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Articole: 8
  1. 4× RTX PRO 6000 Blackwell on Water, and the One Card That Wouldn't Behave

    Converting four RTX PRO 6000 Blackwell cards to waterblocks, finding a VRM choke loose on the workbench, and getting back to 41k tok/s.

  2. Many Contexts Is All You Need

    RLM — Recursive Language Models.

  3. Test-Time Training for LLMs: Models Should Keep Learning After Deployment

    Pretraining taught us that neural networks can compress massive amounts of data into weights.

  4. Teaching Qwen3-4B to Trade: From Hold-Collapse to +9.4% Returns

    How I fine-tuned a 4B parameter LLM into a trading decision model using a 5-stage SFT waterfall and weighted CCE loss, then why I'm pivoting to GRPO reinforcement learning.

  5. MCP Compact: Keep Agent Context Lean

    A proxy that trims noisy tool outputs so MCP agents stay on track.

  6. All You Need is 4x 4090 GPUs to Train Your Own Model

    How I built an ML rig for training LLMs locally, exploring hardware choices, setup tricks, and lessons learned along the way.

  7. Defining AGI

    A thoughtful exploration of Artificial General Intelligence (AGI) through three fundamental concepts.

  8. Embarking on My Journey into LLM

    An introduction to my experiences and explorations in the world of Large Language Models.