4 ms·
Show HN: TurboQuant-WASM – Google's vector quantization in the browser
- hhthrowaway1230 6mo agoAwesome! Also love the gaussian splat demo, cool use case!
- bingbong06 6mo ago[flagged]
- newbrowseruser 6mo ago[dead]
- glohbalrob 6mo agoVery cool. I added the new multi embedding 2 model to my site the other week from google I guess need to dig into this and see if it’s faster and has more use cases! Thanks for publishing your work
- aritzdf 6mo ago[flagged]
- himmelsee2018 6mo ago[flagged]
- refulgentis 6mo agoSloppiest slop I've seen in a couple weeks: - fork of a fork of a quantization technique - Only contribution is...compiling JS to WASM by default? - suspicious burst of ~nothing comments from new accounts - 6 comments 7 hours in, 4 flagged/dead, other 2 also spammy, confused and making category errors at best, at worst, more spam. - Demo shows it's worse: 800 ms instead of 2.6 ms for text embedding search - "but it saves space" - yes! 1.2 MB in RAM instead of 7.2 MB to turn search into 1s on a MacBook Pro M4 Max, instead of sub-frame duration. - It's not even wrong to do this with the output embeddings, there's way more obvious ways to save space that don’t affect retrieval time this much
- teamchong 6mo agoI made some adjustment, can you try again? Is it faster now? https://teamchong.github.io/turboquant-wasm/search.html https://teamchong.github.io/turboquant-wasm/search.html
- netdur 6mo agoI tried TQ for vector search and my findings is not good, it is not worth it if you cannot use GPU, however I got same quality of search as 32f using 8bit quant I wrote ann ext for sqlite, using tq, I do save a lot on space but 32f is still faster despite everything I have tried code here https://github.com/netdur/munind/tree/main/src/tq https://github.com/netdur/munind/tree/main/src/tq