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.
Blog
Blog Archive
Every post from HDC Labs, collected in one place, newest first.
All posts
Showing 11–20 of 28 posts
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.
What can we recover from a bundled hypervector?
Five MAP experiments explore how bundled hypervectors support semantic retrieval, explainable scores, query preferences, and removal of known facts.
A category is something a system does
What a new neuroscience framework proposes about context, compression, and action, and how HDC could turn those ideas into a computational architecture.
Does HDC fit the physics of light? Reviewing PhotoHDC
A critical review of PhotoHDC's modeled electro-photonic accelerator, what its evidence supports, and how OLIX and recent optical HDC work sharpen the deployment question.
Do HRR and MAP preserve the same similarity structure?
A reproducible experiment that tests whether HRR and MAP preserve the same similarity structure in a shared encoder.
The (not so surprising) similarities between HDC algebras
How HRR, BSC, and MAP implement the same broad VSA computation shape despite using different hyperspaces and mathematical operations.
Can a compiler spend HDC's accuracy budget? Reviewing ApproxHDC
How ApproxHDC searches application, compiler, and simulated-hardware choices to trade HDC task quality for speed and energy efficiency, and what the reported evidence establishes.
Why connected data needs associative search
Graph search follows exact relationships, while associative search finds similar situations from incomplete examples.
Can hypervectors learn the hardware they run on?
How learnable HDC encoders can adapt similarity geometry to modeled compute-in-memory nonlinearities, and what the current evidence establishes.
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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