How context can change a retrieval ranking
Why shared bipolar binding preserves a ranking, how weighted similarity can change it, and what remains to be tested for useful retrieval.
Blog
Blog Archive
Every post from HDC Labs, collected in one place, newest first.
All posts
Showing 6–10 of 26 posts
Semantic compression inside wide hypervectors
How a compact abstraction can use thousands of coordinates, and what the extra width buys an HDC system.
Turn graph data into hypervectors for associative search
Learn how to encode node properties and edge direction with HDC, compose a partial query, and resolve similarity matches back to exact graph records.
Your data is connected. Can you find a pattern like this one?
A delayed sales order shows how searching connected patterns could help teams find useful past cases, then check the facts in a graph.
When AI remembers what happened after the answer
A warehouse robot's detour shows how connected evidence and HDC memory could help AI reuse experience while checking what is valid now.
Getting started
New to HDC? Start with these four introductions.
Introduction to Hyperdimensional Computing
A gentle introduction to how hyperdimensional computing represents, combines, and retrieves information using high-dimensional hypervectors.
What is a Hypervector?
A closer look at the high-dimensional, distributed mathematical objects that give hyperdimensional computing its unusual geometry.
The Holographic Nature of Hypervectors
How Hyperdimensional Computing distributes information across an entire hypervector, helping representations degrade gradually under noise.
A brief history of vector symbolic architectures
How the problem of representing structured knowledge in distributed systems gave rise to the family now known as HDC and VSA.
Contact
Have a representation problem in mind?
If you're working with connected data, retrieval, agent memory or online learning, we'd love to hear what you're building and where the current representation is falling short.
Get in touch
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