AWS S3 Vectors aims for 90% cost savings for vector storage. But will it kill vectordbs like Milvus? A deep dive into costs, limits, and the future of tiered storage.

Part 1 of 6 in the series “LLMs Need Knowledge Graphs. Use RDF or End Up Rebuilding It.”

End-to-end deep dive of the project, spanning a large GPU cluster, distributed RocksDB, and terabytes of sharded HNSW.

Retrieval Augmented Generation based on SQLite. Contribute to ggozad/haiku.rag development by creating an account on GitHub.

A brief introduction to using llamafile (a single-file tool for working with large language models) and sqlite-vec (A SQLite extension for vector search) to build a Retrival Augmentation Generation (RAG) application. This was a live online event hosted on Dec 17th 2024 in the Mozilla AI Discord, join us for the next event at at https://discord.gg/Ve7WeCJFXk LINKS: - Doc w/ links to all mentioned projects/blog posts: https://docs.google.com/document/d/17GYLzlGUyJF9EDeaa1P-dFFZnkwxATnBcg5KnNgpvPE/edit?usp=sharing - Slides: https://docs.google.com/presentation/d/14Szda-VnZzepL-1U9Nb7sXQg_TTf56OQ-KtUIMQ5xug/edit?usp=sharing

A vector search SQLite extension that runs anywhere! - asg017/sqlite-vec

Ready to become a certified watsonx AI Assistant Engineer? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/BdngMV 🚀 Try GraphRAG now! Access the code here → https://ibm.biz/BdngaC Learn more about GraphRAG here → https://ibm.biz/BdngM9 🤖 Can AI turn text into structured knowledge? Discover how GraphRAG leverages knowledge graphs, graph databases, and Cypher queries to transform unstructured data into actionable insights. See how LLMs enable intelligent retrieval and automation, reshaping workflows across industries. 🚀 AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdngMU #knowledgegraph #cypher #ai

Vector databases are kind of everywhere these days. There is a big pool of VC's that are pouring money into the ecosystem too. But while all of that is happening, sqlite has also gotten support for it. In this episode we talk the Alex Garcia, the maintainer of this project, and discuss how the project got created on what the future has in store. 00:00 Introduction 00:40 Dataviz 04:39 Chromebook matters 10:30 Why sqlite rocks 17:32 Facebook and VR stuff 26:19 Datasette & Simon 38:31 Towards sqlite-vec 46:46 Getting attention 52:38 Current work Sqlite-vec Github repo: https://github.com/asg017/sqlite-vec Alex Garcia blog: https://alexgarcia.xyz/blog/2024/sqlite-vec-hybrid-search/index.html Datasette discord: https://discord.com/invite/ktd74dm5mw Sqlite-vec channel on Mozilla Discord: https://discord.gg/Ve7WeCJFXk We have a Discord these days, feel free to discuss the podcast with us there! https://discord.probabl.ai You can follow the podcast on most podcast players including apple podcasts, spotify and rss.com. - https://podcasts.apple.com/us/podcast/sample-space/id1739598572 - https://open.spotify.com/show/0BnwEHuyOlHgeZfselpn1n - https://rss.com/podcasts/sample-space/ This podcast is part of the open efforts over at probabl. To learn more you can check out website or reach out to us on social media. Website: https://probabl.ai/ Bluesky: https://bsky.app/profile/probabl.bsky.social LinkedIn: https://www.linkedin.com/company/probabl Twitter: https://x.com/probabl_ai #probabl

Vector search has become a foundational tool for modern applications — from powering recommendation engines to enabling semantic search in…

I built a new plugin for my sqlite-utils CLI tool that lets you ask human-language questions directly of SQLite databases and CSV/JSON files on your computer. It’s called sqlite-utils-ask. Here’s …

Build powerful AI that you can trust with agentic data access for your LLMs.

A library for graph deep learning research. Contribute to divelab/DIG development by creating an account on GitHub.

Build a retrieval system with semantic, full-text, and fuzzy search in Postgres to be used as a backbone in RAG pipelines.

Install with Python, Node.js, Deno, Bun Rust, Go, C, WASM...

txtai is an all-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

Retrieval Augmented Generation (RAG) is a technique for adding extra “knowledge” to systems built on LLMs, allowing them to answer questions against custom information not included in their training data. …

A unified SQL query interface and portable runtime to locally materialize, accelerate, and query data tables sourced from any database, data warehouse, or data lake. - spiceai/spiceai

💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows - neuml/txtai

A series of top performing Text to SQL LLMs. Contribute to cfahlgren1/natural-sql development by creating an account on GitHub.

If you want to build a RAG-based tool, first build search.

With the popularity of Large Language Model, vector databases have also become a hot topic. With just a few lines of simple Python code, a vector database can act as a cheap but highly effective "external brain" for your LLM. But do we really need a specialized vector database?

ChatGPT is all the rage right now, and understandably so. Feeding it prompts and watching it spit out quality articles, recipes, travel itineraries, code examples, and more is fun and addictive. Yep, it’s a rabbit hole, and one we’re all getting a kick out of. One of ChatGPT’s many neat tricks is its ability to […]