While I like the blogpost, I think the use of unexplained acronyms undermines the opportunity of this blogpost to be useful to the wider audience. Small nit: make sure acronyms and jargon is explained.
i actually think thats what made it crisp
Readit Newsanonthrowawy commented on Q-learning is not yet scalable seohong.me/blog/q-learnin... · Posted by u/jxmorris12
This doesn’t address the primary issue: that they had no methodology for choosing puzzles that weren’t in the training set and indeed while they claimed to have chosen puzzles that aren’t they didn’t explain why they think that. The whole point of the paper was to test LLM reasoning in untrained cases but there’s no reason to expect such puzzles to not part of the training set, and if you don’t have any way of telling if it is not or then your paper is not going to work out
how could you prove that?
This news coupled with google raising the new gemini flash cost by 5x, azure dropping their startup credits, and 2-3 others(papers showing RL has also hit a wall for distilling or improving models), are now solid signals that despite what Sam altman says, intelligence will NOT be soon too cheap to meter. I think we are starting to see the squeeze from the big players. Interesting. I wonder how many startups are betting on models becoming 5-10x cheaper for their business models. If on device models don't get good, I bet a lot of them are in big trouble
[1] https://www.investing.com/news/economy-news/anysphere-hires-...
any reference for this?