4 ms·
The model can't reason comprehensively (e.g., like Sol XHigh would to solve a complicated problem), but it's designed to be able to answer anything a human reas
by zenlikethat 16d ago
The model can't reason comprehensively (e.g., like Sol XHigh would to solve a complicated problem), but it's designed to be able to answer anything a human reasonably could quickly and intuitively, i.e., system one thinking: https://en.wikipedia.org/wiki/Thinking,_Fast_and_Slow https://en.wikipedia.org/wiki/Thinking,_Fast_and_Slow
- vintermann 16d agoI wonder how well it can play chess, or go.
- leo4242 14d agoI was wondering the same! So I asked Astra to build me https://jev-chess-master.vercel.app/ https://jev-chess-master.vercel.app/ where you play against Jev AI as chess player. You play White, and Jev plays Black. Rather than asking an LLM to generate move strings or JSON, the backend feeds all server-validated legal candidate moves into Vercel AI SDK's experimental_evaluate(). Jev picks Black's move and outputs its probability distribution across all legal candidates in a single forward pass (~300ms, ~$0.00004/move). Github link: https://github.com/qibinlou/jev-chess https://github.com/qibinlou/jev-chess Give a try and let me know your thoughts! I am having lots of fun coming up with different chess strategies for Jev to try out.
- haute_cuisine 12d agoThanks for the demo. It plays very bad and blunders pieces on every move.