- 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
- I think their point is the size/performance tradeoff rather than outright performance. The point of TurboQuant is the size savings, while still giving high accuracy.
It's been a while, but I do recall some high-performing vector matching indexes being very large.
- Surprised that usearch isn't in any of these, it's pretty fast.
- 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!
- Also the removal latency is on a log scale. Which is quite insane.
- 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
- Anthropic employee. This is what your brain on kool aid looks like
- people should read turboquant's open review comments: https://openreview.net/forum?id=tO3ASKZlok
- tl,dr: there is an allegedly better alternative, and it's already implemented everywhere: https://github.com/VectorDB-NTU/RaBitQ-Library#rabitq-in-ind...
- 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?
- oxirs does embeddings and GraphRAG, and full text search with Tantivy; oxirs-vec, oxirs-graphrag
There's an oxirs-wasm with RDF and SPARQL bindings with a query budget. Tantivy-wasm says that the release WASM bundle is 1.5 MB.
cool-japan/oxirs: https://github.com/cool-japan/oxirs
oxirs-wasm: https://crates.io/crates/oxirs-wasm
tantivy-wasm: https://github.com/phiresky/tantivy-wasm
Is there an advantage to adding an MCP local memory interface over agent instructions on how to use a rust CLI?
And then write Markdown documents with Google OKF-like frontmatter YAML metadata for agents that work with tokens not linked data graphs; https://github.com/GoogleCloudPlatform/knowledge-catalog/blo...
- Also interested.
- 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.
- 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>?
- As it is heavily vibe coded, I think member of technical staff at antropic has no clue....
Next Prompt: remove t@t and force commit.
- 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...
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259 points by fittingopposite 17 hours ago | 32 comments