We initiate the study of multi-attribute group fairness in $k$-nearest neighbor ($k$-NN) search over vector databases. Unlike prior work that optimizes efficiency or query filtering, fairness imposes ...
v0.7 of [trueform](https://trueform.polydera.com) gives NumPy arrays geometric meaning. Wrap a `(3,)` array and it's a Point. `(2, 3)` is a Segment. `(N, 3)` is N points. Eight primitives (Point, Line...
Structured generation for LLM tool use highlights the value of compact DSL intermediate representations (IRs) that can be emitted directly and parsed deterministically. This paper introduces axial gra...
Recent advances in large language models have demonstrated remarkable effectiveness in information retrieval (IR) tasks. While many neural IR systems encode queries and documents into single-vector re...
For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine. (⭐ 733...
Retrieval-Augmented Generation (RAG) addresses limitations of large language models (LLMs) by leveraging a vector database to provide more accurate and up-to-date information. When a user submits a qu...
We consider the non-adaptive bit-probe complexity of the set membership problem, where a set S of size at most n from a universe of size m is to be represented as a short bit vector in order to answer...
We consider the bit-probe complexity of the set membership problem, where a set S of size at most n from a universe of size m is to be represented as a short bit vector in order to answer membership q...
Thanks to sukhad anand for a great breakdown of how vector databases work.
His post inspired me to go a bit deeper into the indexing techniques that power fast vector search.
Most people think vector...
Multi-vector late-interaction retrievers such as ColBERT achieve state-of-the-art retrieval quality, but their query-time cost is dominated by exhaustively computing token-level MaxSim interactions fo...
A vector database, often abbreviated as "vector DB," is a type of database system specifically designed for storing and efficiently querying vector data. In a vector database, data is represented as v...
In this paper we investigate quantum query complexity of two vector problems: vector domination and minimum inner product. We believe that these problems are interesting because they are closely relat...
Stop querying your vector database for things that never change.
Most AI apps use RAG (Retrieval-Augmented Generation). Every single query
→ hits the vector database
→ retrieves chunks
→ se...
Totally unscientific musings on the nature of communication between humans and the similarity of AI hallucination to how we humans are misunderstanding each other all the time. AI hallucination happen...
Google TurboQuant — What it actually improves in AI workloads (and what it doesn’t)? https://lnkd.in/eU8bAEAK
There’s a lot of buzz around Google’s TurboQuant, but here’s the key point:
1....
Most people imagine AI systems like this:
User → AI model → Answer
But real AI products are far more complex.
Behind one response, there is usually a pipeline like this:
User Query
→ Query P...
Article : Kevin Inman and Pinecone Vector
Pinecone is a vector database that enables fast and scalable similarity search for machine learning applications. It has recently announced a serverless versi...
