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Achievement: YOLO

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Achievement: YOLO

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airawatraj/README.md

technologist | experimenter | seeker

"the future belongs to those who understand at a very deep level how to combine their unique expertise with what algorithms do best" — Pedro Domingos, The Master Algorithm


Portfolio

Independent Research & Systems.

  • Cogni-Brain-2: Deployed and optimised Qwen 3.6-35B on NVIDIA DGX Spark via the Atlas engine; achieved 218.85 tok/s, a perfect 100/100 tool-use score, and documented the benchmark methodology for ultra-fast local agentic execution.
  • Cogni-Brain: Pushed Nemotron-3-Super-120B on NVIDIA DGX Spark beyond one-click demo workflows into sustained long-context agentic work; operated within NVIDIA NeMoHermes / NeMoClaw's hardened OpenShell model, stabilised a 131K local context, achieved ~24 tok/s, and documented the benchmark methodology for the community.
  • SageGPT-7.5M (NVIDIA DGX only): SLM trained from scratch on ~140M pure Sanskrit tokens on NVIDIA DGX Spark. 6 Layer, 8 Attn Head, 256 embed, 1024 context.
  • SageGPT-7M (MLX only): SLM trained from scratch on ~57M Sanskrit tokens on Apple Silicon. 4 Layer, 8 Attn Head, 256 embed, 256 context.
  • Cogni.chat: Local-first multimodal AI ecosystem for personal and household intelligence, designed to support memory, planning, wellbeing, learning, creative work, and family coordination.
  • Fiduciary-Ops-Agent: Autonomous enterprise governance agent utilising a strict Check-then-Act protocol via Gemini 2.5 Flash Lite; enforces real-time fiduciary risk-alignment using tool-first orchestration.

"I have no special talent. I am only passionately curious" — Albert Einstein

Pinned Loading

  1. dgx-spark-qwen-super-agent dgx-spark-qwen-super-agent Public

    Cogni-Brain-2: Qwen 3.6-35B on DGX Spark via Atlas. 218.85 tok/s, 100/100 Tool-Eval, local NVFP4 acceleration.

    Python 1

  2. dgx-spark-nemotron-super-agent dgx-spark-nemotron-super-agent Public

    Cogni-Brain: Nemotron-3-Super-120B on DGX Spark via vLLM. Stable 131K local context, ~24 tok/s, hardened agentic stack, and reproducible benchmark methodology.

    Python 5 3

  3. sage-gpt sage-gpt Public

    SageGPT (7.5M param SLM): A Transformer trained from scratch on ~140M pure Sanskrit tokens on NVIDIA DGX Spark. 6 Layer, 8 Attn Head, 256 embed, 1024 context, ~8K vocab.

    Python

  4. fiduciary-ops-agent fiduciary-ops-agent Public

    An autonomous Fiduciary Agent powered by Gemini Flash Lite that enforces enterprise risk governance (CLV vs Refund) using strict tool-first protocols

    Jupyter Notebook

  5. sage-gpt-mlx sage-gpt-mlx Public

    SageGPT 7.25M param SLM trained from scratch on 56.89M Sanskrit tokens using Apple MLX. 4-layer decoder-only Transformer with 8K vocabulary for Apple Silicon inference.

    Python