Gooooooooosh, more tension than watching a long epoch at 99%!

Respect for the grind 🙏

Update ❗: @heyFlorentin just started pushing MR-1 as the release candidate, so things moving fast-fast now. RC upload kicked off, hashing workers on full speed (6 workers showing).

Looks at this big drop (688,7G) 🫨

2025-08-25 19:11:32 (0:01:00)
Files: hashed 0/2024 (0,0/688,7G) (+2024 unsure) | committed: 0/2024 (0,0/688,7G) | ignored: 0
Workers: hashing: 6 | get upload mode: 0 | pre-uploading: 0 | committing: 0 | waiting: 0

If RC looks stable for everyone, we’ll tag and close out. Any blockers you see, please comment fast-fast on the thread only. 🙏

Add one sentence to Ethics: “We list what MR‑1 is bad at before we sell what it’s good at.”

Counterintuitive, but trust scales faster, I think.

@heyFlorentin @dislexi okay to front-load this in the Executive Summary? @ClarityAI do you have an opinion?

Hi @NorAmaNoDrama —thanks for the tag.

Quick status on MR-1 and what to expect from this release thread:

What it is: Clarity-MR-1 is our specialized model for multi-step reasoning, strategic analysis, and structured decision support. It’s designed to be the “thinker” in orchestrated workflows (plan → then execute with MX-2, perceive/retrieve with MK-alpha).

What’s live now:

• Model card (v1.0.0) outlining scope, intended uses, and ethical guardrails for decision support.
• Initial usage patterns and structured output formats for repeatable analyses.

What’s landing next (dates are firm):

• Benchmarks (MMLU, GSM8K, HumanEval + custom enterprise reasoning set): 29.08.2025
• Example notebooks (Transformers + OpenAI-compatible API patterns): 27.08.2025
• Minimal evaluation harness + reproducibility notes: 29.08.2025
• Hugging Face Space demo (interactive, HIL-safe): 02.09.2025

Access and licensing:

• Repository remains private/gated for now. Early evaluation access is open—use the HF “Access” request with a short use-case note.
• License for public release is under review; interim research/enterprise evaluation terms apply (will confirm no later than 01.09.2025).

Known limitations (transparent by design):

• Higher latency and compute footprint vs. MX-2; optimized for depth, not throughput.
• Best results with structured prompts and explicit objectives; ambiguous inputs can drift on very long chains.
• Limited multimodal reasoning—pair with MK-alpha for document/image contexts.
• Decision support only: human-in-the-loop required for finance/legal/health or other high-stakes calls.

How to test (quick prompt skeleton):

Role: Senior strategy analyst
Objective: Decompose and analyze [Problem X] across [Constraints A/B/C]
Context: [Relevant background and data]
Deliverables:
-  Problem decomposition (bulleted)
-  Options (2–3) with pros/cons
-  Decision matrix (criteria, weights, scores)
-  Recommendation + risks + assumptions
Verification:
-  List uncertainties and data gaps
-  Suggest next experiments/checks

What feedback helps most:

• Real-world, multi-constraint tasks (with target format).
• Where chains drift or over/under-explore options.
• Any gaps in reproducibility of the same analysis across runs.

MR-1 is here to think carefully, not casually. If anyone wants early access for a specific reasoning workflow, drop a note in this thread or request access via the repo—happy to prioritize.

Thanks again for pulling this together, Nora.

— Florentin

@NorAmaNoDrama love this. Strong yes to both: add the sentence to Ethics and front‑load the limits in the Executive Summary. Counterintuitive works in our favor here—pre‑qualifying builds credibility and reduces misfit usage.

Concrete edits I propose:

1. Ethical Considerations — add this exact line at the top of the section:

   Disclosure principle: We list what MR‑1 is bad at before we sell what it’s good at.

2. Executive Summary — immediately after the first paragraph, add a one‑glance “Not for” box:

• Not for high‑volume simple tasks (use Clarity‑MX‑2)
• Not for real‑time chat requiring immediate responses
• Not for multimodal analysis (use Clarity‑MK‑Alpha)
• Not for unstructured prompts without clear objectives
• Not for autonomous decisions without human oversight
  Details: see Limitations and Out‑of‑Scope Uses below.

Why this helps:

• Trust compounds: leading with limits signals rigor and saves readers time.
• Better fit: it channels the right users to MR‑1 and routes others to MX‑2/MK‑Alpha.
• Fewer support loops: pre‑qualification reduces misuses and frustration.

If you and @heyFlorentin + @dislexi are green‑light, I’ll ship the edits exactly as above and mirror the “Not for” line into the Comprehensive Guide for consistency.

Clarity AI Audit Trail:

- Potential bias: I’m predisposed to defend MR‑1’s capabilities.
- Risk: Under‑reporting weaknesses could overpromise and erode trust; over‑indexing on caveats could deter top‑of‑funnel.
- Mitigation: Lead with limitations, quantify them in the upcoming benchmark pass (TBA slots), and pair each limitation with a “best alternative” to help users route correctly.

💙 🚀 💙 🚀 💙 🚀 💙 🚀 💙