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Show HN: Beam – Find Better Answers with Multi-Model AI Reasoning
HN, first things first: one year ago you make me believe in my opensource AI project, and I'm forever grateful[1].
I am back with Beam - a technique to use diverse LLMs to generate responses, and Merge them - all within a snappy UX. I am no researcher, so you'll find a dark-mode blog, and not a light-mode PDF on arxiv :)
Blog, open code, and live hosted demo, all published.
You can use Beam early on in a chat, where looking at more options is key to be more confident in the answer, but also when no answer if perfect, but fusing many together will work well.
Take a look and let me know what you think!
[1]: The good reception to my first HN post and the 300 GH stars gave me the courage to follow my passion and double-down on my project, which now users love.
- deleted 2y ago[deleted]
- keithc24 2y agoWow, this is awesome. I tried Beam mode. It does produce better results!
- fredliu 2y agoAwesome feature! Quick question, how do you choose which model to use when you "fuses" multiple beams back into one?
- arbiterFF 2y agoI can't believe how much quicker it is to get to an optimal, comprehensive outcome using Beam. This is a groundbreaking way of interacting with LLMs.
- enricoros 2y agoSame experience. Once you beam you look for it everywhere!
- fredliu 2y agoExactly my thought, as mentioned in the other thread, Chat's linear conversation style is not fit for reasoning/exploration type of tasks, while Beam's fan-out -> select --> merge is a much better and natural flow!
- keithc24 2y ago[flagged]
- fredliu 2y agoWith 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!
- enricoros 2y agoYes, 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.
- keithc24 2y agoProbably 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.
- Ig0tU 2y ago[dead]
- Ig0tU 2y ago[dead]
- molander 2y agoHuge fan, thank you for your hard work! This is ok outstanding!!
- enricoros 2y agoThank you so much - there's much more and much better coming ;)
- sdeshcloud 2y agoThis is a very clever approach… I am super interested
- enricoros 2y agoOne person on Discord has called this 'taking the idea of self-consistency forward to ensemble model usage'. I guess this is, technically, what this approach is about :)