Serverless Rl: Faster, Cheaper and More Flexible Rl Training
Posted3 months agoActive3 months ago
openpipe.aiTechstory
supportivepositive
Debate
10/100
Serverless ComputingReinforcement LearningAI Training
Key topics
Serverless Computing
Reinforcement Learning
AI Training
The article discusses the benefits of using serverless computing for reinforcement learning (RL) training, and the HN community generally agrees on its potential advantages.
Snapshot generated from the HN discussion
Discussion Activity
Light discussionFirst comment
6m
Peak period
3
0-1h
Avg / period
3
Key moments
- 01Story posted
Oct 8, 2025 at 3:06 PM EDT
3 months ago
Step 01 - 02First comment
Oct 8, 2025 at 3:12 PM EDT
6m after posting
Step 02 - 03Peak activity
3 comments in 0-1h
Hottest window of the conversation
Step 03 - 04Latest activity
Oct 8, 2025 at 3:35 PM EDT
3 months ago
Step 04
Generating AI Summary...
Analyzing up to 500 comments to identify key contributors and discussion patterns
Discussion (3 comments)
Showing 3 comments
altryne1
3 months ago
Will the rate limits go higher? How about other models? Qwen 2.5 is nice but 3 is nicer
cmatrub
3 months ago
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.
Arctic_fly
3 months ago
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.
View full discussion on Hacker News
ID: 45519476Type: storyLast synced: 11/17/2025, 11:10:42 AM
Want the full context?
Jump to the original sources
Read the primary article or dive into the live Hacker News thread when you're ready.