[About]
Updating beliefs,
one inference at a time
Our Mission
Hyperpriors exists at the intersection of neuroscience and artificial intelligence. We believe the most profound insights about machine intelligence come from understanding biological intelligence—and vice versa.
Our blog explores the mathematical and conceptual frameworks that unify these fields: Bayesian inference, predictive processing, active inference, and the free energy principle. We translate cutting-edge research into practical engineering insights.
What We Cover
Active Inference
The mathematics of perception, action, and learning as free energy minimization.
LLM Internals
Deep dives into transformer architectures, attention mechanisms, and emergent capabilities.
Bayesian Brains
Neuroscience through the lens of probabilistic inference and prediction.
Responsible AI
Practical alignment, safety, and ethics for production AI systems.
Contributors
Dr. Elena Vasquez
Computational Neuroscience
Former research scientist at DeepMind. Specializes in active inference and predictive processing frameworks.
Marcus Chen
ML Engineering
10+ years deploying ML at scale. Previously at Anthropic and Google Brain. Focuses on production systems and interpretability.
Sarah Kim
AI Safety
Alignment researcher turned practitioner. Bridges theoretical safety research with real-world engineering constraints.
Work with us
Hyperpriors also offers consulting services for organizations building AI systems. We help teams apply neuroscience-inspired principles to real engineering challenges.
Learn about our services[Subscribe]
Posterior Updates
Weekly dispatches on AI, neuroscience, and the mathematics of mind. No spam, just signal.