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if you want to get a deeper intuition about what is pre-training doing to the weights distribution I
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excellent post by @BerenMillidge on why rl actually works for llm's and how it's different from pre-
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I have been using small local models, mainly Qwen3.5-4B, to automate certain tasks. I have been work
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training CUA agents is now as simple as preparing a dataset :)
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@sunnykgupta: 20/ Final mindset
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If you want to understand the latest landscape of RL training and frameworks
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RL is so darn inefficient. But it doesn't need to be. dLLMs can dramatically accelerate RL training
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A solid starting point if you want to understand large language models (LLM) from a technical perspe
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You don't need random papers, just learn these concepts sequentially to kickstart your LLM engineer
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CUDA programming course for GPU optimization
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Training search agents usually assumes expensive ingredients: paid APIs, heavy human annotation, or
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if you're interested in VLAs, robotics, building foundational models for the next layer of physical
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@daniel_mac8: babe, wake up.
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The "Mismanaged Geniuses" Hypothesis
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Agricultural Field Boundary Delineation (Instance Segmentation) with GeoAI
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I'm happy to announce that we've just released a major update to our Mathematics for Machine Learnin
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@AlexFinn: My mind is so blown
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Introducing "codebase to course", a skill that turns any codebase into an interactive coding course
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I'm using Hermes Agent to teach myself Lean. It designed a 12 part curriculum with a bunch of practi
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Reinforcement Learning from Human Feedback by Nathan Lambert
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veeery cool writeup digging into nuances of training, experimentation, and infra for multi-agent RL
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Paged Attention in LLMs, clearly explained!
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Our new course, "Agentic AI Engineering," contains 17 notebooks and a complete multi-agent project (
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I've been teaching 100,000 fake students for 2 weeks.
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