Turning feedback into learning
When tasters score a food product, their feedback reveals more than an overall rating. Explore how HDC turns those scores into patterns we can compare, revise and learn from.
Blog
Exploring HDC, from concepts to implementation
Explore everything we publish, from practical use cases and approachable HDC concepts to research perspectives and implementation.
Latest posts
Allostasis for machines
When a robot's load, charge or temperature changes, a familiar route can make very different demands. We explore how HDC memory could help it prepare for the journey ahead.
Testing the limits of bundling capacity (2)
How many records fit in a 2,048-dimensional hyperspace before unrelated records start to look alike? Our experiments suggest that the answer depends on how many comparisons we make.
Reviewing TrainableHD: What changes when the encoder learns?
How TrainableHD learns its encoder as well as its classes. We follow a mistake through training, work through an incident example, and examine the costs of deployment.
Testing the limits of bundling capacity (1)
What happens as we pack more and more facts into a bundle? We study the limits of bundling capacity with a 50-item questionnaire.
What do cleanup and crosstalk mean in HDC?
A look back at how the HDC literature describes the terms "cleanup" and "crosstalk", and how we can view both terms through a modern lens using vector search in LanceDB.
Durable memory, transient prototypes
An HDC experiment that separates stored examples from temporary class summaries, and compares rebuilding with caching.
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.
Why permutation matters in HDC
An introduction to the role of permutation in hyperdimensional computing and how it preserves structural information in ways that multiplicative binding cannot.
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.
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