Goliath @zero_goliath
reinforcement learning @ritserlabs @uwaterloo cs Waterloo Joined March 2022-
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check out my terminal-bench env and DM me if you have feedback!
check out my terminal-bench env and DM me if you have feedback!
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ryanair in-flight commercials but for meta personal superintelligence
the decade of forcing yourself to stop using em dashes
if you build good evals for the similarity of an AI-generated app/website to its real counterpart, you can RL llms to be better at creating economically valuable RL environments
i think given recent LLM RL progress, it's worth looking into scaling laws for RL out-of-distribution generalization again lesswrong.com/posts/65qmEJHD… especially this > a meaningful measure of distance between tasks, which is difficult and could deserve a project on its own
here are some interesting blog posts from the past few months on scaling RL. (credit to @yong_zhengxin for linking to three others) 1. ysymyth.github.io/The-Second-Hal… 2. yidingjiang.github.io/blog/post/expl… 3. kevinlu.ai/the-only-impor… 4. yongzx.substack.com/p/rl-vs-next-t… 5. blog.jxmo.io/p/how-to-scale…
there'll be a lot more research/tooling in the next 12 months on LLMs for long-horizon/realistic tasks. along the lines of - augmented PRMs - prioritized experience replay (+ envs that support snapshotting) - world-model interpretability most will be unpublished at private labs
its nice to read old tweets and see replies that i know for sure arent AI slop
feel free to DM me about suggestions/feedback
feel free to DM me about suggestions/feedback
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