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  # Cubic β€” AI and Cybersecurity Research
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  Building accessible AI systems that run on consumer hardware. Our projects focus on CPU-first training, open-source research, and practical deployment.
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-
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  ## Key Metrics
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  - **27 models** β€” 1 research paper β€” 3 team members
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  - **$0.004** min training cost β€” **100%** open source
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-
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  ## Research Focus
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  - **AI Development** β€” CPU-first architectures and open-source models
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  - **Cybersecurity** β€” AI-powered security tools and threat detection
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-
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  ## Projects
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  ### AXL β€” CPU-First Code Generation
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  - **27 models** from 566K to 318M parameters
@@ -26,34 +22,21 @@ Building accessible AI systems that run on consumer hardware. Our projects focus
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  - **Architecture**: Multi-scale byte-level transformer
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  - **License**: Apache 2.0
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  - Click the project card on the org page to see the full AXL detail page
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-
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  ## Team
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  - **Kennedy**: CEO & Head of AI Research
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  - **Jasser**: CTO & Head of Cybersecurity
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  - **Taem**: Head of Marketing/Sales/Technical Assist
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-
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  ## Interactive Tools
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- The org card includes functional calculators, grounded in AXL's real published numbers:
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- - **Training Cost Calculator** β€” total cost for N models at the measured $0.004/model rate
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  - **Inference Speed Calculator** β€” estimated CPU tokens/sec by parameter count and thread count
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- - **GGUF File Size Calculator** β€” file size from parameter count and quantization level (Q4/Q5/Q8/F16/F32)
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- - **Context Length Calculator** β€” KV-cache memory for a given context window, layer count, and hidden dimension
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- - **Memory Usage Estimator** β€” total estimated RAM from weights plus KV-cache overhead
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- - **Training Time Estimator** β€” estimated training time from cost and effective hourly CPU rate
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- - **Model Comparison Tool** β€” side-by-side comparison of two AXL model sizes on params, file size, and inference speed
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-
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  ## Key Features
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  - Dark/Light theme toggle
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- - Category filtering on projects
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- - Search across projects
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- - Animated counters on metrics
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- - Keyboard shortcuts (/ to search, Esc to close)
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  - Print-friendly CSS
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  - Responsive design
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-
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  ## Links
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  - [GitHub](https://github.com/Cubic-Labs)
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  - [HuggingFace](https://huggingface.co/Cubic)
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-
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  ---
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  *CPU-first, AI for everyone.*
 
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  app_file: index.html
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  pinned: false
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  ---
 
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  # Cubic β€” AI and Cybersecurity Research
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  Building accessible AI systems that run on consumer hardware. Our projects focus on CPU-first training, open-source research, and practical deployment.
 
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  ## Key Metrics
13
  - **27 models** β€” 1 research paper β€” 3 team members
14
  - **$0.004** min training cost β€” **100%** open source
 
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  ## Research Focus
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  - **AI Development** β€” CPU-first architectures and open-source models
17
  - **Cybersecurity** β€” AI-powered security tools and threat detection
 
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  ## Projects
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  ### AXL β€” CPU-First Code Generation
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  - **27 models** from 566K to 318M parameters
 
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  - **Architecture**: Multi-scale byte-level transformer
23
  - **License**: Apache 2.0
24
  - Click the project card on the org page to see the full AXL detail page
 
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  ## Team
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  - **Kennedy**: CEO & Head of AI Research
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  - **Jasser**: CTO & Head of Cybersecurity
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  - **Taem**: Head of Marketing/Sales/Technical Assist
 
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  ## Interactive Tools
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+ The org card includes two live calculators, grounded in AXL's real published numbers:
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+ - **Memory Usage Estimator** β€” total estimated RAM from weights (at your chosen quantization) plus KV-cache overhead
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  - **Inference Speed Calculator** β€” estimated CPU tokens/sec by parameter count and thread count
 
 
 
 
 
 
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  ## Key Features
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  - Dark/Light theme toggle
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+ - Two live calculators (memory & inference speed)
 
 
 
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  - Print-friendly CSS
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  - Responsive design
 
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  ## Links
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  - [GitHub](https://github.com/Cubic-Labs)
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  - [HuggingFace](https://huggingface.co/Cubic)
 
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  ---
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  *CPU-first, AI for everyone.*