carsonpoole
Comparing web search API providers on a Deep Research gauntlet
Web Search API for Agents 70x Cheaper Than Exa
Using a tiny GPT model to beat Brotli/ZSTD, 600x faster than Fabrice Bellard's
Nvidia GPU Specs and Pricing Cheatsheet
Free AI Audio Book Summaries
Re:Show HN: FileFolder: AI File Manager: Auto Tag and Name and Vector ...
on Sunday September 01, 2024 @10:12PM (#41422062)
Thanks for the feedback! Do you think a dropbox-like setup with syncing some directory would suffice? or would it need to be completely offline?
Show HN: FileFolder: AI File Manager: Auto Tag and Name and Vector Search
Free Client Side Suite of Image/PDF Conversion and Resize and Compression
CUDA Utils – Simple CUDA utils/helpers for simplifying ND tensor memory access
150 LoC CUDA I8 Matmul That Beats CuBLAS Tensor Core FP16
Safetensors.cpp – Zero Dependency Safetensors Loading and Storing in C++
AI Receipt Tracker – AI takes your receipt photos and PDFs and extracts details
Free AI Chatbot – Locally Stored AI Chat, CSVs, Images, Claude, GPT4, Lots More
Local Only Embedding and Vector Search of 50k Web Pages from Fine Web
Haystack Embedded – 30x faster than FAISS, local first vector DB in pure Rust
Re:Haystack DB – 10x faster than FAISS with binary embeddings by default
on Monday April 29, 2024 @01:54AM (#40194914)
I wholeheartedly agree :) I've mostly put this together this weekend, so I haven't had time to do everything yet, but that's definitely on the todo list.
I FT'd some siglip models (see here: https://huggingface.co/carsonpoole/binary-siglip-text) that should be amenable to binary quantization so I'm going to tomorrow get an inference server running with that and then hopefully do the typical MTEB benchmarks for embeddings
Re:Haystack DB – 10x faster than FAISS with binary embeddings by default
on Monday April 29, 2024 @01:04AM (#40194656)
thank you for the kind words!
Re:Haystack DB – 10x faster than FAISS with binary embeddings by default
on Monday April 29, 2024 @01:04AM (#40194654)
not yet, but it's roughly linear at scaling, since it's a brute force algorithm. so with the current version it'd probably be about 22 seconds for a 1B vector search. the whole point of having metadata queries are to prevent those kind of searches from being necessary, and hopefully with some FTS interspersed it can reduce the number of similarity comparisons required even more
Re:Haystack DB – 10x faster than FAISS with binary embeddings by default
on Monday April 29, 2024 @01:02AM (#40194639)
IMO at least there are a lot of things that other vector DBs are missing and should exist. I want to make this work at petabyte scale data with the features on the readme's roadmap plus some others I have nebulous ideas about.
Re:Haystack DB – 10x faster than FAISS with binary embeddings by default
on Monday April 29, 2024 @12:03AM (#40194282)
It works right now, but I'm actively adding a lot of additional things that might make your life easier. The roadmap on the readme shows what I'm working on adding. Feel free to shoot me an email at carson at poole.ai and I'd be happy to give some guidance, but a quickstart is definitely at the top of my priorities also. :)