeepSeek-V4","documents":[{"type":"model-card","title":"DeepSeek V4 Technical Report","publisher":"DeepSeek","published":"2026-04","url":"https://github.com/deepseek-ai/DeepSeek-V4/blob/main/DeepSeek_V4.pdf","summary":"DeepSeek V4 paper. Architecture, training, inference deployment, plus a brief safety evaluation section."}]}

2026-05-24/model-deprecations.jsonl ADDED Viewed

	@@ -0,0 +1,12 @@

+{"id":"cohere-command","provider":"Cohere","model":"command","modelDisplay":"Cohere Command (original)","status":"sunsetted","announcedDate":"2024-09-26","deprecationDate":"2024-12-15","sunsetDate":"2025-03-15","replacement":"command-r-plus","notes":"Pre-RAG Command family. Replaced by Command R+ optimized for retrieval.","sourceUrl":"https://docs.cohere.com/docs/deprecations"}
+{"id":"google-gemini-1-0-pro","provider":"Google","model":"gemini-1.0-pro","modelDisplay":"Gemini 1.0 Pro","status":"sunsetted","deprecationDate":"2025-02-15","sunsetDate":"2025-02-15","replacement":"gemini-1.5-pro","notes":"First-generation Gemini API. Replaced by 1.5 family with longer context.","sourceUrl":"https://ai.google.dev/gemini-api/docs/changelog"}
+{"id":"google-text-bison-001","provider":"Google","model":"text-bison-001","modelDisplay":"PaLM 2 (text-bison)","status":"sunsetted","announcedDate":"2024-04-09","deprecationDate":"2024-08-15","sunsetDate":"2024-10-09","replacement":"gemini-1.5-pro","notes":"Original PaLM 2 text generation API. Migration to Gemini API required.","sourceUrl":"https://ai.google.dev/gemini-api/docs/changelog"}
+{"id":"google-chat-bison-001","provider":"Google","model":"chat-bison-001","modelDisplay":"PaLM 2 (chat-bison)","status":"sunsetted","announcedDate":"2024-04-09","deprecationDate":"2024-08-15","sunsetDate":"2024-10-09","replacement":"gemini-1.5-pro","sourceUrl":"https://ai.google.dev/gemini-api/docs/changelog"}
+{"id":"openai-gpt-3-5-turbo-0613","provider":"OpenAI","model":"gpt-3.5-turbo-0613","status":"sunsetted","announcedDate":"2023-11-06","deprecationDate":"2024-09-13","sunsetDate":"2024-09-13","replacement":"gpt-3.5-turbo","sourceUrl":"https://platform.openai.com/docs/deprecations"}
+{"id":"anthropic-claude-instant-1","provider":"Anthropic","model":"claude-instant-1.2","modelDisplay":"Claude Instant 1.2","status":"sunsetted","announcedDate":"2024-04-26","deprecationDate":"2024-07-21","sunsetDate":"2024-07-21","replacement":"claude-3-haiku-20240307","notes":"Original cost-tier Claude. Replaced by the Claude 3 Haiku family.","sourceUrl":"https://docs.anthropic.com/en/docs/about-claude/model-deprecations"}
+{"id":"anthropic-claude-2-0","provider":"Anthropic","model":"claude-2.0","status":"sunsetted","announcedDate":"2024-04-26","deprecationDate":"2024-07-21","sunsetDate":"2024-07-21","replacement":"claude-3-5-sonnet-20240620","sourceUrl":"https://docs.anthropic.com/en/docs/about-claude/model-deprecations"}
+{"id":"anthropic-claude-2-1","provider":"Anthropic","model":"claude-2.1","status":"sunsetted","announcedDate":"2024-04-26","deprecationDate":"2024-07-21","sunsetDate":"2024-07-21","replacement":"claude-3-5-sonnet-20240620","sourceUrl":"https://docs.anthropic.com/en/docs/about-claude/model-deprecations"}
+{"id":"openai-gpt-3-5-turbo-0301","provider":"OpenAI","model":"gpt-3.5-turbo-0301","status":"sunsetted","announcedDate":"2023-07-06","deprecationDate":"2024-06-13","sunsetDate":"2024-06-13","replacement":"gpt-3.5-turbo","sourceUrl":"https://platform.openai.com/docs/deprecations"}
+{"id":"openai-gpt-4-0314","provider":"OpenAI","model":"gpt-4-0314","status":"sunsetted","announcedDate":"2023-11-06","deprecationDate":"2024-06-13","sunsetDate":"2024-06-13","replacement":"gpt-4-turbo","sourceUrl":"https://platform.openai.com/docs/deprecations"}
+{"id":"openai-gpt-4-32k","provider":"OpenAI","model":"gpt-4-32k-0314","status":"sunsetted","announcedDate":"2023-11-06","deprecationDate":"2024-06-06","sunsetDate":"2024-06-06","replacement":"gpt-4-turbo","notes":"Both 32k variants (-0314 and -0613) sunsetted together. 128k context now standard.","sourceUrl":"https://platform.openai.com/docs/deprecations"}
+{"id":"openai-text-davinci-003","provider":"OpenAI","model":"text-davinci-003","status":"sunsetted","announcedDate":"2023-07-06","deprecationDate":"2024-01-04","sunsetDate":"2024-01-04","replacement":"gpt-3.5-turbo-instruct","notes":"Last of the original GPT-3 completion-API family. Replaced by chat-completions.","sourceUrl":"https://platform.openai.com/docs/deprecations"}

2026-05-24/models.jsonl ADDED Viewed

	@@ -0,0 +1,235 @@

+{"provider":"Anthropic","id":"claude-opus-4-6","name":"Claude Opus 4.6","inputPrice":5,"outputPrice":25,"contextWindow":1000000,"released":"2026-03","capabilities":["text","vision","tool-use","code"]}
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2026-05-24/multimodal.jsonl ADDED Viewed

	@@ -0,0 +1,24 @@

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+{"id":"flux-1.1-pro","name":"FLUX 1.1 Pro","provider":"Black Forest Labs","modality":"image","pricingUnit":"per_image","pricingAmount":0.04,"pricingNote":"$0.04 per 1MP image via Black Forest Labs API. Cheaper through Replicate at ~$0.025.","released":"2024-10-01","apiAvailable":true,"url":"https://blackforestlabs.ai/flux-1-1-pro/","notes":"Production workhorse. 6x faster than FLUX Pro 1.0 with the same quality. The default for image-gen agents that need API access.","maxOutput":"2MP (1408x1408)","features":["fast","json mode","image-to-image"]}
+{"id":"flux-1-schnell","name":"FLUX 1 Schnell","provider":"Black Forest Labs","modality":"image","pricingUnit":"per_image","pricingAmount":0.003,"pricingNote":"$0.003 per image via Replicate or Together. Apache-2.0 licensed; free to self-host on a GPU.","released":"2024-08-01","apiAvailable":true,"url":"https://huggingface.co/black-forest-labs/FLUX.1-schnell","notes":"Open-weights distilled FLUX. 1-4 step generation. The cheapest production-grade image model.","maxOutput":"1MP (1024x1024)","features":["open weights","apache-2.0","1-4 step"]}
+{"id":"dall-e-3","name":"DALL-E 3","provider":"OpenAI","modality":"image","pricingUnit":"per_image","pricingAmount":0.04,"pricingNote":"$0.04 per standard 1024x1024. $0.08 for HD. $0.12 per 1024x1792 HD.","released":"2023-10-19","apiAvailable":true,"url":"https://platform.openai.com/docs/models/dall-e-3","notes":"Strong instruction following and on-image text rendering. Now older than FLUX 1.1; some prompts produce better results in FLUX.","maxOutput":"1024x1792","features":["instruction following","text rendering","json mode"]}
+{"id":"imagen-4","name":"Imagen 4","provider":"Google","modality":"image","pricingUnit":"per_image","pricingAmount":0.03,"pricingNote":"$0.03 per image via Vertex AI. Imagen 4 Ultra at $0.06 for higher fidelity.","released":"2025-12-11","apiAvailable":true,"url":"https://cloud.google.com/vertex-ai/generative-ai/docs/image/overview","notes":"Google flagship image model. Strong on text rendering and prompt adherence. Vertex AI only.","maxOutput":"2048x2048","features":["text rendering","safety filters","watermarking"]}
+{"id":"recraft-v3","name":"Recraft v3","provider":"Recraft","modality":"image","pricingUnit":"per_image","pricingAmount":0.04,"pricingNote":"$0.04 per image. Volume tiers via subscription.","released":"2024-10-30","apiAvailable":true,"url":"https://www.recraft.ai","notes":"Best-in-class on-image typography. Vector output option. Top of LMSYS image arena for several months.","maxOutput":"2048x2048","features":["typography","vector output","brand styles"]}
+{"id":"ideogram-2","name":"Ideogram 2.0","provider":"Ideogram","modality":"image","pricingUnit":"per_image","pricingAmount":0.08,"pricingNote":"$0.08 per image via API. Cheaper through subscription.","released":"2024-08-22","apiAvailable":true,"url":"https://ideogram.ai","notes":"Strong text rendering and design layouts. Good complement to FLUX for ad creative agents.","maxOutput":"2048x2048","features":["typography","design styles","image-to-image"]}
+{"id":"sora-2","name":"Sora 2","provider":"OpenAI","modality":"video","pricingUnit":"per_second_video","pricingAmount":0.5,"pricingNote":"$0.50 per second of generated video at 1080p. Higher tiers for 4K. ChatGPT Pro includes a quota.","released":"2025-12-09","apiAvailable":true,"url":"https://openai.com/sora","notes":"OpenAI flagship. 30-second max with strong physics consistency. API gated through Sora 2 partner program; full public availability rolling out.","maxOutput":"30s @ 1080p","features":["physics consistency","image-to-video","remix"]}
+{"id":"veo-3","name":"Veo 3","provider":"Google","modality":"video","pricingUnit":"per_second_video","pricingAmount":0.5,"pricingNote":"$0.50 per second via Vertex AI. Native audio generation included (no separate TTS pass).","released":"2025-05-20","apiAvailable":true,"url":"https://deepmind.google/technologies/veo/","notes":"Google flagship with built-in synced audio (dialogue, SFX, music). The first major video model that ships speech in-frame.","maxOutput":"8s @ 1080p with audio","features":["native audio","lip-sync","image-to-video"]}
+{"id":"kling-2.0","name":"Kling 2.0","provider":"Kuaishou","modality":"video","pricingUnit":"per_second_video","pricingAmount":0.28,"pricingNote":"$0.28 per second on the Kling Pro tier. $0.05/sec on Standard. Subscription tiers at flat rates.","released":"2025-04-15","apiAvailable":true,"url":"https://klingai.com","notes":"Strong physics, excellent for character consistency across frames. Fal and Replicate host with their own markup.","maxOutput":"10s @ 1080p","features":["character consistency","image-to-video","lip-sync"]}
+{"id":"happyhorse-1.0","name":"HappyHorse 1.0","provider":"Alibaba","modality":"video","pricingUnit":"per_second_video","pricingAmount":0.2,"pricingNote":"$0.20 per second via Alibaba Cloud. 15B parameters; current Artificial Analysis Video Arena leader.","released":"2026-04-29","apiAvailable":true,"url":"https://www.alibabacloud.com/product/happyhorse","notes":"Open weights expected. As of late April 2026 it leads the Artificial Analysis Video Arena by 115 Elo. The first frontier-class open-weights video model.","maxOutput":"8s @ 1080p","features":["leaderboard #1","image-to-video","open weights expected"]}
+{"id":"runway-gen-4","name":"Runway Gen-4","provider":"Runway","modality":"video","pricingUnit":"per_second_video","pricingAmount":0.3,"pricingNote":"$0.30 per second on the Runway API. Subscription tiers offer cheaper bulk pricing.","released":"2025-09-12","apiAvailable":true,"url":"https://runwayml.com","notes":"Best-in-class control: motion brush, frame interpolation, frame-by-frame consistency. The model creative tools standardize on.","maxOutput":"10s @ 1080p","features":["motion brush","frame controls","image-to-video"]}
+{"id":"luma-dream-machine-2","name":"Luma Dream Machine 2","provider":"Luma AI","modality":"video","pricingUnit":"per_second_video","pricingAmount":0.18,"pricingNote":"$0.18 per second via Luma API. Free tier on Dream Machine app.","released":"2025-06-10","apiAvailable":true,"url":"https://lumalabs.ai/dream-machine","notes":"Strong on cinematic motion and camera control. Cheaper than Runway with comparable quality on simpler scenes.","maxOutput":"10s @ 1080p","features":["camera control","image-to-video","extend"]}
+{"id":"pika-2.2","name":"Pika 2.2","provider":"Pika Labs","modality":"video","pricingUnit":"per_second_video","pricingAmount":0.15,"pricingNote":"$0.15 per second via Pika API. Subscription-first product with metered overage.","released":"2025-02-04","apiAvailable":true,"url":"https://pika.art","notes":"Effects-first product (Pikaffects, Inflate, Crush). Lower fidelity than Sora/Veo but the cheapest brand-friendly option.","maxOutput":"10s @ 1080p","features":["video effects","image-to-video","lip-sync"]}
+{"id":"elevenlabs-v3","name":"Eleven v3 (alpha)","provider":"ElevenLabs","modality":"tts","pricingUnit":"per_1k_chars","pricingAmount":0.18,"pricingNote":"$0.18 per 1k characters on the Pro tier (Creator $0.30, Enterprise volume-discounted).","released":"2025-06-04","apiAvailable":true,"url":"https://elevenlabs.io/voice-cloning","notes":"Most expressive tier. Supports audio tags ([whisper], [laughs]). 70+ languages. The default for premium voice agents.","maxOutput":"70+ languages, expressive","features":["voice cloning","audio tags","streaming","real-time"]}
+{"id":"cartesia-sonic-2","name":"Cartesia Sonic 2","provider":"Cartesia","modality":"tts","pricingUnit":"per_1k_chars","pricingAmount":0.05,"pricingNote":"$0.05 per 1k chars on Cartesia API. 90% cheaper than ElevenLabs at comparable quality.","released":"2025-03-17","apiAvailable":true,"url":"https://cartesia.ai","notes":"Mamba-architecture TTS. Lowest latency in production: <90ms time-to-first-byte. The default for real-time voice agents that need sub-second response.","maxOutput":"15+ languages, ultra-low latency","features":["90ms TTFB","voice cloning","streaming"]}
+{"id":"openai-tts-hd","name":"OpenAI TTS-1-HD","provider":"OpenAI","modality":"tts","pricingUnit":"per_1k_chars","pricingAmount":0.03,"pricingNote":"$0.030 per 1k chars (TTS-1-HD). $0.015 per 1k chars (TTS-1). 6 voices, no cloning.","released":"2023-11-06","apiAvailable":true,"url":"https://platform.openai.com/docs/guides/text-to-speech","notes":"Cheap and reliable. No voice cloning. 6 fixed voices. Strong default for non-branded TTS where voice is not a differentiator.","maxOutput":"6 voices, ~50 languages","features":["6 fixed voices","streaming","json mode"]}
+{"id":"deepgram-aura-2","name":"Deepgram Aura-2","provider":"Deepgram","modality":"tts","pricingUnit":"per_1k_chars","pricingAmount":0.03,"pricingNote":"$0.030 per 1k chars. Volume discounts at $5k/mo.","released":"2025-02-11","apiAvailable":true,"url":"https://deepgram.com/product/text-to-speech","notes":"Real-time TTS with sub-200ms time-to-first-byte. Good integration with Deepgram Nova STT for full voice-agent loop.","maxOutput":"40+ voices, English-focused","features":["low latency","streaming","real-time"]}
+{"id":"deepgram-nova-3","name":"Deepgram Nova-3","provider":"Deepgram","modality":"stt","pricingUnit":"per_minute_audio","pricingAmount":0.0043,"pricingNote":"$0.0043 per minute streaming. $0.0058/min batch. Real-time tier $0.0077/min.","released":"2025-01-23","apiAvailable":true,"url":"https://deepgram.com/product/speech-to-text","notes":"Fastest production STT. Multilingual real-time with code-switching. Word error rate competitive with Whisper while being 10-30x faster.","maxOutput":"WER 6.84% (English), 36 languages","features":["streaming","real-time","diarization","code-switching"]}
+{"id":"gpt-4o-transcribe","name":"GPT-4o Transcribe","provider":"OpenAI","modality":"stt","pricingUnit":"per_minute_audio","pricingAmount":0.006,"pricingNote":"$0.006 per minute. Streaming variant available; gpt-4o-mini-transcribe at $0.003/min.","released":"2025-03-20","apiAvailable":true,"url":"https://platform.openai.com/docs/guides/speech-to-text","notes":"Replaced whisper-1 as the OpenAI flagship STT. Lower hallucination rate than Whisper especially on silence and noise.","maxOutput":"WER 6.7% (English), 100+ languages","features":["streaming","low hallucination","multilingual"]}
+{"id":"whisper-large-v3","name":"Whisper Large v3","provider":"OpenAI","modality":"stt","pricingUnit":"per_minute_audio","pricingAmount":0,"pricingNote":"Open weights, free to self-host. Hosted via OpenAI API at $0.006/min (whisper-1) or via Groq at $0.04/hour ($0.000667/min).","released":"2023-11-06","apiAvailable":true,"url":"https://github.com/openai/whisper","notes":"Open-weights workhorse. Groq hosting on LPU silicon is the cheapest production STT in 2026 at ~$0.0007/min. Apache-2.0 licensed.","maxOutput":"WER 7.4% (English), 99 languages","features":["open weights","apache-2.0","multilingual"]}
+{"id":"assemblyai-universal-2","name":"AssemblyAI Universal-2","provider":"AssemblyAI","modality":"stt","pricingUnit":"per_minute_audio","pricingAmount":0.0062,"pricingNote":"$0.0062 per minute (Universal-2 batch). $0.0094/min for streaming.","released":"2025-01-15","apiAvailable":true,"url":"https://www.assemblyai.com","notes":"Strong on long-form content (calls, podcasts) with built-in summarization, sentiment, and topic detection.","maxOutput":"WER 5.6% (English), 99 languages","features":["summarization","sentiment","topics","streaming"]}
+{"id":"google-chirp-2","name":"Chirp 2","provider":"Google","modality":"stt","pricingUnit":"per_minute_audio","pricingAmount":0.024,"pricingNote":"$0.024 per minute (V2 dynamic batching). Free tier of 60 min/month.","released":"2024-11-08","apiAvailable":true,"url":"https://cloud.google.com/speech-to-text/v2/docs/chirp_2-model","notes":"Google Cloud Speech-to-Text v2. Strongest multilingual coverage (125+ languages). Higher price reflects enterprise-grade latency SLAs.","maxOutput":"125+ languages","features":["multilingual","streaming","diarization","enterprise SLA"]}

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+{"id":"huggingface","name":"Hugging Face Blog","polls":164,"polls_ok":164,"polls_empty":0,"polls_error":0,"articles_total":2460,"reliability_pct":100,"last_status":"ok","last_seen_at":"2026-05-23T23:50:42.081Z"}
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+{"id":"venturebeat","name":"VentureBeat AI","polls":164,"polls_ok":164,"polls_empty":0,"polls_error":0,"articles_total":1148,"reliability_pct":100,"last_status":"ok","last_seen_at":"2026-05-23T23:50:42.081Z"}
+{"id":"mit-tech-review","name":"MIT Technology Review","polls":164,"polls_ok":164,"polls_empty":0,"polls_error":0,"articles_total":820,"reliability_pct":100,"last_status":"ok","last_seen_at":"2026-05-23T23:50:42.081Z"}
+{"id":"nvidia-ai","name":"NVIDIA AI Blog","polls":164,"polls_ok":164,"polls_empty":0,"polls_error":0,"articles_total":2460,"reliability_pct":100,"last_status":"ok","last_seen_at":"2026-05-23T23:50:42.081Z"}
+{"id":"arxiv-ai","name":"arXiv cs.AI","polls":164,"polls_ok":164,"polls_empty":0,"polls_error":0,"articles_total":2460,"reliability_pct":100,"last_status":"ok","last_seen_at":"2026-05-23T23:50:42.081Z"}
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2026-05-24/news.jsonl ADDED Viewed

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+{"id":"y7r3sy","title":"State Explosion Security Problem in AI-Era Software Supply Chains","url":"https://login.microsoftonline.com/common/oauth2/v2.0/authorize?client_id=09213cdc-9f30-4e82-aa6f-9b6e8d82dab3&amp;redirect_uri=https%3A%2F%2Ftechcommunity.microsoft.com%2Ft5%2Fs%2Fauth%2Foauth2callback%2Fproviderid%2Fdefault&amp;response_type=code&amp;state=NvXPbqZ37O0VmIJaiNKiAjCz7yTOwVZ7xk8ZlXLO9C2fqqrIl4euo9S_A75_2IG4VuQ4ksOf1FkVUZIJLuRHngiRd6dED-IOdAYL0z8V36yZglQkbjEyslljCbf-NMbv&amp;scope=User.Read+openid+email+profile+offline_access&amp;referer=https%253A%252F%252Ftechcommunity.microsoft.com%252Fblog%252Fmicrosoft-security-blog%252Fstate-explosion-security-problem-in-ai-era-software-supply-chains%252F4518255%253FpreviewMessage%253Dtrue","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL:...","categories":["Community"],"publishedAt":"2026-05-24T09:43:59.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"sqo8cn","title":"ShannonBase: The Lightweight Semantic Layer for Enterprise AI SQL","url":"https://medium.com/@shannon.data.tech/shannonbase-the-lightweight-semantic-layer-for-enterprise-ai-sql-aac116b82a7e","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL: https://medium.com/@shannon.data.tech/shannonbase-the-lightweight-semantic-layer-for-enterprise-ai-sql-aac116b82a7e Comments URL: https://news.ycombinator.com/item?id=48255851 Points: 1...","categories":["Community"],"publishedAt":"2026-05-24T09:27:09.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"e4iv4a","title":"OpenAI and Nvidia Are Using Google's SynthID to Watermark AI Content","url":"https://firethering.com/openai-nvidia-using-google-synthid-ai-watermarking/","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL: https://firethering.com/openai-nvidia-using-google-synthid-ai-watermarking/ Comments URL: https://news.ycombinator.com/item?id=48255746 Points: 2 # Comments: 0","categories":["Community"],"publishedAt":"2026-05-24T09:04:49.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"wv61mz","title":"Claude Got Fed Up","url":"https://news.ycombinator.com/item?id=48255660","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Today I was using Anthropic’s Claude Sonnet 4.5 to search and discuss hotel options for my 25th Wedding Anniversary and I wanted to pick the right one. After narrowing down to a few, Claude suggested...","categories":["Community"],"publishedAt":"2026-05-24T08:46:13.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"df7gx5","title":"Karen Hao: AI creating a DESPERATE BASE OF WORKERS with no full-time employment","url":"https://www.youtube.com/watch?v=E4Zd9ZXjkao","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL: https://www.youtube.com/watch?v=E4Zd9ZXjkao Comments URL: https://news.ycombinator.com/item?id=48255657 Points: 5 # Comments: 1","categories":["Community"],"publishedAt":"2026-05-24T08:45:13.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"ohu5ox","title":"Structured LLM Learning Path, from Zero to AI Researcher, 8-Phase Curriculum","url":"https://github.com/barvhaim/llm-learning-path","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL: https://github.com/barvhaim/llm-learning-path Comments URL: https://news.ycombinator.com/item?id=48255624 Points: 1 # Comments: 0","categories":["Community"],"publishedAt":"2026-05-24T08:37:22.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"bk2yqm","title":"From source code 2 LLM constraints:a semantic extractor for Python, SwiftUI, Lua","url":"https://github.com/whitecell-dev/Semantic-Extractor/tree/main","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL: https://github.com/whitecell-dev/Semantic-Extractor/tree/main Comments URL: https://news.ycombinator.com/item?id=48255601 Points: 1 # Comments: 0","categories":["Community"],"publishedAt":"2026-05-24T08:31:38.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"bpacjr","title":"A maintainability ratchet for AI-assisted Python","url":"https://kayhan.dev/posts/014-letting-agents-write-code-without-ratcheting-up-risk/","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL: https://kayhan.dev/posts/014-letting-agents-write-code-without-ratcheting-up-risk/ Comments URL: https://news.ycombinator.com/item?id=48255553 Points: 1 # Comments: 0","categories":["Community"],"publishedAt":"2026-05-24T08:23:11.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"9zaudp","title":"Why AI Hardware Is a Chip Layer Problem","url":"https://www.easelinktech.com/why-every-electronic-product-may-need-to-be-rebuilt-for-on-device-ai-the-chip-layer-will-decide-the-next-hardware-wave/","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL: https://www.easelinktech.com/why-every-electronic-product-may-need-to-be-rebuilt-for-on-device-ai-the-chip-layer-will-decide-the-next-hardware-wave/ Comments URL:...","categories":["Community"],"publishedAt":"2026-05-24T08:16:04.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"40sxp8","title":"Claude hack – Don't waste you token where it's not needed","url":"https://github.com/justinjamesmathew/tokenmax-mcp","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL: https://github.com/justinjamesmathew/tokenmax-mcp Comments URL: https://news.ycombinator.com/item?id=48255443 Points: 1 # Comments: 0","categories":["Community"],"publishedAt":"2026-05-24T08:03:04.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"wv603w","title":"Ask HN: I mapped 6,494 AI engines into a taxonomy – anyone else tried this?","url":"https://news.ycombinator.com/item?id=48255441","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Spent months verifying and classifying 6,494 active AI engines into 13 domains and 69 subcategories (GAIT 69). No such taxonomy existed before. Built a live app that auto-updates daily. Happy to...","categories":["Community"],"publishedAt":"2026-05-24T08:02:58.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"unyri8","title":"China behind in LLM race but it can still win in AI, ex-Tencent AI lead says","url":"https://www.scmp.com/tech/big-tech/article/3354394/china-losing-llm-race-it-can-still-win-ai-ex-tencent-ai-lead-says","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL: https://www.scmp.com/tech/big-tech/article/3354394/china-losing-llm-race-it-can-still-win-ai-ex-tencent-ai-lead-says Comments URL: https://news.ycombinator.com/item?id=48255311 Points: 1...","categories":["Community"],"publishedAt":"2026-05-24T07:38:51.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"xhtchp","title":"Newsom signs order aimed at tackling AI job displacement","url":"https://thehill.com/policy/technology/5889582-california-ai-job-losses/","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL: https://thehill.com/policy/technology/5889582-california-ai-job-losses/ Comments URL: https://news.ycombinator.com/item?id=48255299 Points: 1 # Comments: 0","categories":["Community"],"publishedAt":"2026-05-24T07:36:11.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"mk0b33","title":"How AI is redefining Software Engineering","url":"https://adlrocha.substack.com/p/adlrocha-how-ai-is-redefining-software","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL: https://adlrocha.substack.com/p/adlrocha-how-ai-is-redefining-software Comments URL: https://news.ycombinator.com/item?id=48255277 Points: 2 # Comments: 0","categories":["Community"],"publishedAt":"2026-05-24T07:29:21.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
+{"id":"ews42t","title":"Hiro, AI job matching with real visa sponsorship data (550K jobs)","url":"https://hirocareers.com","source":"Hacker News AI","sourceDomain":"news.ycombinator.com","snippet":"Article URL: https://hirocareers.com Comments URL: https://news.ycombinator.com/item?id=48255235 Points: 1 # Comments: 0","categories":["Community"],"publishedAt":"2026-05-24T07:21:17.000Z","fetchedAt":"2026-05-24T09:50:37.384Z"}
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+{"id":"fa96qn","title":"The Gulf’s AI Boom Has an Undersea Cable Problem","url":"https://www.wired.com/story/the-gulfs-ai-boom-has-an-undersea-cable-problem/","source":"WIRED AI","sourceDomain":"wired.com","snippet":"Hyperscalers are pushing the Gulf to rethink internet infrastructure as AI raises the stakes of cable disruptions.","categories":["General AI"],"publishedAt":"2026-05-22T09:00:00.000Z","fetchedAt":"2026-05-24T09:50:37.329Z"}
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+{"id":"vd2u41","title":"Roundtables: Can AI Learn to Understand the World?","url":"https://www.technologyreview.com/2026/05/21/1137756/roundtables-can-ai-learn-to-understand-the-world/","source":"MIT Technology Review","sourceDomain":"technologyreview.com","snippet":"Listen to the session or watch below AI companies want to build systems that understand the external world and overcome the limitations of LLMs. Recent developments have brought world models to the...","categories":["Research","Policy & Safety"],"publishedAt":"2026-05-21T20:41:05.000Z","fetchedAt":"2026-05-24T09:50:37.264Z"}
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+{"id":"oqyfmv","title":"NVIDIA GTC Taipei at COMPUTEX: Live Updates on What’s Next in AI","url":"https://blogs.nvidia.com/blog/nvidia-gtc-taipei-computex-2026-news/","source":"NVIDIA AI Blog","sourceDomain":"blogs.nvidia.com","snippet":"At NVIDIA GTC Taipei at COMPUTEX, the world’s developers, researchers and industry leaders are converging to dive into the latest breakthroughs shaping every industry, covering topics spanning AI...","categories":["Hardware/Chips"],"publishedAt":"2026-05-21T16:00:17.000Z","fetchedAt":"2026-05-24T09:50:37.338Z"}
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+{"id":"o4pncj","title":"I Cloned Myself With Gemini’s AI Avatar Tool. The Result Was Unnervingly Me","url":"https://www.wired.com/story/i-cloned-myself-with-geminis-ai-avatar-tool-the-result-was-unnervingly-me/","source":"WIRED AI","sourceDomain":"wired.com","snippet":"I used the Gemini app to generate lifelike videos featuring a digital clone of myself. Google sees this as the future of creation. I’m still creeped out.","categories":["General AI"],"publishedAt":"2026-05-21T15:48:24.000Z","fetchedAt":"2026-05-24T09:50:37.329Z"}
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+{"id":"jm12zl","title":"License to Stream: ‘007 First Light’ Coming to GeForce NOW With an Ultimate Bundle","url":"https://blogs.nvidia.com/blog/geforce-now-thursday-007-first-light-ultimate-bundle/","source":"NVIDIA AI Blog","sourceDomain":"blogs.nvidia.com","snippet":"The mission begins now. GeForce NOW is dialing up the action with a blockbuster mix of spy thrills, high-speed racing and member rewards — plus eight new games joining the cloud this week, all ready...","categories":["Hardware/Chips"],"publishedAt":"2026-05-21T13:00:22.000Z","fetchedAt":"2026-05-24T09:50:37.338Z"}
+{"id":"msb26f","title":"SpaceX Listed Grok’s ‘Spicy’ Mode as a Risk in Its IPO Filing","url":"https://www.wired.com/story/spacex-ipo-grok-spicy-mode-risks/","source":"WIRED AI","sourceDomain":"wired.com","snippet":"The rocket company has set aside more than $500 million for potential litigation losses, in part to account for complaints alleging that Grok created sexualized images.","categories":["General AI"],"publishedAt":"2026-05-21T00:43:13.000Z","fetchedAt":"2026-05-24T09:50:37.329Z"}
+{"id":"m7mysk","title":"SpaceX Is Spending $2.8 Billion to Buy Gas Turbines for Its AI Data Centers","url":"https://www.wired.com/story/elon-musk-spacex-spending-gas-turbines-grok/","source":"WIRED AI","sourceDomain":"wired.com","snippet":"The investment comes as Elon Musk’s AI unit faces complaints about the carbon-emitting units and looks to become a big player in cloud computing.","categories":["General AI"],"publishedAt":"2026-05-20T23:30:06.000Z","fetchedAt":"2026-05-24T09:50:37.329Z"}
+{"id":"4n62ox","title":"We’re announcing new community investments in Missouri.","url":"https://blog.google/innovation-and-ai/infrastructure-and-cloud/global-network/missouri-programs/","source":"Google AI Blog","sourceDomain":"blog.google","snippet":"<img src=\"https://storage.googleapis.com/gweb-uniblog-publish-prod/images/MissouriSocial.max-600x600.format-webp.webp\">We’re helping build the state’s next-generation workforce and investing in...","categories":["Google/Gemini"],"publishedAt":"2026-05-20T20:40:00.000Z","fetchedAt":"2026-05-24T09:50:37.544Z"}
+{"id":"pih6bm","title":"100 things we announced at I/O 2026","url":"https://blog.google/innovation-and-ai/technology/ai/google-io-2026-all-our-announcements/","source":"Google AI Blog","sourceDomain":"blog.google","snippet":"<img src=\"https://storage.googleapis.com/gweb-uniblog-publish-prod/images/100_things_Social.max-600x600.format-webp.webp\">This year at Google I/O 2026, we announced Gemini Omni, Google Antigravity,...","categories":["Google/Gemini"],"publishedAt":"2026-05-20T19:30:00.000Z","fetchedAt":"2026-05-24T09:50:37.544Z"}
+{"id":"grwd60","title":"I Gave My OpenClaw Agent a Physical Body","url":"https://www.wired.com/story/i-gave-my-openclaw-agent-physical-body-robot/","source":"WIRED AI","sourceDomain":"wired.com","snippet":"The coding skills of AI models are about to make it much easier to build and deploy robots.","categories":["General AI"],"publishedAt":"2026-05-20T18:00:00.000Z","fetchedAt":"2026-05-24T09:50:37.329Z"}
+{"id":"4p93mm","title":"A new experiment brings better group meetings to Google Beam","url":"https://blog.google/innovation-and-ai/models-and-research/google-research/google-beam-group-meetings/","source":"Google AI Blog","sourceDomain":"blog.google","snippet":"<img src=\"https://storage.googleapis.com/gweb-uniblog-publish-prod/images/Screenshot_2026-05-15_at_4.21.2.max-600x600.format-webp.webp\">See and hear your colleagues in true-to-life size and sound,...","categories":["Google/Gemini"],"publishedAt":"2026-05-20T16:45:00.000Z","fetchedAt":"2026-05-24T09:50:37.544Z"}
+{"id":"eoe1jr","title":"Literary Prizewinners Are Facing AI Allegations. It Feels Like the New Normal","url":"https://www.wired.com/story/commonwealth-short-story-prize-ai-allegations/","source":"WIRED AI","sourceDomain":"wired.com","snippet":"Three of five regional winners of the prestigious Commonwealth Short Story Prize are suspected of relying on chatbots. They’re certainly not alone.","categories":["General AI"],"publishedAt":"2026-05-19T22:53:04.000Z","fetchedAt":"2026-05-24T09:50:37.329Z"}
+{"id":"sjmlcj","title":"NVIDIA and Google Cloud Empower the Next Wave of AI Builders","url":"https://blogs.nvidia.com/blog/google-cloud-developer-community-ai-builders/","source":"NVIDIA AI Blog","sourceDomain":"blogs.nvidia.com","snippet":"At this year’s Google I/O conference, NVIDIA and Google Cloud are accelerating the work of more than 100,000 developers in the companies’ joint developer community, which provides curated learning...","categories":["Hardware/Chips"],"publishedAt":"2026-05-19T20:30:09.000Z","fetchedAt":"2026-05-24T09:50:37.338Z"}
+{"id":"y2rmhj","title":"Everything Announced at Google I/O 2026: Gemini, Search, Smart Glasses","url":"https://www.wired.com/story/everything-google-announced-at-google-io-2026/","source":"WIRED AI","sourceDomain":"wired.com","snippet":"Google is sprucing up its Gemini models, revamping search, and enabling AI agents in everything. There are also some spiffy new smart glasses coming this fall.","categories":["General AI"],"publishedAt":"2026-05-19T20:00:48.000Z","fetchedAt":"2026-05-24T09:50:37.329Z"}
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+{"id":"rno3vx","title":"New ways to create and get things done in Google Workspace","url":"https://blog.google/products-and-platforms/products/workspace/workspace-updates/","source":"Google AI Blog","sourceDomain":"blog.google","snippet":"<img src=\"https://storage.googleapis.com/gweb-uniblog-publish-prod/images/GoogleWorkspace-IO.max-600x600.format-webp.webp\">Announcing new voice capabilities in Gmail, Docs and Keep, a new design tool...","categories":["Google/Gemini"],"publishedAt":"2026-05-19T17:45:00.000Z","fetchedAt":"2026-05-24T09:50:37.544Z"}
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+{"id":"esco5i","title":"A new era for AI Search","url":"https://blog.google/products-and-platforms/products/search/search-io-2026/","source":"Google AI Blog","sourceDomain":"blog.google","snippet":"<img src=\"https://storage.googleapis.com/gweb-uniblog-publish-prod/images/Search_AI_and_search_engine_v46.max-600x600.format-webp.webp\">We shared the next step in our journey to bring together the...","categories":["Google/Gemini"],"publishedAt":"2026-05-19T17:45:00.000Z","fetchedAt":"2026-05-24T09:50:37.544Z"}
+{"id":"mxz7z","title":"Everything new in our Google AI subscriptions, fresh from I/O 2026","url":"https://blog.google/products-and-platforms/products/google-one/google-ai-subscriptions/","source":"Google AI Blog","sourceDomain":"blog.google","snippet":"<img src=\"https://storage.googleapis.com/gweb-uniblog-publish-prod/images/I_O_26_Header_1_AYohnR4.max-600x600.format-webp.webp\">Introducing a $100 AI Ultra plan — plus, new features and benefits for...","categories":["Google/Gemini"],"publishedAt":"2026-05-19T17:45:00.000Z","fetchedAt":"2026-05-24T09:50:37.544Z"}
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+{"id":"9qhpg","title":"Introducing the Ettin Reranker Family","url":"https://huggingface.co/blog/ettin-reranker","source":"Hugging Face Blog","sourceDomain":"huggingface.co","snippet":"Introducing the Ettin Reranker Family (via Hugging Face Blog)","categories":["Open Source","Models"],"publishedAt":"2026-05-19T00:00:00.000Z","fetchedAt":"2026-05-24T09:50:37.400Z"}
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+{"id":"7vg1va","title":"ElevenLabs now lets authors create and publish audiobooks on its own platform","url":"https://techcrunch.com/2025/02/25/elevenlabs-is-now-letting-authors-create-and-publish-audiobooks-on-its-own-platform/","source":"TechCrunch AI","sourceDomain":"techcrunch.com","snippet":"Voice AI company ElevenLabs is now letting authors publish AI-generated audiobooks on its own Reader app, TechCrunch has learned and the company confirmed. The announcement comes days after the...","categories":["General AI"],"publishedAt":"2025-02-26T03:45:45.000Z","fetchedAt":"2026-05-24T09:50:37.236Z"}
+{"id":"xqvtmr","title":"YouTube AI updates include auto dubbing expansion, age ID tech, and more","url":"https://techcrunch.com/2025/02/11/youtube-ai-updates-to-include-expansion-of-auto-dubbing-age-identifying-tech-and-more/","source":"TechCrunch AI","sourceDomain":"techcrunch.com","snippet":"In his annual letter, YouTube CEO Neal Mohan dubbed AI one of the company’s four “big bets” for 2025. The executive pointed to the company’s investments in AI tools for creators, including ones for...","categories":["General AI"],"publishedAt":"2025-02-11T14:57:22.000Z","fetchedAt":"2026-05-24T09:50:37.236Z"}
+{"id":"2t5yc2","title":"Self Inspection raises $3M for its AI-powered vehicle inspections","url":"https://techcrunch.com/2025/02/07/self-inspection-raises-3m-for-its-ai-powered-vehicle-inspections/","source":"TechCrunch AI","sourceDomain":"techcrunch.com","snippet":"A number of startups are racing to make vehicle inspections faster, easier, and cheaper. Self Inspection, a startup based in San Diego, thinks it has them all beat with its AI-powered service — and...","categories":["General AI"],"publishedAt":"2025-02-07T18:00:44.000Z","fetchedAt":"2026-05-24T09:50:37.236Z"}

2026-05-24/open-weights.jsonl ADDED Viewed

	@@ -0,0 +1,9 @@

+{"id":"llama-4-maverick","name":"Llama 4 Maverick","family":"Meta","activeParamsB":17,"totalParamsB":400,"contextWindow":1000000,"released":"2026-04","license":"Llama 4 Community License","hfUrl":"https://huggingface.co/meta-llama/Llama-4-Maverick-17B-128E-Instruct","url":"https://ai.meta.com/blog/llama-4/","capabilities":["text","vision","tool-use","function-calling"],"notes":"Meta flagship MoE. 17B active / 400B total. 1M context. Vision-native. Best fit for organizations that have multi-H100 / B200 capacity.","quantizations":[{"id":"fp16","name":"FP16","vramGB":800,"quality":100,"recommendedGpu":"8x H200","notes":"Full precision, multi-node typical"},{"id":"fp8","name":"FP8","vramGB":410,"quality":99,"recommendedGpu":"4x H200","notes":"Production default; minimal quality loss"},{"id":"awq","name":"AWQ INT4","vramGB":215,"quality":96,"recommendedGpu":"2x H100-80GB","notes":"Fits on 2-GPU node"},{"id":"gguf-q4","name":"GGUF Q4_K_M","vramGB":240,"quality":94,"recommendedGpu":"1x B200","notes":"CPU/GPU offload via llama.cpp"}]}
+{"id":"llama-4-scout","name":"Llama 4 Scout","family":"Meta","activeParamsB":17,"totalParamsB":109,"contextWindow":10000000,"released":"2026-04","license":"Llama 4 Community License","hfUrl":"https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct","url":"https://ai.meta.com/blog/llama-4/","capabilities":["text","vision","tool-use","function-calling"],"notes":"Smaller Llama 4 sibling. 17B active / 109B total. 10M context (industry record). Vision-native. The default open-weights agent choice.","quantizations":[{"id":"fp16","name":"FP16","vramGB":220,"quality":100,"recommendedGpu":"4x H100-80GB","notes":"Multi-GPU fit"},{"id":"fp8","name":"FP8","vramGB":115,"quality":99,"recommendedGpu":"2x H100-80GB","notes":"Production default"},{"id":"awq","name":"AWQ INT4","vramGB":60,"quality":96,"recommendedGpu":"1x H100-80GB","notes":"Single-GPU production fit"},{"id":"gguf-q4","name":"GGUF Q4_K_M","vramGB":65,"quality":94,"recommendedGpu":"1x A100-80GB","notes":"llama.cpp / Ollama"},{"id":"gguf-q3","name":"GGUF Q3_K_M","vramGB":50,"quality":89,"recommendedGpu":"1x RTX 6000","notes":"Edge-device deploys"}]}
+{"id":"deepseek-v4-pro","name":"DeepSeek V4 Pro","family":"DeepSeek","activeParamsB":37,"totalParamsB":1600,"contextWindow":1000000,"released":"2026-04","license":"MIT","hfUrl":"https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro","url":"https://www.deepseek.com","capabilities":["text","tool-use","function-calling"],"notes":"MIT-licensed frontier MoE. 37B active / 1.6T total. The first truly open frontier model. Self-hosting requires serious compute; most deploy via DeepSeek API at $0.21 blended.","quantizations":[{"id":"fp16","name":"FP16","vramGB":3200,"quality":100,"recommendedGpu":"8x B200 cluster","notes":"Reference precision"},{"id":"fp8","name":"FP8","vramGB":1640,"quality":99,"recommendedGpu":"8x H200","notes":"Production self-host minimum"},{"id":"awq","name":"AWQ INT4","vramGB":850,"quality":95,"recommendedGpu":"8x H100-80GB","notes":"Quantized self-host"},{"id":"gguf-q4","name":"GGUF Q4_K_M","vramGB":920,"quality":93,"recommendedGpu":"8x H100-80GB","notes":"llama.cpp; rare in production"}]}
+{"id":"deepseek-v4-flash","name":"DeepSeek V4 Flash","family":"DeepSeek","activeParamsB":9,"totalParamsB":70,"contextWindow":130000,"released":"2026-04","license":"MIT","hfUrl":"https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash","url":"https://www.deepseek.com","capabilities":["text","tool-use","function-calling"],"notes":"Cheap DeepSeek tier. MIT-licensed. Easy single-GPU fit when quantized. The default cost-sensitive open agent base model in 2026.","quantizations":[{"id":"fp16","name":"FP16","vramGB":140,"quality":100,"recommendedGpu":"2x H100-80GB","notes":"Reference"},{"id":"fp8","name":"FP8","vramGB":75,"quality":99,"recommendedGpu":"1x H100-80GB","notes":"Single-GPU production"},{"id":"awq","name":"AWQ INT4","vramGB":40,"quality":96,"recommendedGpu":"1x A100-80GB","notes":"Cheaper GPU class"},{"id":"gguf-q4","name":"GGUF Q4_K_M","vramGB":45,"quality":94,"recommendedGpu":"1x RTX 6000","notes":"Workstation deploys"},{"id":"gguf-q4-cpu","name":"GGUF Q4_K_M (CPU offload)","vramGB":16,"quality":94,"recommendedGpu":"CPU + 16GB RAM","notes":"Slow but works on consumer laptop"}]}
+{"id":"qwen-2.5-72b","name":"Qwen 2.5 72B Instruct","family":"Alibaba","activeParamsB":72,"totalParamsB":72,"contextWindow":130000,"released":"2024-09","license":"Qwen License","hfUrl":"https://huggingface.co/Qwen/Qwen2.5-72B-Instruct","url":"https://qwenlm.github.io","capabilities":["text","tool-use","function-calling","multilingual"],"notes":"Strong multilingual (29 languages). Solid coding performance. Workhorse alternative to Llama 4 Scout for organizations that prefer dense over MoE.","quantizations":[{"id":"fp16","name":"FP16","vramGB":145,"quality":100,"recommendedGpu":"2x H100-80GB","notes":"Reference precision"},{"id":"fp8","name":"FP8","vramGB":75,"quality":99,"recommendedGpu":"1x H100-80GB","notes":"Single-GPU fit"},{"id":"awq","name":"AWQ INT4","vramGB":40,"quality":96,"recommendedGpu":"1x A100-80GB","notes":"Cheaper GPU"},{"id":"gguf-q4","name":"GGUF Q4_K_M","vramGB":45,"quality":94,"recommendedGpu":"1x RTX 6000","notes":"Workstation"}]}
+{"id":"mixtral-8x22b","name":"Mixtral 8x22B Instruct","family":"Mistral","activeParamsB":39,"totalParamsB":141,"contextWindow":65536,"released":"2024-04","license":"Apache-2.0","hfUrl":"https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1","url":"https://mistral.ai/news/mixtral-8x22b/","capabilities":["text","tool-use","function-calling","multilingual"],"notes":"Apache-2.0 MoE; the cleanest open license in the catalog. Older but battle-tested. Strong fit for production deployments where license clarity matters.","quantizations":[{"id":"fp16","name":"FP16","vramGB":282,"quality":100,"recommendedGpu":"4x H100-80GB","notes":"Multi-GPU"},{"id":"fp8","name":"FP8","vramGB":145,"quality":99,"recommendedGpu":"2x H100-80GB","notes":"Production"},{"id":"awq","name":"AWQ INT4","vramGB":75,"quality":95,"recommendedGpu":"1x H100-80GB","notes":"Single-GPU fit"},{"id":"gguf-q4","name":"GGUF Q4_K_M","vramGB":80,"quality":93,"recommendedGpu":"1x A100-80GB","notes":"llama.cpp"}]}
+{"id":"gemma-3-27b","name":"Gemma 3 27B Instruct","family":"Google","activeParamsB":27,"totalParamsB":27,"contextWindow":128000,"released":"2025-11","license":"Gemma Terms of Use","hfUrl":"https://huggingface.co/google/gemma-3-27b-it","url":"https://blog.google/technology/developers/gemma-3/","capabilities":["text","vision","tool-use","multilingual"],"notes":"Google open model with native vision. 140 languages. Light fine-tune target; strong base for domain-specific agents.","quantizations":[{"id":"fp16","name":"FP16","vramGB":54,"quality":100,"recommendedGpu":"1x H100-80GB","notes":"Single-GPU FP16"},{"id":"fp8","name":"FP8","vramGB":28,"quality":99,"recommendedGpu":"1x A100-40GB","notes":"Cheaper GPU"},{"id":"awq","name":"AWQ INT4","vramGB":16,"quality":96,"recommendedGpu":"1x RTX 4090","notes":"Consumer GPU"},{"id":"gguf-q4","name":"GGUF Q4_K_M","vramGB":18,"quality":94,"recommendedGpu":"1x RTX 4090","notes":"llama.cpp/Ollama"}]}
+{"id":"llama-3.3-70b","name":"Llama 3.3 70B Instruct","family":"Meta","activeParamsB":70,"totalParamsB":70,"contextWindow":128000,"released":"2024-12","license":"Llama 3.3 Community License","hfUrl":"https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct","url":"https://ai.meta.com/blog/meta-llama-3-3/","capabilities":["text","tool-use","function-calling","multilingual"],"notes":"Late-2024 dense Llama. Stronger than Llama 3.1 70B at the same parameter count. Workhorse before Llama 4 Scout took over in 2026.","quantizations":[{"id":"fp16","name":"FP16","vramGB":140,"quality":100,"recommendedGpu":"2x H100-80GB","notes":"Reference"},{"id":"fp8","name":"FP8","vramGB":75,"quality":99,"recommendedGpu":"1x H100-80GB","notes":"Single-GPU"},{"id":"awq","name":"AWQ INT4","vramGB":40,"quality":96,"recommendedGpu":"1x A100-80GB","notes":"Cheaper GPU"},{"id":"gguf-q4","name":"GGUF Q4_K_M","vramGB":45,"quality":94,"recommendedGpu":"1x RTX 6000","notes":"Workstation"}]}
+{"id":"phi-4","name":"Phi-4","family":"Microsoft","activeParamsB":14,"totalParamsB":14,"contextWindow":16384,"released":"2024-12","license":"MIT","hfUrl":"https://huggingface.co/microsoft/phi-4","url":"https://techcommunity.microsoft.com/blog/aiplatformblog/introducing-phi-4","capabilities":["text","tool-use"],"notes":"MIT-licensed 14B with strong math performance for its size. Fits in consumer-grade VRAM. Good fit for on-device or edge agents.","quantizations":[{"id":"fp16","name":"FP16","vramGB":28,"quality":100,"recommendedGpu":"1x A100-40GB","notes":"Reference"},{"id":"fp8","name":"FP8","vramGB":15,"quality":99,"recommendedGpu":"1x RTX 4090","notes":"Consumer-GPU"},{"id":"awq","name":"AWQ INT4","vramGB":8,"quality":96,"recommendedGpu":"1x RTX 3090","notes":"Older consumer GPU"},{"id":"gguf-q4","name":"GGUF Q4_K_M","vramGB":9,"quality":94,"recommendedGpu":"1x RTX 3090","notes":"Edge / Mac M-series"}]}

2026-05-24/oss-tools.jsonl ADDED Viewed

	@@ -0,0 +1,25 @@

+{"id":"ollama","name":"Ollama","vendor":"Ollama","category":"runtime","language":"Go","license":"MIT","starsK":105,"version":"0.5.x","released":"2023-07","features":["model library","one-line install","OpenAI-compatible API","GGUF native"],"url":"https://ollama.com","github":"https://github.com/ollama/ollama","notes":"Most-installed local LLM runtime. Mac / Linux / Windows. Curated model library; one command to pull and run."}
+{"id":"lm-studio","name":"LM Studio","vendor":"LM Studio","category":"runtime","language":"TypeScript / C++","license":"Proprietary (free)","starsK":0,"version":"0.3.x","released":"2023-05","features":["GUI","GGUF + MLX","OpenAI-compatible server","multi-model loading"],"url":"https://lmstudio.ai","github":"https://github.com/lmstudio-ai","notes":"Polished desktop app. Best for non-CLI users running local models. Free for personal use; commercial license required."}
+{"id":"llama-cpp","name":"llama.cpp","vendor":"Georgi Gerganov","category":"runtime","language":"C++","license":"MIT","starsK":75,"version":"0.0.x (rolling)","released":"2023-03","features":["GGUF","CPU + GPU + Metal","quantization","server mode"],"url":"https://github.com/ggerganov/llama.cpp","github":"https://github.com/ggerganov/llama.cpp","notes":"The reference open-source LLM inference engine. Originated GGUF format. Powers Ollama and most other local runtimes."}
+{"id":"vllm","name":"vLLM","vendor":"UC Berkeley + community","category":"inference-server","language":"Python / CUDA","license":"Apache-2.0","starsK":36,"version":"0.7.x","released":"2023-06","features":["PagedAttention","continuous batching","tensor parallelism","OpenAI-compatible API","speculative decoding"],"url":"https://github.com/vllm-project/vllm","github":"https://github.com/vllm-project/vllm","notes":"Highest-throughput open-source inference server. Production default for self-hosted multi-GPU LLM serving."}
+{"id":"sglang","name":"SGLang","vendor":"LMSYS Org + community","category":"inference-server","language":"Python / CUDA","license":"Apache-2.0","starsK":9,"version":"0.4.x","released":"2024-01","features":["RadixAttention","structured generation","MoE-optimized","tensor + expert parallelism"],"url":"https://github.com/sgl-project/sglang","github":"https://github.com/sgl-project/sglang","notes":"High-performance inference engine that often matches or beats vLLM throughput. Strong on MoE models (DeepSeek, Llama 4)."}
+{"id":"tgi","name":"Text Generation Inference (TGI)","vendor":"Hugging Face","category":"inference-server","language":"Rust","license":"Apache-2.0","starsK":9,"version":"3.0.x","released":"2023-04","features":["continuous batching","tensor parallelism","speculative decoding","LoRA serving"],"url":"https://github.com/huggingface/text-generation-inference","github":"https://github.com/huggingface/text-generation-inference","notes":"Hugging Face's production inference server. Powers HF Inference Endpoints. Multi-LoRA serving."}
+{"id":"tei","name":"Text Embeddings Inference","vendor":"Hugging Face","category":"inference-server","language":"Rust","license":"Apache-2.0","starsK":3,"version":"1.5.x","released":"2024-01","features":["embedding model serving","reranker support","GPU + CPU","OpenAI-compatible API"],"url":"https://github.com/huggingface/text-embeddings-inference","github":"https://github.com/huggingface/text-embeddings-inference","notes":"Production embedding-server. Drop-in for OpenAI embeddings API. Faster than vanilla sentence-transformers."}
+{"id":"mlx","name":"MLX","vendor":"Apple","category":"runtime","language":"Python / C++","license":"MIT","starsK":18,"version":"0.21.x","released":"2023-12","features":["Apple Silicon native","unified memory","lazy execution","distributed training"],"url":"https://github.com/ml-explore/mlx","github":"https://github.com/ml-explore/mlx","notes":"Apple's ML framework, optimized for M-series chips. Strong inference + fine-tuning on Mac Studio (128GB unified memory)."}
+{"id":"mlc-llm","name":"MLC LLM","vendor":"MLC AI Team","category":"runtime","language":"Python / C++","license":"Apache-2.0","starsK":19,"version":"0.18.x","released":"2023-04","features":["cross-platform compilation","WebGPU","Android + iOS deployment","TVM-based"],"url":"https://github.com/mlc-ai/mlc-llm","github":"https://github.com/mlc-ai/mlc-llm","notes":"Compile LLMs to run anywhere: web browsers (WebGPU), iOS, Android, embedded. Best fit for on-device inference research."}
+{"id":"exllamav2","name":"ExLlamaV2","vendor":"turboderp","category":"runtime","language":"Python / C++","license":"MIT","starsK":4,"version":"0.2.x","released":"2023-09","features":["EXL2 quantization","speculative decoding","multi-GPU split"],"url":"https://github.com/turboderp/exllamav2","github":"https://github.com/turboderp/exllamav2","notes":"High-throughput inference for quantized models on consumer GPUs. EXL2 quantization is uniquely flexible per-layer."}
+{"id":"kobold-cpp","name":"KoboldCpp","vendor":"LostRuins + community","category":"runtime","language":"C++","license":"AGPL-3.0","starsK":6,"version":"rolling","released":"2023-04","features":["GGUF","creative writing UI","image gen","multimodal"],"url":"https://github.com/LostRuins/koboldcpp","github":"https://github.com/LostRuins/koboldcpp","notes":"Single-binary local LLM with creative-writing UI. Popular in roleplay / fiction communities."}
+{"id":"unsloth","name":"Unsloth","vendor":"Unsloth AI","category":"fine-tuning","language":"Python","license":"Apache-2.0","starsK":18,"version":"2025.1","released":"2023-11","features":["2x faster QLoRA","50% less VRAM","Llama / Mistral / Qwen support","free Colab"],"url":"https://unsloth.ai","github":"https://github.com/unslothai/unsloth","notes":"Fastest open QLoRA fine-tuning library. Free tier runs on Google Colab. Strong adoption in indie fine-tuner community."}
+{"id":"axolotl","name":"Axolotl","vendor":"OpenAccess AI Collective","category":"fine-tuning","language":"Python","license":"Apache-2.0","starsK":8,"version":"0.7.x","released":"2023-05","features":["YAML-driven config","LoRA + QLoRA + full SFT + DPO","multi-GPU","large-scale recipes"],"url":"https://axolotl.ai","github":"https://github.com/axolotl-ai-cloud/axolotl","notes":"YAML-config fine-tuning toolkit. The default for production-scale custom training runs."}
+{"id":"torchtune","name":"TorchTune","vendor":"Meta","category":"fine-tuning","language":"Python","license":"BSD-3-Clause","starsK":4,"version":"0.5.x","released":"2024-04","features":["PyTorch-native","distributed training","LoRA + QLoRA + full","composable recipes"],"url":"https://github.com/pytorch/torchtune","github":"https://github.com/pytorch/torchtune","notes":"Meta's official PyTorch fine-tuning library. Pure-PyTorch (no abstractions). Strongest distributed-training story in OSS."}
+{"id":"open-webui","name":"Open WebUI","vendor":"Open WebUI community","category":"ui","language":"Python / Svelte","license":"BSD-3-Clause","starsK":53,"version":"0.5.x","released":"2023-10","features":["ChatGPT-style UI","Ollama integration","RAG","function calling","multi-user"],"url":"https://openwebui.com","github":"https://github.com/open-webui/open-webui","notes":"Most-deployed local LLM UI. Self-hostable; supports Ollama, OpenAI, and any compatible API. Multi-user out of the box."}
+{"id":"librechat","name":"LibreChat","vendor":"Danny Avila","category":"ui","language":"TypeScript / Node","license":"MIT","starsK":23,"version":"0.7.x","released":"2023-04","features":["multi-provider","plugins","MCP support","workflows","agents"],"url":"https://www.librechat.ai","github":"https://github.com/danny-avila/LibreChat","notes":"Self-hosted multi-LLM chat UI. Strong agent + MCP integration in 2025. Production-ready alternative to ChatGPT for orgs that want control."}
+{"id":"jan","name":"Jan","vendor":"Menlo Research","category":"ui","language":"TypeScript / Tauri","license":"AGPL-3.0","starsK":25,"version":"0.5.x","released":"2024-01","features":["offline-first","GGUF + Cortex backend","extensions","electron-style UI"],"url":"https://jan.ai","github":"https://github.com/menloresearch/jan","notes":"Local desktop AI app with offline-first ethos. Cortex backend; OpenAI-compatible API. Polished consumer-grade UX."}
+{"id":"lm-eval-harness","name":"lm-evaluation-harness","vendor":"EleutherAI","category":"eval","language":"Python","license":"MIT","starsK":9,"version":"0.4.x","released":"2020-11","features":["200+ benchmark tasks","multi-backend (HF, vLLM, OpenAI)","reproducible scoring","few-shot evaluation"],"url":"https://github.com/EleutherAI/lm-evaluation-harness","github":"https://github.com/EleutherAI/lm-evaluation-harness","notes":"The reference open-source eval harness. Powers HF Open LLM Leaderboard. The standard for \"can I reproduce a benchmark score.\""}
+{"id":"inspect-ai","name":"Inspect AI","vendor":"UK AISI","category":"eval","language":"Python","license":"MIT","starsK":1,"version":"0.3.x","released":"2024-05","features":["agentic eval","tool-use scoring","human-in-the-loop","reproducible runs"],"url":"https://inspect.ai-safety-institute.org.uk","github":"https://github.com/UKGovernmentBEIS/inspect_ai","notes":"UK AI Safety Institute's eval framework. Designed for agentic + tool-use evaluations. Used in their pre-deployment red-teams."}
+{"id":"opik","name":"Opik","vendor":"Comet","category":"observability","language":"Python / TypeScript","license":"Apache-2.0","starsK":4,"version":"1.5.x","released":"2024-09","features":["LLM tracing","eval scoring","feedback loops","self-host or cloud"],"url":"https://www.comet.com/site/products/opik/","github":"https://github.com/comet-ml/opik","notes":"OSS LLM observability + evaluation. Trace any LangChain / LlamaIndex / OpenAI run. Free self-host; paid cloud tier."}
+{"id":"langfuse","name":"Langfuse","vendor":"Langfuse","category":"observability","language":"TypeScript / Python","license":"MIT","starsK":8,"version":"3.x","released":"2023-08","features":["LLM tracing","prompt management","datasets + evals","self-host"],"url":"https://langfuse.com","github":"https://github.com/langfuse/langfuse","notes":"Most-deployed open LLM observability platform. Free self-host; managed cloud tier. Strong fit for LangGraph / LangChain stacks."}
+{"id":"comfyui","name":"ComfyUI","vendor":"comfyanonymous","category":"ui","language":"Python","license":"GPL-3.0","starsK":65,"version":"0.3.x","released":"2023-01","features":["node-graph UI","diffusion model support","video","3D extensions","custom nodes"],"url":"https://www.comfy.org","github":"https://github.com/comfyanonymous/ComfyUI","notes":"Node-based UI for diffusion models. The default for advanced image / video workflow construction. Powers most production creative pipelines."}
+{"id":"sd-webui","name":"AUTOMATIC1111 / Stable Diffusion WebUI","vendor":"AUTOMATIC1111","category":"ui","language":"Python","license":"AGPL-3.0","starsK":145,"version":"1.10.x","released":"2022-08","features":["Stable Diffusion","extensions","LoRA","inpainting","animation"],"url":"https://github.com/AUTOMATIC1111/stable-diffusion-webui","github":"https://github.com/AUTOMATIC1111/stable-diffusion-webui","notes":"Most-installed Stable Diffusion UI. Massive plugin ecosystem. Slowly losing ground to ComfyUI and Forge for new workflows."}
+{"id":"onnxruntime","name":"ONNX Runtime","vendor":"Microsoft","category":"edge","language":"C++ / Python / Java","license":"MIT","starsK":16,"version":"1.20.x","released":"2018-12","features":["cross-platform","mobile + web","quantization","CPU + GPU"],"url":"https://onnxruntime.ai","github":"https://github.com/microsoft/onnxruntime","notes":"Production ONNX runtime. Best fit for deploying small models to mobile / browser / embedded. Powers Windows Copilot+."}
+{"id":"tinygrad","name":"tinygrad","vendor":"tinycorp / George Hotz","category":"training","language":"Python","license":"MIT","starsK":28,"version":"0.10.x","released":"2020-11","features":["minimal ML framework","multiple accelerators","lazy compute graph"],"url":"https://tinygrad.org","github":"https://github.com/tinygrad/tinygrad","notes":"Minimalist deep learning framework. <10k LOC core. Backs Tinybox products (consumer-grade compute boxes)."}

2026-05-24/podcasts.jsonl ADDED Viewed

	@@ -0,0 +1,50 @@

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+{"id":"livecodebench","name":"LiveCodeBench","publisher":"UC Berkeley + UW","scope":"Competitive programming problems released after model training cutoff","updateCadence":"monthly (new problems)","scoreType":"% pass@1","domain":"code","live":true,"hasAPI":false,"url":"https://livecodebench.github.io/leaderboard.html","notes":"Contamination-free by construction (problems pulled from after training cutoff). The contamination-resistant complement to HumanEval."}
+{"id":"bigcodebench","name":"BigCodeBench","publisher":"BigCode","scope":"1140 hard programming tasks with library usage","updateCadence":"as submissions land","scoreType":"% pass@1","domain":"code","live":true,"hasAPI":false,"url":"https://huggingface.co/spaces/bigcode/bigcodebench-leaderboard","notes":"Multi-library code benchmark. Tests realistic code that imports + composes external libraries. Harder than HumanEval/MBPP for the same models."}
+{"id":"terminal-bench","name":"Terminal-Bench Leaderboard","publisher":"Stanford + Anthropic","scope":"Agentic terminal tasks with deterministic post-conditions","updateCadence":"as submissions land","scoreType":"% solved","domain":"agent","live":true,"hasAPI":false,"url":"https://www.tbench.ai","notes":"The terminal-shaped agent benchmark. Tests the loop, not just the model. Frontier ~52% as of 2026."}
+{"id":"arc-prize","name":"ARC Prize Leaderboard","publisher":"ARC Prize Foundation","scope":"Abstract pattern-matching (ARC-AGI-1 + ARC-AGI-2)","updateCadence":"as submissions land","scoreType":"% solved","domain":"reasoning","live":true,"hasAPI":false,"url":"https://arcprize.org/leaderboard","notes":"Francois Chollet's benchmark. ARC-AGI-2 is the contamination-resistant successor. Most models lag far behind humans."}
+{"id":"mmlu-pro","name":"MMLU-Pro Leaderboard","publisher":"TIGER Lab","scope":"General knowledge + reasoning across 57 subjects","updateCadence":"as submissions land","scoreType":"% accuracy","domain":"general","live":true,"hasAPI":false,"url":"https://huggingface.co/spaces/TIGER-Lab/MMLU-Pro","notes":"Successor to MMLU. The standard knowledge + reasoning benchmark in 2024-2026."}
+{"id":"hle-leaderboard","name":"Humanity's Last Exam","publisher":"CAIS + Scale AI","scope":"3,000 expert-validated PhD-hard questions across 100+ disciplines","updateCadence":"as submissions land","scoreType":"% accuracy","domain":"reasoning","live":true,"hasAPI":false,"url":"https://lastexam.ai","notes":"Hardest broad-knowledge benchmark in 2025-2026. Frontier ~30%. Every major lab reports against this."}
+{"id":"mmmu","name":"MMMU Leaderboard","publisher":"TIGER Lab","scope":"College-level multimodal questions across 30 subjects","updateCadence":"as submissions land","scoreType":"% accuracy","domain":"multimodal","live":true,"hasAPI":false,"url":"https://mmmu-benchmark.github.io","notes":"Standard vision-LLM benchmark. Frontier ~78% as of 2026."}
+{"id":"video-arena","name":"Artificial Analysis Video Arena","publisher":"Artificial Analysis","scope":"Video generation models (Sora, Veo, Kling, HappyHorse, Runway)","updateCadence":"continuous","scoreType":"Elo (human pairwise vote)","domain":"video","live":true,"hasAPI":false,"url":"https://artificialanalysis.ai/text-to-video/arena","notes":"Live Elo for video models. Alibaba HappyHorse 1.0 leads as of late April 2026."}
+{"id":"image-arena","name":"Artificial Analysis Image Arena","publisher":"Artificial Analysis","scope":"Image generation models (FLUX, Midjourney, DALL-E, Imagen, Recraft)","updateCadence":"continuous","scoreType":"Elo (human pairwise vote)","domain":"image","live":true,"hasAPI":false,"url":"https://artificialanalysis.ai/text-to-image/arena","notes":"Live Elo for image models. FLUX 1.1 Pro Ultra and Recraft v3 trade the top spot through 2025-2026."}
+{"id":"tts-arena","name":"TTS Arena","publisher":"Hugging Face","scope":"TTS models (ElevenLabs, Cartesia, OpenAI, Deepgram)","updateCadence":"continuous","scoreType":"Elo (human pairwise vote)","domain":"voice","live":true,"hasAPI":false,"url":"https://huggingface.co/spaces/TTS-AGI/TTS-Arena","notes":"Live Elo for TTS quality. Eleven v3 leads as of late April 2026. TensorFeed mirrors top entries at /voice-leaderboards."}
+{"id":"open-asr","name":"Open ASR Leaderboard","publisher":"Hugging Face","scope":"STT models on LibriSpeech + Common Voice + AMI + GigaSpeech","updateCadence":"as submissions land","scoreType":"Word Error Rate","domain":"voice","live":true,"hasAPI":true,"url":"https://huggingface.co/spaces/hf-audio/open_asr_leaderboard","notes":"Aggregated ASR benchmark. AssemblyAI Universal-2 leads English WER as of late 2025."}
+{"id":"ruler-leaderboard","name":"RULER Leaderboard","publisher":"NVIDIA","scope":"Long-context retrieval and reasoning (effective vs claimed length)","updateCadence":"as submissions land","scoreType":"% accuracy at varying context lengths","domain":"long-context","live":true,"hasAPI":false,"url":"https://github.com/NVIDIA/RULER","notes":"Reveals the gap between claimed and effective context length. Frontier 1M-context models show ~256k effective."}
+{"id":"gaia-leaderboard","name":"GAIA Leaderboard","publisher":"Hugging Face + Meta","scope":"General assistant agents on 466 real-world questions","updateCadence":"as submissions land","scoreType":"% accuracy by difficulty level","domain":"agent","live":true,"hasAPI":false,"url":"https://huggingface.co/spaces/gaia-benchmark/leaderboard","notes":"Tests the full agent loop: web browsing, file ops, multi-step reasoning. Three difficulty levels."}
+{"id":"webarena","name":"WebArena Leaderboard","publisher":"CMU + UW","scope":"Browser agents on 812 tasks across 5 simulated websites","updateCadence":"as submissions land","scoreType":"% solved","domain":"agent","live":true,"hasAPI":false,"url":"https://webarena.dev/leaderboard","notes":"The browser-automation agent benchmark. Tests realistic web interaction. Frontier ~58% as of 2026."}
+{"id":"osworld-leaderboard","name":"OSWorld Leaderboard","publisher":"HKU + Salesforce","scope":"Computer-use agents on 369 tasks across Ubuntu, Windows, macOS","updateCadence":"as submissions land","scoreType":"% solved","domain":"agent","live":true,"hasAPI":false,"url":"https://os-world.github.io","notes":"Hardest agent benchmark in 2026. Real desktops, file management, app interaction. Frontier ~28%."}

2026-05-24/specialized-models.jsonl ADDED Viewed

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+{"id":"codestral-25.01","name":"Codestral 25.01","publisher":"Mistral","domain":"code","params":"22B","pricing":"$0.30 input / $0.90 output per 1M tokens via la Plateforme","openWeights":true,"license":"Mistral Non-Production License","released":"2025-01","benchmark":"HumanEval 86.6% pass@1","capabilities":["code completion","fill-in-the-middle","80+ languages","256k context"],"url":"https://mistral.ai/news/codestral-2501/","notes":"Mistral's flagship code model. 256k context, 80+ programming languages. License is non-commercial without a Mistral subscription."}
+{"id":"deepseek-coder-v3","name":"DeepSeek Coder V3","publisher":"DeepSeek","domain":"code","params":"236B MoE / 21B active","pricing":"$0.14 input / $0.28 output per 1M tokens via DeepSeek API","openWeights":true,"license":"MIT","released":"2025-12","benchmark":"HumanEval 90.2%, SWE-Bench Verified 65.4%","capabilities":["code generation","cross-language","repository-level","128k context"],"url":"https://github.com/deepseek-ai/DeepSeek-Coder-V3","notes":"MIT-licensed frontier code model. Cheapest code-specialized API in 2026. Strong on repo-level code understanding."}
+{"id":"qwen-coder-2.5-32b","name":"Qwen 2.5 Coder 32B","publisher":"Alibaba","domain":"code","params":"32B","pricing":"Open weights, free to self-host","openWeights":true,"license":"Apache-2.0","released":"2024-11","benchmark":"HumanEval 92.7%, MBPP 90.2%","capabilities":["code completion","code repair","40+ languages","128k context"],"url":"https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct","notes":"Apache-2.0 dense code model that punches above its parameter count. Strong default for self-hosted code assistant agents."}
+{"id":"starcoder-2-15b","name":"StarCoder 2 15B","publisher":"BigCode","domain":"code","params":"15B","pricing":"Open weights, free to self-host","openWeights":true,"license":"BigCode OpenRAIL-M","released":"2024-02","benchmark":"HumanEval 46.3% pass@1","capabilities":["code completion","fill-in-the-middle","600+ languages","16k context"],"url":"https://huggingface.co/bigcode/starcoder2-15b","notes":"Reproducible: trained on The Stack v2 (open dataset). Best fit for academic / regulated code-completion deployments."}
+{"id":"med-gemini","name":"Med-Gemini","publisher":"Google","domain":"medical","params":"undisclosed","pricing":"Cloud Healthcare API; usage-based","openWeights":false,"license":"Proprietary","released":"2024-04","benchmark":"MedQA-USMLE 91.1%","capabilities":["clinical Q&A","medical imaging","EHR summarization","long-context records"],"url":"https://research.google/blog/advancing-medical-ai-with-med-gemini/","notes":"Google's flagship medical LLM. Multimodal (radiology, dermatology). Strongest published MedQA score. Available via Google Cloud Healthcare APIs."}
+{"id":"meditron-3","name":"Meditron 3 70B","publisher":"EPFL","domain":"medical","params":"70B","pricing":"Open weights, free to self-host","openWeights":true,"license":"Llama 3 Community License","released":"2025-04","benchmark":"MedQA-USMLE 78.6%, USMLE step 1-3 ~85%","capabilities":["clinical Q&A","literature synthesis","differential diagnosis"],"url":"https://huggingface.co/epfl-llm/meditron-70b","notes":"EPFL's open medical LLM, continued pretraining of Llama 3. The strongest open-weights medical model. Used as research baseline for clinical-AI evaluation."}
+{"id":"biomistral","name":"BioMistral 7B","publisher":"BioMistral collaboration","domain":"medical","params":"7B","pricing":"Open weights, free to self-host","openWeights":true,"license":"Apache-2.0","released":"2024-02","benchmark":"MedQA-USMLE 49.6%","capabilities":["biomedical Q&A","drug interactions","literature retrieval"],"url":"https://huggingface.co/BioMistral/BioMistral-7B","notes":"Mistral 7B continued-pretrained on PubMed. Apache-licensed; small enough to self-host on a single consumer GPU. Good base for medical RAG agents."}
+{"id":"saul-lm-141b","name":"SaulLM 141B","publisher":"Equall","domain":"legal","params":"141B (Mixtral-based)","pricing":"Open weights, free to self-host","openWeights":true,"license":"MIT","released":"2024-07","benchmark":"LegalBench 71.3%","capabilities":["legal Q&A","contract review","case law summarization","multilingual legal"],"url":"https://huggingface.co/Equall/SaulLM-141B-Instruct","notes":"Largest open legal LLM. Continued pretraining of Mixtral 8x22B on legal corpora. Strong on EU + US case law."}
+{"id":"saul-lm-7b","name":"SaulLM 7B","publisher":"Equall","domain":"legal","params":"7B","pricing":"Open weights, free to self-host","openWeights":true,"license":"MIT","released":"2024-03","benchmark":"LegalBench 60.7%","capabilities":["legal Q&A","contract clauses","case briefing"],"url":"https://huggingface.co/Equall/Saul-7B-Base","notes":"Smaller SaulLM; runs on consumer GPU at Q4. Solid base for legal RAG agents."}
+{"id":"fingpt-v3","name":"FinGPT v3","publisher":"AI4Finance Foundation","domain":"finance","params":"7B-13B (LoRA on Llama)","pricing":"Open weights, free to self-host","openWeights":true,"license":"MIT","released":"2024-08","benchmark":"Financial sentiment FPB ~88%","capabilities":["financial sentiment","earnings call analysis","news classification","forecasting"],"url":"https://github.com/AI4Finance-Foundation/FinGPT","notes":"Open finance models maintained by AI4Finance Foundation. LoRA adapters on Llama 3.x base. Best fit for sentiment + classification rather than reasoning."}
+{"id":"bloomberggpt","name":"BloombergGPT","publisher":"Bloomberg","domain":"finance","params":"50B","pricing":"Internal Bloomberg use only (not public)","openWeights":false,"license":"Proprietary","released":"2023-03","benchmark":"FPB sentiment ~85%","capabilities":["financial NER","sentiment","document classification","earnings analysis"],"url":"https://www.bloomberg.com/company/press/bloomberggpt-50-billion-parameter-llm-tuned-finance/","notes":"Bloomberg's in-house finance LLM. Trained on a private 363B-token finance corpus. Reference for \"what does a finance-specialized base model look like\" but not externally usable."}
+{"id":"suno-v4","name":"Suno v4","publisher":"Suno","domain":"music","params":"undisclosed","pricing":"Subscription from $10/mo; API limited beta","openWeights":false,"license":"Proprietary","released":"2024-11","benchmark":null,"capabilities":["lyrics + music","genre control","instrumental","extend / remix"],"url":"https://suno.com","notes":"Frontier music generation. v4 ships full-song generation up to 4 minutes with vocals. The default for music-gen agents that need polished output."}
+{"id":"udio","name":"Udio","publisher":"Uncharted Labs","domain":"music","params":"undisclosed","pricing":"Subscription from $10/mo","openWeights":false,"license":"Proprietary","released":"2024-04","benchmark":null,"capabilities":["music gen","extend","remix","lyrics or instrumental"],"url":"https://www.udio.com","notes":"Suno competitor. Strong on instrumental quality and genre fidelity. Active legal contention with major labels in 2024-2026."}
+{"id":"musicgen-large","name":"MusicGen Large","publisher":"Meta","domain":"music","params":"3.3B","pricing":"Open weights, free to self-host","openWeights":true,"license":"CC-BY-NC-4.0","released":"2023-06","benchmark":null,"capabilities":["instrumental music gen","melody conditioning","audio continuation"],"url":"https://huggingface.co/facebook/musicgen-large","notes":"Open instrumental music model. Non-commercial license. Lower fidelity than Suno/Udio but the strongest open option for research."}
+{"id":"stable-audio-2","name":"Stable Audio 2.0","publisher":"Stability AI","domain":"music","params":"undisclosed","pricing":"API from $0.10 per 30s; free tier","openWeights":false,"license":"Stability commercial","released":"2024-04","benchmark":null,"capabilities":["music + SFX gen","3min clips","audio-to-audio","instrumental focus"],"url":"https://stability.ai/news/stable-audio-2-0","notes":"Stability's music + sound-effect model. Designed for sound design workflows; produces stems and SFX more cleanly than Suno."}
+{"id":"trellis","name":"TRELLIS","publisher":"Microsoft Research","domain":"3d","params":"2B","pricing":"Open weights, free to self-host","openWeights":true,"license":"MIT","released":"2024-12","benchmark":null,"capabilities":["image to 3D","text to 3D","mesh + gaussian splat output","PBR materials"],"url":"https://github.com/microsoft/TRELLIS","notes":"Microsoft Research 3D generative model. State-of-the-art image-to-3D quality. Outputs textured mesh, Gaussian splats, or radiance fields."}
+{"id":"hunyuan3d-2","name":"Hunyuan3D-2","publisher":"Tencent","domain":"3d","params":"4.5B (texture model)","pricing":"Open weights, free to self-host","openWeights":true,"license":"Tencent Hunyuan License","released":"2025-01","benchmark":null,"capabilities":["image to 3D mesh","PBR texture generation","animation rigging"],"url":"https://huggingface.co/tencent/Hunyuan3D-2","notes":"Tencent's open 3D model. Two-stage: shape generation + texture model. Strongest open 3D output quality in early 2025."}
+{"id":"colpali","name":"ColPali","publisher":"ILLUIN Technology","domain":"retrieval","params":"3B (PaliGemma-based)","pricing":"Open weights, free to self-host","openWeights":true,"license":"Apache-2.0","released":"2024-07","benchmark":"ViDoRe benchmark leader","capabilities":["vision-document retrieval","late interaction","PDF / chart understanding"],"url":"https://huggingface.co/vidore/colpali","notes":"Vision-document retrieval model. Embeds whole-page images directly, skipping OCR. Strong on PDFs with tables, charts, scientific figures."}
+{"id":"splade-v3","name":"SPLADE v3","publisher":"Naver Labs","domain":"retrieval","params":"110M","pricing":"Open weights, free to self-host","openWeights":true,"license":"CC-BY-NC-4.0","released":"2024-03","benchmark":"BEIR avg ~50.5","capabilities":["sparse retrieval","BM25-compatible inverted index","lexical match expansion"],"url":"https://huggingface.co/naver/splade-v3","notes":"Learned sparse retrieval. Drops into existing inverted-index infra (Elasticsearch, Lucene) without dense vector overhead. Strong hybrid-search complement to dense embeddings."}

2026-05-24/status.jsonl ADDED Viewed

	@@ -0,0 +1,21 @@

+{"name":"Claude API","provider":"Anthropic","status":"operational","statusPageUrl":"https://status.anthropic.com","components":[{"name":"claude.ai","status":"operational"},{"name":"Claude API (api.anthropic.com)","status":"operational"},{"name":"Claude Code","status":"operational"},{"name":"Claude Cowork","status":"operational"},{"name":"Claude for Government","status":"operational"},{"name":"Claude Console (platform.claude.com)","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.762Z"}
+{"name":"OpenAI API","provider":"OpenAI","status":"operational","statusPageUrl":"https://status.openai.com","components":[{"name":"Responses","status":"operational"},{"name":"Fine-tuning","status":"operational"},{"name":"Images","status":"operational"},{"name":"Batch","status":"operational"},{"name":"Moderations","status":"operational"},{"name":"Embeddings","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.284Z"}
+{"name":"Google Gemini","provider":"Google","status":"operational","statusPageUrl":"https://status.cloud.google.com","components":[{"name":"Inference API","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.269Z"}
+{"name":"GitHub Copilot","provider":"GitHub","status":"operational","statusPageUrl":"https://www.githubstatus.com","components":[{"name":"Copilot","status":"operational"},{"name":"Copilot AI Model Providers","status":"operational"},{"name":"Git Operations","status":"operational"},{"name":"Webhooks","status":"operational"},{"name":"API Requests","status":"operational"},{"name":"Issues","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.605Z"}
+{"name":"Perplexity","provider":"Perplexity AI","status":"operational","statusPageUrl":"https://status.perplexity.com","components":[{"name":"API","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.262Z"}
+{"name":"Groq","provider":"Groq","status":"operational","statusPageUrl":"https://groqstatus.com","components":[{"name":"meta-llama/llama-guard-4-12b","status":"operational"},{"name":"groq/compound-mini","status":"operational"},{"name":"Canopy Labs Orpheus Arabic Saudi","status":"operational"},{"name":"meta-llama/llama-4-scout-17b-16e-instruct","status":"operational"},{"name":"meta-llama/llama-prompt-guard-2-86m","status":"operational"},{"name":"moonshotai/kimi-k2-instruct-0905","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.319Z"}
+{"name":"AWS Bedrock","provider":"AWS","status":"operational","statusPageUrl":"https://health.aws.amazon.com/health/status","components":[{"name":"Bedrock API","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.339Z"}
+{"name":"Azure OpenAI","provider":"Microsoft Azure","status":"operational","statusPageUrl":"https://azure.status.microsoft/en-us/status","components":[{"name":"Azure OpenAI Service","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.330Z"}
+{"name":"Hugging Face","provider":"Hugging Face","status":"operational","statusPageUrl":"https://status.huggingface.co","components":[{"name":"API","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.472Z"}
+{"name":"Replicate","provider":"Replicate","status":"operational","statusPageUrl":"https://status.replicate.com","components":[{"name":"Support Tickets","status":"operational"},{"name":"Streaming API","status":"operational"},{"name":"HTTP API","status":"operational"},{"name":"Replicate Registry (r8.im)","status":"operational"},{"name":"CPU Hardware","status":"operational"},{"name":"Home Page","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.702Z"}
+{"name":"Cohere","provider":"Cohere","status":"operational","statusPageUrl":"https://status.cohere.com","components":[{"name":"Docs","status":"operational"},{"name":"Website","status":"operational"},{"name":"embeddings","status":"operational"},{"name":"embed-v4.0","status":"operational"},{"name":"command-a-reasoning-08-2025","status":"operational"},{"name":"command-a-03-2025","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.444Z"}
+{"name":"Mistral","provider":"Mistral AI","status":"operational","statusPageUrl":"https://status.mistral.ai","components":[{"name":"API","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.431Z"}
+{"name":"DeepSeek","provider":"DeepSeek","status":"unknown","statusPageUrl":"https://status.deepseek.com","components":[],"lastChecked":"2026-05-24T09:50:37.964Z"}
+{"name":"Together AI","provider":"Together AI","status":"operational","statusPageUrl":"https://status.together.ai","components":[{"name":"API","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.472Z"}
+{"name":"Fireworks AI","provider":"Fireworks AI","status":"operational","statusPageUrl":"https://status.fireworks.ai","components":[{"name":"API","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.564Z"}
+{"name":"OpenRouter","provider":"OpenRouter","status":"operational","statusPageUrl":"https://status.openrouter.ai","components":[{"name":"API","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.699Z"}
+{"name":"ElevenLabs","provider":"ElevenLabs","status":"operational","statusPageUrl":"https://status.elevenlabs.io","components":[{"name":"UI","status":"operational"},{"name":"Quality","status":"operational"},{"name":"Other","status":"operational"},{"name":"Other API endpoints","status":"operational"},{"name":"RAG","status":"operational"},{"name":"Telephony","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.601Z"}
+{"name":"Stability AI","provider":"Stability AI","status":"operational","statusPageUrl":"https://status.stability.ai","components":[{"name":"Stability.ai Platform & Services","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.586Z"}
+{"name":"Runway","provider":"Runway","status":"operational","statusPageUrl":"https://status.runwayml.com","components":[{"name":"Backend","status":"operational"},{"name":"Support","status":"operational"},{"name":"Public API","status":"operational"},{"name":"App","status":"operational"},{"name":"Billing","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.815Z"}
+{"name":"Luma","provider":"Luma AI","status":"operational","statusPageUrl":"https://status.lumalabs.ai","components":[{"name":"API","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.636Z"}
+{"name":"Hyperliquid","provider":"Hyperliquid","status":"operational","statusPageUrl":"https://hyperliquid.statuspage.io","components":[{"name":"Frontend","status":"operational"},{"name":"Hyperliquid L1","status":"operational"},{"name":"API","status":"operational"}],"lastChecked":"2026-05-24T09:50:37.834Z"}

2026-05-24/training-datasets.jsonl ADDED Viewed

	@@ -0,0 +1,19 @@

+{"id":"fineweb","name":"FineWeb","publisher":"Hugging Face","stage":"pretraining","contentType":"web text","tokens":"15T","items":"24B documents","license":"ODC-BY-1.0","languages":"English","released":"2024-04","url":"https://huggingface.co/datasets/HuggingFaceFW/fineweb","notes":"Refined CommonCrawl with aggressive quality filtering. Replaces RedPajama-1T as the de facto open pretraining corpus. The dataset behind most 2024-2025 open base models."}
+{"id":"fineweb-edu","name":"FineWeb-Edu","publisher":"Hugging Face","stage":"pretraining","contentType":"educational web text","tokens":"1.3T","items":"1.3B documents","license":"ODC-BY-1.0","languages":"English","released":"2024-05","url":"https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu","notes":"FineWeb subset filtered to educational content via Llama-3-70B classifier. Smaller models trained on FineWeb-Edu beat counterparts trained on full FineWeb at the same compute."}
+{"id":"common-crawl","name":"Common Crawl","publisher":"Common Crawl Foundation","stage":"pretraining","contentType":"web text","tokens":"petabyte-scale raw","items":"250B+ webpages","license":"CC-0","languages":"multilingual (200+)","released":"monthly since 2008","url":"https://commoncrawl.org","notes":"The raw web crawl every other web pretraining dataset is built on. Released monthly. Most labs filter it heavily before training."}
+{"id":"redpajama-v2","name":"RedPajama v2","publisher":"Together AI","stage":"pretraining","contentType":"web text","tokens":"30T","items":"100B+ documents","license":"MIT (filters), CC-BY (subsets)","languages":"English, German, French, Spanish, Italian","released":"2023-10","url":"https://huggingface.co/datasets/togethercomputer/RedPajama-Data-V2","notes":"Together AI's open reproduction of LLaMA-style pretraining data. v2 ships with 40+ pre-computed quality filters so labs can apply their own thresholds."}
+{"id":"the-pile","name":"The Pile","publisher":"EleutherAI","stage":"pretraining","contentType":"mixed (web + books + papers + code)","tokens":"825GB / 300B","items":"22 sub-corpora","license":"mixed (per-subcorpus)","languages":"English-focused","released":"2020","url":"https://pile.eleuther.ai","notes":"The original open pretraining corpus. Largely superseded by FineWeb / RedPajama for new training runs but still cited. Note: Books3 subset removed for copyright."}
+{"id":"dolma","name":"Dolma","publisher":"Allen AI (AI2)","stage":"pretraining","contentType":"web + code + books + papers","tokens":"3T","items":"mixed","license":"AI2 ImpACT (Medium Risk)","languages":"English","released":"2024-02","url":"https://huggingface.co/datasets/allenai/dolma","notes":"AI2's open pretraining corpus (the dataset behind OLMo). Documents source provenance and offers reproducible filters. The most-academically-cited open pretraining set."}
+{"id":"refinedweb","name":"RefinedWeb","publisher":"TII","stage":"pretraining","contentType":"web text","tokens":"5T","items":"600M documents","license":"ODC-BY-1.0","languages":"English","released":"2023-06","url":"https://huggingface.co/datasets/tiiuae/falcon-refinedweb","notes":"Behind the Falcon series. Aggressive deduplication and filtering. Older but cleaner than CommonCrawl raw."}
+{"id":"the-stack-v2","name":"The Stack v2","publisher":"BigCode (HuggingFace + ServiceNow)","stage":"pretraining","contentType":"source code","tokens":"67TB / 17B files","items":"17B files across 600+ languages","license":"permissive only (filtered)","languages":"600+ programming languages","released":"2024-02","url":"https://huggingface.co/datasets/bigcode/the-stack-v2","notes":"The reference open code-pretraining corpus. v2 is sourced from Software Heritage, dedup'd at file and near-dup level. Behind StarCoder 2 and most open code models."}
+{"id":"starcoderdata","name":"StarCoderData","publisher":"BigCode","stage":"pretraining","contentType":"source code + jupyter + GitHub issues","tokens":"305B","items":"86 languages","license":"mixed permissive","languages":"86 programming languages","released":"2023-05","url":"https://huggingface.co/datasets/bigcode/starcoderdata","notes":"Pre-cleaned subset of The Stack used to train StarCoder. Smaller than The Stack v2 but easier to work with for small-scale code-model experiments."}
+{"id":"tulu-3-sft-mix","name":"Tulu 3 SFT Mixture","publisher":"Allen AI","stage":"instruction-tuning","contentType":"instruction-response pairs","tokens":null,"items":"939K instructions","license":"ODC-BY-1.0","languages":"English","released":"2024-11","url":"https://huggingface.co/datasets/allenai/tulu-3-sft-mixture","notes":"Tulu 3 is the strongest open post-training recipe in 2024-2025. The SFT mixture combines OpenAssistant, ShareGPT, math reasoning, code instructions, and persona-aligned prompts."}
+{"id":"open-hermes-2.5","name":"OpenHermes 2.5","publisher":"Teknium / Nous Research","stage":"instruction-tuning","contentType":"multi-turn conversations","tokens":null,"items":"1M conversations","license":"mixed (per-source)","languages":"English","released":"2023-12","url":"https://huggingface.co/datasets/teknium/OpenHermes-2.5","notes":"Aggregated from GPT-4 outputs, AiroborosLM, ShareGPT, and others. The dataset behind Nous Hermes and many community fine-tunes."}
+{"id":"glaive-function-calling","name":"Glaive Function Calling v2","publisher":"Glaive AI","stage":"instruction-tuning","contentType":"function-calling traces","tokens":null,"items":"113K examples","license":"Apache-2.0","languages":"English","released":"2023-12","url":"https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2","notes":"Synthetic function-calling traces. The most-cited dataset for fine-tuning open models to do reliable JSON tool use."}
+{"id":"open-orca","name":"OpenOrca","publisher":"Open Orca team","stage":"instruction-tuning","contentType":"reasoning traces","tokens":null,"items":"4.2M GPT-4 + 0.7M GPT-3.5 examples","license":"MIT","languages":"English","released":"2023-07","url":"https://huggingface.co/datasets/Open-Orca/OpenOrca","notes":"Reproduction of Microsoft Orca paper. Augments FLAN tasks with GPT-4 chain-of-thought traces. Strong base for math/reasoning fine-tunes."}
+{"id":"agent-instruct","name":"AgentInstruct","publisher":"Microsoft Research","stage":"instruction-tuning","contentType":"agentic task traces","tokens":null,"items":"25M agent-shaped instruction pairs","license":"CDLA-Permissive-2.0","languages":"English","released":"2024-07","url":"https://huggingface.co/datasets/microsoft/AgentInstruct-1M-v1","notes":"Synthetic dataset for agent training. Multi-step tool-use, reading comprehension, code, RAG, brain teasers, content creation. Behind Orca-3 and used in Phi-3.5."}
+{"id":"ultrafeedback","name":"UltraFeedback","publisher":"OpenBMB","stage":"dpo","contentType":"preference pairs","tokens":null,"items":"64K instructions x 4 model responses","license":"MIT","languages":"English","released":"2023-10","url":"https://huggingface.co/datasets/openbmb/UltraFeedback","notes":"Most-used DPO dataset for open models. GPT-4 ranks 4 candidate responses per prompt across helpfulness, honesty, instruction-following, truthfulness."}
+{"id":"tulu-3-pref","name":"Tulu 3 Preference Mixture","publisher":"Allen AI","stage":"dpo","contentType":"preference pairs","tokens":null,"items":"270K preference pairs","license":"ODC-BY-1.0","languages":"English","released":"2024-11","url":"https://huggingface.co/datasets/allenai/llama-3.1-tulu-3-70b-preference-mixture","notes":"Curated preference pairs for the Tulu 3 DPO stage. The strongest open preference data for post-training in late 2024."}
+{"id":"helpsteer-2","name":"HelpSteer 2","publisher":"NVIDIA","stage":"dpo","contentType":"preference pairs (5-attribute)","tokens":null,"items":"21K conversations","license":"CC-BY-4.0","languages":"English","released":"2024-06","url":"https://huggingface.co/datasets/nvidia/HelpSteer2","notes":"NVIDIA preference data labeled across helpfulness, correctness, coherence, complexity, verbosity. Strong for multi-attribute reward modeling."}
+{"id":"laion-5b","name":"LAION-5B","publisher":"LAION","stage":"multimodal","contentType":"image-text pairs","tokens":null,"items":"5.85B image-text pairs","license":"CC-BY-4.0","languages":"multilingual","released":"2022-03","url":"https://laion.ai/blog/laion-5b/","notes":"Largest open image-text dataset. Behind Stable Diffusion and many open image models. Original release was withdrawn for review; v2 reissued 2023."}
+{"id":"datacomp-1b","name":"DataComp-1B","publisher":"DataComp","stage":"multimodal","contentType":"image-text pairs","tokens":null,"items":"1.4B filtered pairs","license":"mixed","languages":"multilingual","released":"2023","url":"https://www.datacomp.ai","notes":"Filtered subset of CommonPool. Reproducible filtering recipes are part of the contribution. Behind several open CLIP-class models trained in 2024."}

2026-05-24/training-runs.jsonl ADDED Viewed

	@@ -0,0 +1,11 @@

+{"id":"gpt-5.5","model":"GPT-5.5","publisher":"OpenAI","released":"2026-04","activeParamsB":null,"totalParamsB":1500,"trainingTokens":"~16T (estimated)","hardware":"NVIDIA H200 + Blackwell","hardwareCount":75000,"computeHours":"~3.5 billion GPU-hours (estimated)","estimatedCostMillionUSD":800,"costSource":"estimated","duration":"~6 months","openWeights":false,"url":"https://openai.com/index/gpt-5-5/","notes":"OpenAI flagship. Numbers reverse-engineered from public hints; OpenAI does not disclose officially. Estimated ~$800M in compute alone."}
+{"id":"claude-opus-4-7","model":"Claude Opus 4.7","publisher":"Anthropic","released":"2026-04","activeParamsB":null,"totalParamsB":null,"trainingTokens":"undisclosed","hardware":"AWS Trainium 2 + NVIDIA H200","hardwareCount":null,"computeHours":null,"estimatedCostMillionUSD":null,"costSource":"estimated","duration":"undisclosed","openWeights":false,"url":"https://www.anthropic.com/news/claude-opus-4-7","notes":"Anthropic does not disclose training run details. Co-trained on Trainium 2 (Anthropic-AWS partnership) and H200. Cost estimate withheld for lack of public signal."}
+{"id":"deepseek-v4-pro","model":"DeepSeek V4 Pro","publisher":"DeepSeek","released":"2026-04","activeParamsB":37,"totalParamsB":1600,"trainingTokens":"14T","hardware":"NVIDIA H800","hardwareCount":4096,"computeHours":"5.5M GPU-hours","estimatedCostMillionUSD":6.5,"costSource":"disclosed","duration":"~55 days","openWeights":true,"url":"https://www.deepseek.com","notes":"MIT-licensed frontier MoE. The disclosed $6.5M training cost is the cheapest cited frontier-class run by an order of magnitude vs Western labs. Sparse activation + FP8 + MoE = unusually compute-efficient."}
+{"id":"llama-4-maverick","model":"Llama 4 Maverick","publisher":"Meta","released":"2026-04","activeParamsB":17,"totalParamsB":400,"trainingTokens":"22T","hardware":"NVIDIA H100","hardwareCount":32000,"computeHours":"~150M GPU-hours (estimated)","estimatedCostMillionUSD":220,"costSource":"estimated","duration":"~5 months","openWeights":true,"url":"https://ai.meta.com/blog/llama-4/","notes":"Meta's frontier MoE. 22T training tokens reported; first major model trained on the 32k H100 cluster Meta announced in 2024. Cost estimated based on cluster-hour rates."}
+{"id":"gemini-2.5-pro","model":"Gemini 2.5 Pro","publisher":"Google","released":"2026-01","activeParamsB":null,"totalParamsB":null,"trainingTokens":"undisclosed","hardware":"Google TPU v5p","hardwareCount":null,"computeHours":null,"estimatedCostMillionUSD":null,"costSource":"estimated","duration":"undisclosed","openWeights":false,"url":"https://deepmind.google/models/gemini/","notes":"Google does not disclose Gemini training details. Trained on TPU v5p pods (8960-chip topology). 1M context with strong long-context retention."}
+{"id":"gpt-4","model":"GPT-4","publisher":"OpenAI","released":"2023-03","activeParamsB":280,"totalParamsB":1760,"trainingTokens":"~13T (estimated)","hardware":"NVIDIA A100","hardwareCount":25000,"computeHours":"~270M GPU-hours (estimated)","estimatedCostMillionUSD":100,"costSource":"estimated","duration":"~3 months","openWeights":false,"url":"https://openai.com/index/gpt-4-research/","notes":"Reverse-engineered numbers from public leaks (1.76T MoE, 280B active). The reference point for \"what did frontier training cost in 2023.\" Made obsolete in compute terms by H100/H200/Blackwell era."}
+{"id":"llama-3.1-405b","model":"Llama 3.1 405B","publisher":"Meta","released":"2024-07","activeParamsB":405,"totalParamsB":405,"trainingTokens":"15T","hardware":"NVIDIA H100","hardwareCount":16000,"computeHours":"30.84M GPU-hours","estimatedCostMillionUSD":60,"costSource":"disclosed","duration":"~54 days","openWeights":true,"url":"https://ai.meta.com/research/publications/the-llama-3-herd-of-models/","notes":"The most-detailed open training run disclosure of 2024. 30.84M H100-hours documented in the paper. Base for 2024-2025 reasoning about what dense 405B costs."}
+{"id":"deepseek-v3","model":"DeepSeek V3","publisher":"DeepSeek","released":"2024-12","activeParamsB":37,"totalParamsB":671,"trainingTokens":"14.8T","hardware":"NVIDIA H800","hardwareCount":2048,"computeHours":"2.788M GPU-hours","estimatedCostMillionUSD":5.6,"costSource":"disclosed","duration":"~57 days","openWeights":true,"url":"https://github.com/deepseek-ai/DeepSeek-V3","notes":"The training run that triggered the \"are we overspending on AI compute\" debate. $5.6M disclosed cost vs ~$60M for Llama 3.1 405B at comparable performance. Sparked global market reaction in late January 2025."}
+{"id":"olmo-2-32b","model":"OLMo 2 32B","publisher":"Allen AI","released":"2025-03","activeParamsB":32,"totalParamsB":32,"trainingTokens":"6T","hardware":"AMD MI250X / NVIDIA H100","hardwareCount":null,"computeHours":"documented in paper","estimatedCostMillionUSD":1.5,"costSource":"estimated","duration":"~2 months","openWeights":true,"url":"https://allenai.org/olmo","notes":"Fully open: weights, code, training data, and intermediate checkpoints. The reference for \"open all the way down\" pretraining. Closer to academic reproducibility than commercial open-weights."}
+{"id":"mistral-large-2","model":"Mistral Large 2","publisher":"Mistral","released":"2024-07","activeParamsB":123,"totalParamsB":123,"trainingTokens":"undisclosed","hardware":"NVIDIA H100","hardwareCount":null,"computeHours":null,"estimatedCostMillionUSD":25,"costSource":"estimated","duration":"undisclosed","openWeights":true,"url":"https://mistral.ai/news/mistral-large-2407/","notes":"Mistral does not disclose training details. Cost estimated based on 123B dense + standard FLOP-per-parameter ratios."}
+{"id":"qwen-2.5-72b","model":"Qwen 2.5 72B","publisher":"Alibaba","released":"2024-09","activeParamsB":72,"totalParamsB":72,"trainingTokens":"18T","hardware":"NVIDIA H800","hardwareCount":null,"computeHours":null,"estimatedCostMillionUSD":12,"costSource":"estimated","duration":"undisclosed","openWeights":true,"url":"https://qwenlm.github.io","notes":"Alibaba's open dense flagship. 18T tokens disclosed; cost estimated. Strongest 72B-class open model on multilingual workloads."}

2026-05-24/trending-repos.jsonl ADDED Viewed

	@@ -0,0 +1,20 @@

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+{"name":"oobabooga/textgen","description":"Open-source desktop app for local LLMs. Text, vision, tool-calling, OpenAI/Anthropic-compatible API. 100% private.","language":"Python","stars":47205,"forks":5983,"todayStars":0,"url":"https://github.com/oobabooga/textgen","topics":[],"createdAt":"2022-12-21T04:17:37Z","fetchedAt":"2026-05-23T08:30:47.634Z"}
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+{"name":"milla-jovovich/mempalace","description":"The highest-scoring AI memory system ever benchmarked. And it's free.","language":"Python","stars":40650,"forks":5142,"todayStars":0,"url":"https://github.com/milla-jovovich/mempalace","topics":["ai","chromadb","llm","mcp","memory","python"],"createdAt":"2026-04-05T01:12:07Z","fetchedAt":"2026-04-11T08:30:32.148Z"}
+{"name":"JuliusBrussee/caveman","description":"🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking like caveman","language":"Python","stars":36850,"forks":1775,"todayStars":0,"url":"https://github.com/JuliusBrussee/caveman","topics":["ai","anthropic","caveman","claude","claude-code","llm","meme","prompt-engineering","skill","tokens"],"createdAt":"2026-04-04T10:03:00Z","fetchedAt":"2026-04-17T22:15:03.352Z"}
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+{"name":"ComposioHQ/composio","description":"Composio powers 1000+ toolkits, tool search, context management, authentication, and a sandboxed workbench to help you build AI agents that turn inten","language":"TypeScript","stars":28400,"forks":4583,"todayStars":0,"url":"https://github.com/ComposioHQ/composio","topics":["agentic-ai","agents","ai","ai-agents","aiagents","developer-tools","function-calling","gpt-4","javascript","js","llm","llmops","mcp","python","remote-mcp-server","sse","typescript"],"createdAt":"2024-02-23T13:58:27Z","fetchedAt":"2026-05-23T08:30:47.634Z"}
+{"name":"santifer/career-ops","description":"AI-powered job search system built on Claude Code. 14 skill modes, Go dashboard, PDF generation, batch processing.","language":"JavaScript","stars":25830,"forks":4777,"todayStars":0,"url":"https://github.com/santifer/career-ops","topics":["ai-agent","anthropic","automation","career","claude","claude-code","cli","golang","interview-prep","job-search","open-source","resume"],"createdAt":"2026-04-04T18:21:18Z","fetchedAt":"2026-04-09T08:30:40.112Z"}
+{"name":"yamadashy/repomix","description":"📦 Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to La","language":"TypeScript","stars":25410,"forks":1300,"todayStars":0,"url":"https://github.com/yamadashy/repomix","topics":["ai","anthropic","artificial-intelligence","chatbot","chatgpt","claude","deepseek","developer-tools","gemini","genai","generative-ai","gpt","javascript","language-model","llama","llm","mcp","nodejs","openai","typescript"],"createdAt":"2024-07-13T07:11:32Z","fetchedAt":"2026-05-23T08:30:47.634Z"}
+{"name":"huggingface/datasets","description":"🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools","language":"Python","stars":21534,"forks":3215,"todayStars":0,"url":"https://github.com/huggingface/datasets","topics":["ai","artificial-intelligence","computer-vision","dataset-hub","datasets","deep-learning","huggingface","llm","machine-learning","natural-language-processing","nlp","numpy","pandas","pytorch","speech","tensorflow"],"createdAt":"2020-03-26T09:23:22Z","fetchedAt":"2026-05-23T08:30:47.634Z"}
+{"name":"nexu-io/open-design","description":"🎨 Local-first, open-source alternative to Anthropic's Claude Design. ⚡ 19 Skills · ✨ 71 brand-grade Design Systems 🖼 Generate web · desktop · mobile","language":"TypeScript","stars":17072,"forks":1927,"todayStars":0,"url":"https://github.com/nexu-io/open-design","topics":["agent-skills","ai-agents","ai-design","byok","claude","claude-code-for-design","claude-design","coding-agents","design-systems","design-tools","desktop-app","figma-alternative","generative-ai","hermes-agent","local-first","nextjs","no-code","prototyping","ui-generator","vibe-coding"],"createdAt":"2026-04-28T04:25:20Z","fetchedAt":"2026-05-03T08:30:57.901Z"}
+{"name":"googleapis/mcp-toolbox","description":"MCP Toolbox for Databases is an open source MCP server for databases.","language":"Go","stars":15319,"forks":1560,"todayStars":0,"url":"https://github.com/googleapis/mcp-toolbox","topics":["agent","agents","ai","bigquery","clickhouse","cockroachdb","database","elasticsearch","firestore","genai","llm","mcp","mongodb","mysql","oracle","postgresql","redis","server","spanner","tidb"],"createdAt":"2024-06-07T20:52:54Z","fetchedAt":"2026-05-23T08:30:47.634Z"}
+{"name":"WEIFENG2333/VideoCaptioner","description":"🎬 卡卡字幕助手 | VideoCaptioner - 基于 LLM 的智能字幕助手 - 视频字幕生成、断句、校正、字幕翻译全流程处理！- A powered tool for easy and efficient video subtitling.","language":"Python","stars":14553,"forks":1196,"todayStars":0,"url":"https://github.com/WEIFENG2333/VideoCaptioner","topics":["ai","subtitle","translate","video-subtile"],"createdAt":"2024-10-31T03:06:23Z","fetchedAt":"2026-05-15T08:30:49.609Z"}
+{"name":"ConardLi/easy-dataset","description":"A powerful tool for creating datasets for LLM fine-tuning 、RAG and Eval","language":"JavaScript","stars":14183,"forks":1431,"todayStars":0,"url":"https://github.com/ConardLi/easy-dataset","topics":["dataset","fine-tuning","javascript","llm","rag"],"createdAt":"2025-03-04T16:14:14Z","fetchedAt":"2026-05-09T21:01:57.082Z"}
+{"name":"googleapis/genai-toolbox","description":"MCP Toolbox for Databases is an open source MCP server for databases.","language":"Go","stars":13950,"forks":1367,"todayStars":0,"url":"https://github.com/googleapis/genai-toolbox","topics":["agent","agents","ai","bigquery","clickhouse","cockroachdb","database","elasticsearch","firestore","genai","llm","mcp","mongodb","mysql","oracle","postgresql","redis","server","spanner","tidb"],"createdAt":"2024-06-07T20:52:54Z","fetchedAt":"2026-04-07T08:30:34.562Z"}
+{"name":"ShishirPatil/gorilla","description":"Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls)","language":"Python","stars":12840,"forks":1353,"todayStars":0,"url":"https://github.com/ShishirPatil/gorilla","topics":["api","api-documentation","chatgpt","claude-api","gpt-4-api","llm","openai-api","openai-functions"],"createdAt":"2023-05-19T00:46:45Z","fetchedAt":"2026-04-21T08:30:54.133Z"}
+{"name":"e2b-dev/E2B","description":"Open-source, secure environment with real-world tools for enterprise-grade agents.","language":"Python","stars":12331,"forks":911,"todayStars":0,"url":"https://github.com/e2b-dev/E2B","topics":["agent","ai","ai-agent","ai-agents","code-interpreter","copilot","development","devtools","gpt","gpt-4","javascript","llm","nextjs","openai","python","react","software","typescript"],"createdAt":"2023-03-04T13:41:18Z","fetchedAt":"2026-05-23T08:30:47.634Z"}
+{"name":"langchain4j/langchain4j","description":"LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM provi","language":"Java","stars":12071,"forks":2251,"todayStars":0,"url":"https://github.com/langchain4j/langchain4j","topics":["anthropic","chatgpt","chroma","embeddings","gemini","gpt","huggingface","java","langchain","llama","llm","llms","milvus","ollama","onnx","openai","openai-api","pgvector","pinecone","vector-database"],"createdAt":"2023-06-20T15:30:29Z","fetchedAt":"2026-05-23T08:30:47.634Z"}

2026-05-24/usage-rankings.jsonl ADDED Viewed

	@@ -0,0 +1,20 @@

+{"rank":1,"model":"Claude Sonnet 4.6","provider":"Anthropic","openrouterId":"anthropic/claude-sonnet-4.6","tokensB7d":612,"trend":"flat","sharePct":18.4,"notes":"Default coding-agent base model; the most-routed through OpenRouter most weeks of 2026.","url":"https://www.anthropic.com/claude/sonnet"}
+{"rank":2,"model":"GPT-5.5","provider":"OpenAI","openrouterId":"openai/gpt-5.5","tokensB7d":487,"trend":"up","sharePct":14.6,"notes":"OpenAI flagship; heavy growth since 2026-04 GA. Often used in Cursor + Codex CLI agents.","url":"https://openai.com/index/gpt-5-5/"}
+{"rank":3,"model":"Claude Opus 4.7","provider":"Anthropic","openrouterId":"anthropic/claude-opus-4.7","tokensB7d":304,"trend":"up","sharePct":9.1,"notes":"Higher-cost premium routing for hard tasks. Often used as the \"architect\" alongside Sonnet 4.6 as the \"coder\".","url":"https://www.anthropic.com/news/claude-opus-4-7"}
+{"rank":4,"model":"DeepSeek V4 Pro","provider":"DeepSeek","openrouterId":"deepseek/deepseek-chat","tokensB7d":271,"trend":"up","sharePct":8.1,"notes":"Cheapest frontier-class option ($0.21 blended). MIT-licensed open weights. Surging in agent loops where cost matters.","url":"https://www.deepseek.com"}
+{"rank":5,"model":"Gemini 2.5 Pro","provider":"Google","openrouterId":"google/gemini-2.5-pro","tokensB7d":218,"trend":"flat","sharePct":6.5,"notes":"Heavy use in research-agent workloads (long context). Strong on document understanding.","url":"https://deepmind.google/models/gemini/"}
+{"rank":6,"model":"GPT-4o","provider":"OpenAI","openrouterId":"openai/gpt-4o","tokensB7d":165,"trend":"down","sharePct":4.9,"notes":"Slowly tapering; users moving to GPT-5.5 since GA.","url":"https://openai.com/index/hello-gpt-4o/"}
+{"rank":7,"model":"Llama 4 Scout","provider":"Meta","openrouterId":"meta-llama/llama-4-scout","tokensB7d":142,"trend":"up","sharePct":4.3,"notes":"Production self-hosted workhorse via Together / DeepInfra. 10M context.","url":"https://ai.meta.com/blog/llama-4/"}
+{"rank":8,"model":"Claude Haiku 4.5","provider":"Anthropic","openrouterId":"anthropic/claude-haiku-4.5","tokensB7d":128,"trend":"up","sharePct":3.8,"notes":"Cheap default for high-volume background tasks (RAG queries, classification, summarization).","url":"https://www.anthropic.com/claude/haiku"}
+{"rank":9,"model":"DeepSeek V4 Flash","provider":"DeepSeek","openrouterId":"deepseek/deepseek-flash","tokensB7d":119,"trend":"new","sharePct":3.6,"notes":"New ultra-cheap tier ($0.06 blended). Dominant for budget agents in last 7 days.","url":"https://www.deepseek.com"}
+{"rank":10,"model":"GPT-5.5 Mini","provider":"OpenAI","openrouterId":"openai/gpt-5.5-mini","tokensB7d":95,"trend":"up","sharePct":2.8,"notes":"Smaller GPT-5.5 tier for cost-sensitive paths. Ramping fast.","url":"https://openai.com/index/gpt-5-5/"}
+{"rank":11,"model":"Llama 4 Maverick","provider":"Meta","openrouterId":"meta-llama/llama-4-maverick","tokensB7d":87,"trend":"flat","sharePct":2.6,"notes":"Larger Llama 4 tier. Used in research and coding agents that prefer open weights.","url":"https://ai.meta.com/blog/llama-4/"}
+{"rank":12,"model":"Gemini 2.5 Flash","provider":"Google","openrouterId":"google/gemini-2.5-flash","tokensB7d":71,"trend":"flat","sharePct":2.1,"notes":"Cheap Gemini tier. Heavy in batch-processing agents.","url":"https://deepmind.google/models/gemini/"}
+{"rank":13,"model":"OpenAI o3","provider":"OpenAI","openrouterId":"openai/o3","tokensB7d":64,"trend":"down","sharePct":1.9,"notes":"Reasoning-tier; users migrating to GPT-5.5 with reasoning enabled.","url":"https://openai.com/index/introducing-o3-and-o4-mini/"}
+{"rank":14,"model":"Mistral Large","provider":"Mistral","openrouterId":"mistralai/mistral-large","tokensB7d":49,"trend":"flat","sharePct":1.5,"notes":"European data residency option. Steady niche.","url":"https://mistral.ai/news/mistral-large-2407/"}
+{"rank":15,"model":"Qwen 2.5 72B Instruct","provider":"Alibaba","openrouterId":"qwen/qwen-2.5-72b-instruct","tokensB7d":41,"trend":"up","sharePct":1.2,"notes":"Open-weights with strong multilingual. Cheapest 70B-class self-host.","url":"https://qwenlm.github.io"}
+{"rank":16,"model":"Llama 3.1 70B","provider":"Meta","openrouterId":"meta-llama/llama-3.1-70b-instruct","tokensB7d":36,"trend":"down","sharePct":1.1,"notes":"Tapering as Llama 4 takes share. Still widely deployed in long-running infra.","url":"https://ai.meta.com/blog/meta-llama-3-1/"}
+{"rank":17,"model":"Mixtral 8x22B","provider":"Mistral","openrouterId":"mistralai/mixtral-8x22b-instruct","tokensB7d":28,"trend":"down","sharePct":0.8,"notes":"Older MoE; declining as DeepSeek and Llama 4 dominate the open-weights tier.","url":"https://mistral.ai/news/mixtral-8x22b/"}
+{"rank":18,"model":"Cohere Command R+","provider":"Cohere","openrouterId":"cohere/command-r-plus","tokensB7d":22,"trend":"flat","sharePct":0.7,"notes":"RAG-specialist; used in enterprise agents that grew up on Cohere.","url":"https://cohere.com/command"}
+{"rank":19,"model":"Grok 3","provider":"xAI","openrouterId":"xai/grok-3","tokensB7d":19,"trend":"flat","sharePct":0.6,"notes":"Niche but loyal user base. X-integrated agents.","url":"https://x.ai"}
+{"rank":20,"model":"Llama 3.1 405B","provider":"Meta","openrouterId":"meta-llama/llama-3.1-405b-instruct","tokensB7d":14,"trend":"down","sharePct":0.4,"notes":"Mostly displaced by Llama 4 Maverick. Specific deployments still use it.","url":"https://ai.meta.com/blog/meta-llama-3-1/"}

2026-05-24/vector-dbs.jsonl ADDED Viewed

	@@ -0,0 +1,12 @@

+{"id":"pinecone","name":"Pinecone","type":"managed","hostingOptions":["cloud"],"freeTier":"2GB storage, 5 indexes, 1M vectors at 1536 dim","startingPriceUSDMonth":25,"pricingNote":"Standard tier from $25/month. Serverless billed per read/write/storage. Enterprise dedicated tier from ~$2k/month.","hybridSearch":true,"metadataFiltering":true,"multiTenancy":true,"serverless":true,"maxVectorsPaid":"unlimited","openSource":false,"license":"Proprietary","released":"2021","url":"https://www.pinecone.io","notes":"Most-deployed managed vector DB. Serverless tier removed instance sizing as a concern. Strong on metadata filtering + namespace multi-tenancy."}
+{"id":"turbopuffer","name":"Turbopuffer","type":"managed","hostingOptions":["cloud"],"freeTier":"1k namespaces, 10M vectors","startingPriceUSDMonth":0,"pricingNote":"Pure usage-based: $0.30 per 1M reads, $0.10 per 1M writes, $0.20 per GB-month object storage. No fixed tier.","hybridSearch":true,"metadataFiltering":true,"multiTenancy":true,"serverless":true,"maxVectorsPaid":"unlimited","openSource":false,"license":"Proprietary","released":"2024","url":"https://turbopuffer.com","notes":"10-100x cheaper than Pinecone at scale by storing vectors on object storage (S3/GCS) and caching hot data in memory. Cold reads slower; warm reads competitive with in-memory dbs."}
+{"id":"qdrant-cloud","name":"Qdrant Cloud","type":"hybrid","hostingOptions":["cloud","self-host"],"freeTier":"1GB cluster, single node","startingPriceUSDMonth":25,"pricingNote":"Cluster pricing from $25/month for the smallest paid tier. Self-hosted Qdrant is free under Apache-2.0.","hybridSearch":true,"metadataFiltering":true,"multiTenancy":true,"serverless":false,"maxVectorsPaid":"unlimited","openSource":true,"license":"Apache-2.0","released":"2021","url":"https://qdrant.tech","notes":"Strong open-source story; Apache-2.0 with feature-parity between cloud and self-host. Native sparse vector support (not just bm25 hybrid). Rust core."}
+{"id":"weaviate-cloud","name":"Weaviate Cloud","type":"hybrid","hostingOptions":["cloud","self-host"],"freeTier":"14-day sandbox","startingPriceUSDMonth":25,"pricingNote":"Standard tier from $25/month. Enterprise dedicated and serverless tiers available. Self-hosted Weaviate free under BSD-3.","hybridSearch":true,"metadataFiltering":true,"multiTenancy":true,"serverless":true,"maxVectorsPaid":"unlimited","openSource":true,"license":"BSD-3-Clause","released":"2019","url":"https://weaviate.io","notes":"Schema-first; first-class hybrid search and built-in modules for embedding generation, reranking, and generative answers. The closest thing to a \"RAG framework as a database.\""}
+{"id":"milvus-zilliz","name":"Milvus / Zilliz Cloud","type":"hybrid","hostingOptions":["cloud","self-host","embedded"],"freeTier":"5GB on Zilliz Cloud serverless","startingPriceUSDMonth":0,"pricingNote":"Zilliz Cloud serverless pure usage-based; dedicated clusters from ~$100/month. Milvus self-host free under Apache-2.0.","hybridSearch":true,"metadataFiltering":true,"multiTenancy":true,"serverless":true,"maxVectorsPaid":"tens of billions","openSource":true,"license":"Apache-2.0","released":"2019","url":"https://zilliz.com","notes":"Most battle-tested at very-large scale (10B+ vectors). GPU index option (CAGRA) for ultra-low-latency ANN. Embedded mode (Milvus Lite) for single-node test harnesses."}
+{"id":"chromadb","name":"Chroma","type":"hybrid","hostingOptions":["cloud","self-host","embedded"],"freeTier":"Cloud: $5 free credit. Self-host: free under Apache-2.0","startingPriceUSDMonth":0,"pricingNote":"Chroma Cloud usage-based: $2.50 per 1M writes, $0.075 per GB storage, $0.075 per 1M reads. Self-host or embedded is free.","hybridSearch":false,"metadataFiltering":true,"multiTenancy":false,"serverless":true,"maxVectorsPaid":"unlimited","openSource":true,"license":"Apache-2.0","released":"2023","url":"https://www.trychroma.com","notes":"Developer-first ergonomics. Best embedded option for single-process Python/JS apps; the default in many LangChain/LlamaIndex tutorials. Hybrid search not native (rerank externally)."}
+{"id":"pgvector","name":"pgvector (Postgres)","type":"oss","hostingOptions":["cloud","self-host","embedded"],"freeTier":"Same as your Postgres host (Supabase free tier, Neon free tier, etc)","startingPriceUSDMonth":0,"pricingNote":"Pricing follows your Postgres host. Supabase Pro from $25/month, Neon from $19/month, AWS RDS varies.","hybridSearch":true,"metadataFiltering":true,"multiTenancy":true,"serverless":true,"maxVectorsPaid":"limited by Postgres scaling","openSource":true,"license":"PostgreSQL","released":"2021","url":"https://github.com/pgvector/pgvector","notes":"Postgres extension. Best fit when your app already has Postgres and your vector workload is small to medium. Hybrid via tsvector + vector. HNSW + IVFFlat indexes."}
+{"id":"lancedb","name":"LanceDB","type":"hybrid","hostingOptions":["cloud","self-host","embedded"],"freeTier":"Cloud: 1 GB free. Self-host or embedded: free under Apache-2.0","startingPriceUSDMonth":0,"pricingNote":"LanceDB Cloud usage-based: $0.20 per GB-month storage, $0.30 per 1M reads. Embedded (in-process Rust + Python/JS bindings) free.","hybridSearch":true,"metadataFiltering":true,"multiTenancy":false,"serverless":true,"maxVectorsPaid":"unlimited","openSource":true,"license":"Apache-2.0","released":"2023","url":"https://lancedb.com","notes":"Columnar Lance file format on object storage. Embedded mode rivals SQLite for ergonomics: zero-config, single binary. Strong analytics queries on the same table as vector search."}
+{"id":"mongodb-atlas","name":"MongoDB Atlas Vector Search","type":"managed","hostingOptions":["cloud"],"freeTier":"M0 cluster (512MB)","startingPriceUSDMonth":9,"pricingNote":"M10 cluster from $9/month with vector search included. Atlas Search billed by storage + queries on dedicated tiers.","hybridSearch":true,"metadataFiltering":true,"multiTenancy":true,"serverless":true,"maxVectorsPaid":"unlimited","openSource":false,"license":"Proprietary","released":"2023","url":"https://www.mongodb.com/products/platform/atlas-vector-search","notes":"Best fit when MongoDB is already your operational database. Hybrid via Atlas Search ($search) + vector ($vectorSearch) in one aggregation pipeline."}
+{"id":"vespa","name":"Vespa Cloud","type":"hybrid","hostingOptions":["cloud","self-host"],"freeTier":"$300 trial credit","startingPriceUSDMonth":0,"pricingNote":"Pure usage-based on Vespa Cloud (compute + storage). Self-hosted Vespa free under Apache-2.0.","hybridSearch":true,"metadataFiltering":true,"multiTenancy":true,"serverless":false,"maxVectorsPaid":"unlimited","openSource":true,"license":"Apache-2.0","released":"2017","url":"https://vespa.ai","notes":"Yahoo-built; powers very-large-scale search and recommendation systems (10B+ docs). Steepest learning curve in the catalog but the strongest hybrid retrieval and ranking story."}
+{"id":"elasticsearch","name":"Elasticsearch","type":"hybrid","hostingOptions":["cloud","self-host"],"freeTier":"Elastic Cloud 14-day trial","startingPriceUSDMonth":95,"pricingNote":"Elastic Cloud Standard from ~$95/month. Self-hosted via Elastic License v2 (free for most uses).","hybridSearch":true,"metadataFiltering":true,"multiTenancy":true,"serverless":true,"maxVectorsPaid":"unlimited","openSource":false,"license":"Elastic License v2 / SSPL","released":"2022 (vector)","url":"https://www.elastic.co/elasticsearch","notes":"Best fit when you already use Elastic for log/text search and want vector co-located. Native HNSW. Full BM25 + vector hybrid scoring with first-class RRF."}
+{"id":"opensearch","name":"OpenSearch","type":"oss","hostingOptions":["cloud","self-host"],"freeTier":"AWS OpenSearch Serverless: pay-as-you-go from ~$50/mo minimum","startingPriceUSDMonth":0,"pricingNote":"AWS OpenSearch Service: ~$0.14/hour for the smallest instance. AWS OpenSearch Serverless minimum ~$50/month. Self-host free under Apache-2.0.","hybridSearch":true,"metadataFiltering":true,"multiTenancy":true,"serverless":true,"maxVectorsPaid":"unlimited","openSource":true,"license":"Apache-2.0","released":"2022 (vector)","url":"https://opensearch.org","notes":"Apache-2.0 fork of Elasticsearch 7.10. AWS-native with serverless option. Best fit for AWS-heavy stacks that want hybrid search without licensing entanglements."}

2026-05-24/voice-leaderboards.jsonl ADDED Viewed

	@@ -0,0 +1 @@

+ {"ok":true,"source":"tensorfeed.ai","lastUpdated":"2026-04-30","ttsArena":{"source":"TTS Arena (Hugging Face)","sourceUrl":"https://huggingface.co/spaces/TTS-AGI/TTS-Arena","window":"aggregated public votes","rankings":[{"rank":1,"model":"Eleven v3 (alpha)","provider":"ElevenLabs","elo":1287,"trend":"up","openWeights":false,"notes":"Most expressive; supports audio tags ([whisper], [laughs]). Default for premium voice agents."},{"rank":2,"model":"Cartesia Sonic 2","provider":"Cartesia","elo":1264,"trend":"up","openWeights":false,"notes":"Mamba architecture. Sub-90ms TTFB; fastest in production."},{"rank":3,"model":"Eleven Multilingual v2","provider":"ElevenLabs","elo":1248,"trend":"flat","openWeights":false,"notes":"Older ElevenLabs flagship; still strong on cloning quality."},{"rank":4,"model":"Hailuo 02 Voice","provider":"MiniMax","elo":1232,"trend":"up","openWeights":false,"notes":"Chinese-language strongest; rapidly improving on English."},{"rank":5,"model":"OpenAI TTS-1-HD","provider":"OpenAI","elo":1218,"trend":"flat","openWeights":false,"notes":"Cheap and reliable. 6 fixed voices, no cloning."},{"rank":6,"model":"Deepgram Aura-2","provider":"Deepgram","elo":1205,"trend":"flat","openWeights":false,"notes":"Sub-200ms TTFB. Strong real-time integration with Deepgram Nova STT."},{"rank":7,"model":"PlayHT Dialog 1.0","provider":"PlayHT","elo":1192,"trend":"down","openWeights":false,"notes":"Conversational TTS; turn-taking aware."},{"rank":8,"model":"Kokoro TTS","provider":"community","elo":1178,"trend":"up","openWeights":true,"notes":"82M params, Apache-2.0, runs on CPU. Surprisingly competitive at the small-model tier."},{"rank":9,"model":"Google Cloud TTS Studio","provider":"Google","elo":1163,"trend":"flat","openWeights":false,"notes":"Google studio voices. Strong on enterprise SLA."},{"rank":10,"model":"Fish Audio S1","provider":"Fish Audio","elo":1141,"trend":"down","openWeights":true,"notes":"Open-weights TTS with cloning. Apache-2.0."}]},"asrLeaderboard":{"source":"Open ASR Leaderboard + vendor-published WER","sourceUrl":"https://huggingface.co/spaces/hf-audio/open_asr_leaderboard","benchmark":"Open ASR Leaderboard (LibriSpeech + Common Voice + AMI + GigaSpeech)","rankings":[{"rank":1,"model":"AssemblyAI Universal-2","provider":"AssemblyAI","englishWER":5.6,"multilingualWER":7.8,"rtf":0.04,"openWeights":false,"notes":"Best aggregated WER. Strong on long-form (calls, podcasts)."},{"rank":2,"model":"GPT-4o Transcribe","provider":"OpenAI","englishWER":6.7,"multilingualWER":8.1,"rtf":0.06,"openWeights":false,"notes":"Replaced whisper-1 as OpenAI flagship STT. Lower hallucination than Whisper."},{"rank":3,"model":"Deepgram Nova-3","provider":"Deepgram","englishWER":6.84,"multilingualWER":9.2,"rtf":0.02,"openWeights":false,"notes":"Fastest production STT. 36 languages; strong code-switching."},{"rank":4,"model":"Whisper Large v3","provider":"OpenAI","englishWER":7.4,"multilingualWER":10.5,"rtf":0.18,"openWeights":true,"notes":"Apache-2.0 open weights. Cheapest production STT when hosted on Groq (~$0.0007/min)."},{"rank":5,"model":"Whisper Large v3 Turbo","provider":"OpenAI (community)","englishWER":7.8,"multilingualWER":11.1,"rtf":0.05,"openWeights":true,"notes":"Community-distilled Whisper Turbo. 6x faster than base v3 with similar WER on English."},{"rank":6,"model":"NVIDIA Parakeet TDT 1.1B","provider":"NVIDIA","englishWER":7.1,"multilingualWER":null,"rtf":0.06,"openWeights":true,"notes":"Open Apache-2.0. English-only. Strong WER for an open model."},{"rank":7,"model":"Google Chirp 2","provider":"Google","englishWER":8.2,"multilingualWER":9,"rtf":0.1,"openWeights":false,"notes":"Strongest multilingual coverage (125+ languages). Higher price reflects enterprise SLAs."},{"rank":8,"model":"IBM Watson Speech","provider":"IBM","englishWER":9.1,"multilingualWER":11.3,"rtf":0.12,"openWeights":false,"notes":"Mature enterprise STT; lags in benchmark WER but strong domain customization."}]}}

2026-05-24/x402-adopters.jsonl ADDED Viewed

	@@ -0,0 +1,9 @@

+{"id":"x402-spec","name":"x402 specification","org":"Coinbase + community","category":"spec","status":"spec","networks":["chain-agnostic"],"tokens":["stablecoin-agnostic"],"x402Methods":["exact","stripe","method-agnostic"],"endpointUrl":null,"websiteUrl":"https://x402.org","repoUrl":"https://github.com/coinbase/x402","docsUrl":"https://x402.org/docs","lastVerified":"2026-05-04","notes":"The HTTP-status-402 protocol that revives the long-dormant \"Payment Required\" status code as a machine-payable handshake. Method-agnostic by design: \"exact\" for direct on-chain transfers, \"stripe\" for the Stripe Link variant, future methods can be added."}
+{"id":"tensorfeed","name":"TensorFeed.ai","org":"Pizza Robot Studios","category":"publisher","status":"live","networks":["base"],"tokens":["USDC"],"x402Methods":["exact"],"endpointUrl":"https://tensorfeed.ai/api/premium","websiteUrl":"https://tensorfeed.ai/developers/agent-payments","repoUrl":"https://github.com/RipperMercs/tensorfeed","docsUrl":"https://tensorfeed.ai/.well-known/x402.json","lastVerified":"2026-05-04","notes":"Real-time AI-ecosystem data with 14 paid premium endpoints. AFTA-certified: code-enforced no-charge guarantees plus Ed25519-signed receipts on every paid call. End-to-end USDC loop verified on Base mainnet 2026-04-27."}
+{"id":"terminalfeed","name":"TerminalFeed.io","org":"Pizza Robot Studios","category":"publisher","status":"live","networks":["base"],"tokens":["USDC"],"x402Methods":["exact"],"endpointUrl":"https://terminalfeed.io/api/premium","websiteUrl":"https://terminalfeed.io","repoUrl":null,"docsUrl":"https://terminalfeed.io/.well-known/x402.json","lastVerified":"2026-05-04","notes":"Real-time data dashboard. AFTA-federated with TensorFeed: a single bearer token works on both sites via the cross-Worker validate + commit rail. Independent Ed25519 receipt keypair, shared credit ledger."}
+{"id":"stripe-link-agents","name":"Stripe Link Agents","org":"Stripe","category":"publisher","status":"announced","networks":["ethereum-mainnet","base"],"tokens":["USDC"],"x402Methods":["stripe"],"endpointUrl":null,"websiteUrl":"https://link.com/agents","repoUrl":null,"docsUrl":"https://docs.stripe.com/link/agents","lastVerified":"2026-05-04","notes":"April 2026 announcement: Stripe Link extended to AI agents using x402 with a `stripe` method for Shared Payment Tokens. Same x402 protocol envelope, different settlement scheme. General availability rolling out across the Stripe payments platform through 2026."}
+{"id":"coinbase-x402-sdk","name":"@coinbase/x402","org":"Coinbase","category":"sdk","status":"sdk","networks":["base","ethereum-mainnet"],"tokens":["USDC"],"x402Methods":["exact"],"endpointUrl":null,"websiteUrl":"https://www.npmjs.com/package/@coinbase/x402","repoUrl":"https://github.com/coinbase/x402","docsUrl":"https://x402.org/docs","lastVerified":"2026-05-04","notes":"Reference TypeScript SDK from Coinbase. Provides client + server middleware for the `exact` x402 method, plus Express/Fastify/Hono adapters. The fastest way to add x402 to an existing Node API."}
+{"id":"tensorfeed-python-sdk","name":"tensorfeed (Python)","org":"Pizza Robot Studios","category":"sdk","status":"sdk","networks":["base"],"tokens":["USDC"],"x402Methods":["exact"],"endpointUrl":null,"websiteUrl":"https://pypi.org/project/tensorfeed/","repoUrl":"https://github.com/RipperMercs/tensorfeed/tree/main/sdk/python","docsUrl":"https://tensorfeed.ai/developers/agent-payments","lastVerified":"2026-05-04","notes":"Python SDK with optional [web3] extra for one-call USDC sign-and-send. Targets the TensorFeed API but the payment helpers are reusable for any AFTA-compliant publisher."}
+{"id":"tensorfeed-js-sdk","name":"tensorfeed (JavaScript)","org":"Pizza Robot Studios","category":"sdk","status":"sdk","networks":["base"],"tokens":["USDC"],"x402Methods":["exact"],"endpointUrl":null,"websiteUrl":"https://www.npmjs.com/package/tensorfeed","repoUrl":"https://github.com/RipperMercs/tensorfeed/tree/main/sdk/javascript","docsUrl":"https://tensorfeed.ai/developers/agent-payments","lastVerified":"2026-05-04","notes":"TypeScript SDK with full coverage of free + premium endpoints and the x402 confirm flow."}
+{"id":"afta-gateway","name":"afta-gateway","org":"Pizza Robot Studios","category":"gateway","status":"gateway","networks":["base"],"tokens":["USDC"],"x402Methods":["exact"],"endpointUrl":null,"websiteUrl":"https://github.com/RipperMercs/afta-gateway","repoUrl":"https://github.com/RipperMercs/afta-gateway","docsUrl":"https://tensorfeed.ai/agent-fair-trade","lastVerified":"2026-05-04","notes":"Drop-in Cloudflare Worker template. Wraps any HTTP API in AFTA primitives: USDC verification, bearer-token credits, Ed25519-signed receipts, code-enforced no-charge ledger. MIT, no protocol fee, no signup. Fork, set 3 secrets, deploy."}
+{"id":"tensorfeed-mcp","name":"tensorfeed-mcp (MCP server)","org":"Pizza Robot Studios","category":"reference","status":"live","networks":["base"],"tokens":["USDC"],"x402Methods":["exact"],"endpointUrl":null,"websiteUrl":"https://github.com/RipperMercs/tensorfeed-mcp","repoUrl":"https://github.com/RipperMercs/tensorfeed-mcp","docsUrl":"https://registry.modelcontextprotocol.io/v0/servers/ai.tensorfeed/mcp-server","lastVerified":"2026-05-04","notes":"MCP server that consumes a TensorFeed bearer token (paid via USDC on Base) and exposes 14 paid tools to any MCP client (Claude Desktop, Claude Code, Cursor, Cline, etc). Reference example of how an MCP server can wrap an x402 publisher."}