First screen, captured .
Looks similar
OK, I can partly explain the LLM chess weirdness now(dynomight.net)
467 points by dmazin | 419 comments
Dynomight blog post following up on why gpt-3.5-turbo-instruct plays chess well while other LLMs play poorly, testing several theories.
LLMs are good at playing you(lcamtuf.substack.com)
117 points by zdw | 56 comments
Chess engines do weird stuff(girl.surgery)
136 points by admiringly | 69 comments
Related stories
Training LLMs from ground zero as a startup(yitay.net)
360 points by swyx | 92 comments
Yi Tay's blog post on the experience of training large language models from scratch at a startup (Reka), covering compute, infrastructure, and lessons learned.
LLMs use a surprisingly simple mechanism to retrieve some stored knowledge(news.mit.edu)
336 points by CharlesW | 121 comments
MIT News article on research showing LLMs often retrieve stored facts via simple linear functions, and a technique to probe what a model knows about subjects.
Grandmaster-level chess without search(github.com)
340 points by lawrenceyan | 150 comments
GitHub repository from Google DeepMind with code, data, and checkpoints for the paper 'Grandmaster-Level Chess Without Search'.
Some thoughts on LLMs and software development(martinfowler.com)
378 points by floverfelt | 347 comments
Martin Fowler's blog post sharing scattered thoughts on the state of LLMs and AI and their effect on software development.
Spending 10 months building the most human-like chess bot(mbuffett.com)
29 points by marcusbuffett | 10 comments
A blog post by Marcus Buffett describing ten months spent building a chess bot designed to play like a human.
LLMs aren't world models(yosefk.com)
330 points by ingve | 189 comments
Blog post by Yossi Kreinin arguing that large language models are not world models, illustrated with examples like LLMs losing track of chess board state.