Active Inference AI for Scientific and Technical Computing: A Physics-Grounded Alternative to Machine Learning
March 10, 2026
9:00 AM - 10:00 AM PST
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About the Session
AI is rapidly being adopted across scientific and technical computing, from hypothesis generation and autonomous experimentation to robotic control and computational optimization. Most of these systems are built on machine learning, relying on statistical training, pattern completion, and post-hoc control mechanisms.
This talk introduces Active Inference AI as a fundamentally different approach that is grounded in the Free Energy Principle and explicitly aligned with physical systems. We compare machine learning–based AI with Active Inference AI, highlighting key differences in representation, adaptability, uncertainty handling, and system stability. The discussion focuses on why Active Inference is particularly well suited for scientific and engineering domains that require real-time control, coherent reasoning under uncertainty, and tight coupling to physical constraints, with examples spanning advanced computing and emerging applications such as quantum systems.
Speaker
Denise Holt
Founder & CEO, AIX Global Innovations
Denise Holt is Founder & CEO of AIX Global Innovations, advancing a new class of execution intelligence through Seed IQ™, an adaptive multi-agent autonomous control architecture.
At the intersection of Active Inference, physics-based dynamics, and intelligent systems deployment, her work focuses on building the intelligence layer required for complex, real-world systems that can coordinate action, maintain coherence, and adapt under uncertainty across environments where traditional AI breaks down, from enterprise operations and industrial automation to distributed infrastructure, energy systems, and emerging compute domains.
In 2024, she founded Learning Lab Central, a global education hub focused on Active Inference and spatial AI technologies. She is a voting member of the IEEE Spatial Web Protocol working group and speaks globally on Active Inference AI, execution intelligence, and adaptive autonomous multi-agent systems.
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