kkkamur

4 ms·

1. 1.▲
   by kkkamur 27d ago

   I agree with everything you wrote but I would rather choose to be an optimist here because it will unlock an age of discovery where humans are going to live at 10x of their potential eventually and cure cancer and become a society bold and
2. 2.▲
   Show HN: 188M Hindi encoder, 28B tokens, 8K context, 1× RTX 4090(github.com)

   2 points by kkkamur 27d ago|0 comments
3. 3.▲
   by kkkamur 29d ago

   This is so dystopian dammmmm
4. 4.▲
   Show HN: Kullback – Synthetic RL Environments from Traces(leibler.dev)

   1 points by kkkamur 29d ago|0 comments
5. 5.▲
   by kkkamur 1mo ago

   Damm this is so cheap literally, I have been running 100s of subagents and it is cheap - with the contributor model ofc :)
6. 6.▲
   by kkkamur 1mo ago

   Fine tuning is a part of it, but environment generation and evaluation so that the training data matches the production is the hardest part. After the data comes in we can try OPD, RL, SFT to understand what method is the best one. Is this
7. 7.▲
   Leibler - Self Evolving Production Agents(leibler.dev)

   3 points by kkkamur 1mo ago|3 comments
8. 8.▲
   by kkkamur 1mo ago

   We’re building Leibler, a harness that turns production agent traces into training data and environments, then post-trains smaller models for your actual workload. Production traces → curated data & environments → evals → post-training