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Currently doing a write up on scaling laws for RL. Here are the papers I'm covering so far:
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very high quality and detailed content if you want to learn how to post train llm!! https://t.co/9mD
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HOW TO GO VIRAL ON X: complete basics easy mode
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I didn’t used to have friends btw, had to learn how to meet people like this from first principles
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For more than 200 yrs, thousands of books & articles have been written about the history of the
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Grant Sanderson, (@3Blue1Brown) created one of the most beloved math channels on the internet.
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Wrote up some flashcards and practice problems to help myself retain what @reinerpope taught.
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Meta researchers cut LLM RL training compute by 40% using experience replay
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@teortaxesTex: excellent writeup
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These are also the two books I recommend to people wanting a foundation in post-training. Both comin
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lovely article going deeper into the RL-SFT-OPD spectrum with some very nice intuitions + experiment
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New blog post! Wrote about how SFT, RL, OPD relate to generalization and catastrophic forgetting :)
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How to actually land a remote job in 30 days.
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Incredible how Z. ai literally has their RL infrastructure open source.
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There is a really banger article on On-Policy Distillation. Came out on HF a few months back. https:
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Songlin Yang's video explanations
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Anthropic engineer just released a 2-hour workshop on "Graph Engineering" for agentic systems:
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NVIDIA has lost it..
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It’s late, so I’ll quietly give you the opening lesson from something I normally teach inside my $20
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ravi got to know about competition from my blog and then proceeded to mog me on the leaderboard. (i
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How does a model understand and explore a world it has never seen?
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Reading "Hyperagents". I am so glad I created Paper Breakdown.
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just finished a 3-hour /office-hours session using the prompt from the article:
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there is something very beautiful about gpt-oss-120b that makes it most hackable model for numerous
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