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How does Exa serve billion-scale vector search? We combine binary quantization, Matryoshka embeddings, SIMD, and IVF into a novel system that can beat alternatives like HNSW. Shreyas gave a talk today at the AI Engineer World's Fair explaining our approach! ⬇️

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Exa

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85,482 просмотров • 1 год назад •via X (Twitter)

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Комментарии: 10

Фото профиля Jeffrey Wang
Jeffrey Wang1 год назад

@shreyas4_ @aiDotEngineer I wanna be nearest neighbors w/ @shreyas4_

Фото профиля Tigran III
Tigran III1 год назад

@shreyas4_ @aiDotEngineer i am still struggling to believe how much cracked engineering talent is coming from that one university. @shreyas4_ what's the secret sauce?

Фото профиля Martyn Strydom 🤸
Martyn Strydom 🤸1 год назад

@shreyas4_ @aiDotEngineer Unreal @shreyas4_

Фото профиля Karan☕
Karan☕1 год назад

@shreyas4_ @aiDotEngineer great talk learned a lot of new things, had this question: I think if you use binary quantization, for smaller embeddings you will get poorer results because of lossy compression(already dimension reduction is done and then BQ)

Фото профиля Prashant Dixit
Prashant Dixit1 год назад

@shreyas4_ @aiDotEngineer Anyone wants to just give a quick try and Build Matryoshka Embedding based RAG in a min, Give it a try 🙂

Фото профиля sophia
sophia1 год назад

@shreyas4_ @aiDotEngineer I'm confused why you said 8TB of memory to hold everything in RAM is too expensive. Back of the envelope Hetzner has 24 core/192GB systems for $366/mo. 8TB would be ~$200k/y or ~18k queries/$ @ 100 QPS

Фото профиля Hamish Ogilvy
Hamish Ogilvy1 год назад

@shreyas4_ @aiDotEngineer Nice work. So funny how obsessed people were with HNSW…

Фото профиля omkaar
omkaar1 год назад

@shreyas4_ @aiDotEngineer awesome great job guys

Фото профиля Aarush Sah
Aarush Sah1 год назад

@shreyas4_ @aiDotEngineer i love shreyas shreyas is so cool

Фото профиля agi
agi1 год назад

@shreyas4_ @aiDotEngineer love this - great insight for my product

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