Wow! 4GB for 10 million documents. This means one could build a reverse index much faster than before and devx processes like debugging, performance testing would become much smoother. Can't wait for the sqlite bindings to come out!
show comments
nharada
It would be nice to have the README be a little more human written for a project where you actually want people to adopt it
If anyone is looking to retrofit to an existing pipeline, I use similar ideas to compress vectors for job search, getting roughly 8x compression with about a 3.5% drop in quality. My experiment: https://corvi.careers/blog/vector-search-embedding-compressi...
lmeyerov
Interestingly, while we don't fine-tune generative models for Louie.ai, we found fine-tuning embedding models to be a major $ saver. Instead of 1K-2K wide frontier embedding vector lens... Just 64. Huge savings on vector DB $$$.
I'm curious how that works with something like turboquant. Not needed any more, still dominant, better together, ... .
anishvarghese
This looks perfect for local, privacy first search, but since it's built in Rust, has anyone tried compiling it to WASM to run directly inside a browser extension?
What's a good embedding model and search to run locally? something fast and lightweight.
beernet
Why not just use Qdrant? They've been integrating TurboQuant for months, works well.
show comments
OutOfHere
I am not convinced that Turbovec yields better retrieval than the same amount of bits of a Matryoshka embedding.
burgerboii
Who is this co-author called t <t@t>?
show comments
refulgentis
Bloviating nonsense, 3rd time I’ve seen something like this in HN since TurboQuant came out. You don’t need float32, never did. Source: I’ve been writing on device embedding code for 4 years.
spoaceman7777
Well. That is insane. O_O Fantastic job!
cute_boi
Another vibe coded slop where they can't even spend time on Readme or documentation around code...
esafak
lancedb and duckdb integrations would be great...
zuzululu
what could i use this for as part of my agentic workflow? codebase indexing? docs ?
FAISS is no longer close to SoTA:
https://ann-benchmarks.com/index.html https://vector-index-bench.github.io/ https://big-ann-benchmarks.com/neurips23.html
Wow! 4GB for 10 million documents. This means one could build a reverse index much faster than before and devx processes like debugging, performance testing would become much smoother. Can't wait for the sqlite bindings to come out!
It would be nice to have the README be a little more human written for a project where you actually want people to adopt it
people should read turboquant's open review comments: https://openreview.net/forum?id=tO3ASKZlok
If anyone is looking to retrofit to an existing pipeline, I use similar ideas to compress vectors for job search, getting roughly 8x compression with about a 3.5% drop in quality. My experiment: https://corvi.careers/blog/vector-search-embedding-compressi...
Interestingly, while we don't fine-tune generative models for Louie.ai, we found fine-tuning embedding models to be a major $ saver. Instead of 1K-2K wide frontier embedding vector lens... Just 64. Huge savings on vector DB $$$.
I'm curious how that works with something like turboquant. Not needed any more, still dominant, better together, ... .
This looks perfect for local, privacy first search, but since it's built in Rust, has anyone tried compiling it to WASM to run directly inside a browser extension?
There are already several openreview comments alleging academic misconduct around TurboQuant: https://openreview.net/forum?id=tO3ASKZlok
Some write-ups argue that this was deliberate rather than a good-faith mistake: https://dev.to/gaoj0017/turboquant-and-rabitq-what-the-publi...
And now this. Pretty bold AI slop.
What's a good embedding model and search to run locally? something fast and lightweight.
Why not just use Qdrant? They've been integrating TurboQuant for months, works well.
I am not convinced that Turbovec yields better retrieval than the same amount of bits of a Matryoshka embedding.
Who is this co-author called t <t@t>?
Bloviating nonsense, 3rd time I’ve seen something like this in HN since TurboQuant came out. You don’t need float32, never did. Source: I’ve been writing on device embedding code for 4 years.
Well. That is insane. O_O Fantastic job!
Another vibe coded slop where they can't even spend time on Readme or documentation around code...
lancedb and duckdb integrations would be great...
what could i use this for as part of my agentic workflow? codebase indexing? docs ?
[dead]
[dead]
[flagged]