ghita_

6 ms·

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Show HN: Ask Anything over NeurIPS 2025 Papers (Free, No Signup)(neurips.zeroentropy.dev)
2 points by ghita_ 10mo ago|0 comments
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Show HN: Zbench, RAG evals using chess Elo ratings(github.com)
3 points by ghita_ 1y ago|0 comments
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by ghita_ 1y ago
Hey! Thanks so much! I fixed the link thanks for flagging. Yes the same approach could be used for internet search. The fact that we now have an "absolute score" is very interesting since we can also use a threshold value to dete
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by ghita_ 1y ago
would love to check out the code if you have it!
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by ghita_ 1y ago
Yes! We did this here: https://www.zeroentropy.dev/blog/announcing-zeroentropys-fir... We wanted to share the approach with the community in this post. It does do better than competitors though!
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by ghita_ 1y ago
thank you, will check out the paper, the hf space is very cool!
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by ghita_ 1y ago
Thanks! We trained on most european languages (english, french, spanish, russian...), arabic, and chinese so it does well on those! We haven't tested too much on other languages, but happy to do so if there is a use case
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by ghita_ 1y ago
oh interesting, had no idea, thanks for sharing
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by ghita_ 1y ago
It actually runs pretty fast, our benchmarks show ~149ms for 12665 bytes. It's faster than many other models
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by ghita_ 1y ago
oh waw thanks for flagging, just fixed, thanks!
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by ghita_ 1y ago
yes we found it hard to find a good title for this, thanks for the feedback
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Show HN: Improving search ranking with chess Elo scores(zeroentropy.dev)
193 points by ghita_ 1y ago|65 comments
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by ghita_ 1y ago
ZeroEntropy (W25) | GTM Engineer | SF in person preferred, remote ok | Full-time | www.zeroentropy.dev We are building a high accuracy search engine for RAG and AI Agents. Our API is live and we're processing billions of tokens monthly
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by ghita_ 1y ago
ZeroEntropy | Founding Engineer | In person (San Francisco) | Full time | ghita@zeroentropy.dev Company: ZeroEntropy is building the next-generation retrieval engine for AI systems. We’re rethinking search from the ground up: faster, more a
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Show HN: ZeroEntropy (YC W25), Advanced AI Search over Complex Documents(dashboard.zeroentropy.dev)
3 points by ghita_ 2y ago|0 comments
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by ghita_ 2y ago
got it - i think the anecdotal evidence is what intrigued me a little bit looking forward to seeing the systematic relevancy benchmarks
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by ghita_ 2y ago
yeah i already have so many AI-generated videos in my feed on all social media it's insane. i spot them from far for now but at some point i'll just be consuming content that took seconds to generate just to get money
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by ghita_ 2y ago
there is a YC company that does that I think: https://www.rollstack.com/ i've never used them but I think they have many satisfied customers, maybe worth a shot!
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Show HN: I Used Llama-70B Logprobs for Better, Cheaper and Faster Chunking(github.com)
1 points by ghita_ 2y ago|0 comments
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by ghita_ 2y ago
Very impressive results. I'm curious how you benchmarked against bm25 in terms of accuracy? I couldn't find metrics around that, just one search example. I think there are use cases where latency is king, but when it comes to vect
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Ask HN: Is 100% recall search over private data solvable?
1 points by ghita_ 2y ago|0 comments
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by ghita_ 2y ago
Interesting, did you figure out a way to solve those?
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Show HN: Upload and Chat with Docs (Outperforms Azure Search)(searchlab.app)
1 points by ghita_ 2y ago|0 comments
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AGI requires better retrieval, not just better LLMs. Here's why(medium.com)
7 points by ghita_ 2y ago|0 comments
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by ghita_ 2y ago
That's cool! How does it perform compared to more "naive" methods? How did you go about comparing that performance, and was it in a real world RAG?
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GPT-4 is judged more human than humans in displaced and inverted Turing tests(arxiv.org)
3 points by ghita_ 2y ago|1 comments
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First open source Legal AI retrieval benchmark for RAG finally released(arxiv.org)
9 points by ghita_ 2y ago|0 comments