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コメント (15)

ghm21997日前
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!
nharada7日前
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
bobmarleybiceps6日前
people should read turboquant's open review comments: https://openreview.net/forum?id=tO3ASKZlok
sp19827日前
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...
anishvarghese7日前
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?
lmeyerov6日前
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, ... .

OutOfHere6日前
I am not convinced that Turbovec yields better retrieval than the same amount of bits of a Matryoshka embedding.
cat-whisperer6日前
What's a good embedding model and search to run locally? something fast and lightweight.
beernet7日前
Why not just use Qdrant? They've been integrating TurboQuant for months, works well.
mskkm6日前
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.

refulgentis7日前
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.
cute_boi6日前
Another vibe coded slop where they can't even spend time on Readme or documentation around code...
burgerboii7日前
Who is this co-author called t <t@t>?
esafak7日前
lancedb and duckdb integrations would be great...