With Beam, we can easily experiment approaches such as Chain-Of-Though-with-Self-Consistency (CoT-SC) and other reasoning meta framework, but with more manual control. I always had issues using LLM's chat driven interface to figuring out/explore issues that i'm interested, since conversation/chats is always linear while reasoning/working on some ideas is structural. Beam seems to be a much better UX than the linear chat UX that saves me a lot of copy and paste and save and retry. Awesome work!
Yes, the only issue is the usage of tokens, which is obviously greater as we are sampling more of the solutions space. But it's a compromise to have GPT-4.5 level intelligence with GPT-4.
Probably even higher jump as the models have some amount of unique training data, and they are fact-checking each other, to a more common “truth”, and hallucinations are weeded out.
Comments
With Beam, we can easily experiment approaches such as Chain-Of-Though-with-Self-Consistency (CoT-SC) and other reasoning meta framework, but with more manual control. I always had issues using LLM's chat driven interface to figuring out/explore issues that i'm interested, since conversation/chats is always linear while reasoning/working on some ideas is structural. Beam seems to be a much better UX than the linear chat UX that saves me a lot of copy and paste and save and retry. Awesome work!
Yes, the only issue is the usage of tokens, which is obviously greater as we are sampling more of the solutions space. But it's a compromise to have GPT-4.5 level intelligence with GPT-4.
Probably even higher jump as the models have some amount of unique training data, and they are fact-checking each other, to a more common “truth”, and hallucinations are weeded out.