Skip to content

Serverless RL: Faster, Cheaper and More Flexible RL Training

openpipe.ai
9 pointsslewis3 comments
On HN

Comments

Interesting post. Did the difference in wall clock training time take the reduction in cold start time into account? Seems like that could be a significant factor for small jobs and negligible for large ones.

Will the rate limits go higher? How about other models? Qwen 2.5 is nice but 3 is nicer

higher abstraction than Tinker, more flexible than OpenAI RFT. i like integration to production inference, so i can switch between training and inference for continuous learning.

AboutSource Built by g1lg1l

Hackerly is an independent reader for Hacker News, built on the public HN API. Not affiliated with Y Combinator.