In this episode of Hidden Layers, Ron Green sits down with Dr. Karl Friston—world-renowned neuroscientist and originator of the Free Energy Principle—and Dan Mapes, founder of Verses AI and the Spatial Web Foundation. Together, they explore how neuroscience is beginning to reshape artificial intelligence.

They break down complex but powerful ideas like active inference, biologically plausible AI, and collective intelligence. You'll hear how concepts from brain science are influencing next-gen AI architectures and what the future might hold beyond large language models.

From the limitations of backpropagation to the promise of decentralized, embodied, and domain-specific models, this is a deep dive into the future of intelligent systems—and the science behind them.

In this episode of Hidden Layers: Decoded, Ron Green, Dr. ZZ Si, and Michael Wharton explore the latest AI breakthroughs, including Sakana AI’s biologically-inspired “Continuous Thought Machines,” the self-taught coding model Absolute Zero, and Salesforce’s unified vision-language system BLIP3-o. They discuss the growing importance of reinforcement learning in a data-constrained world, Google’s diffusion-based language and video models, and Anthropic’s industry-leading interpretability efforts. The team also covers Apple’s AI missteps and a new study revealing why single, well-structured prompts outperform long chat sessions. Throughout, they reflect on alignment risks, emergent reasoning, and the changing shape of model development and training strategy.

In this episode of Hidden Layers, Ron Green sits down with Dr. Risto Miikkulainen — Vice President of AI Research at Cognizant Advanced AI Labs and Professor of Computer Science at UT Austin — to explore the fascinating world of evolutionary computation. They dive deep into the differences between supervised learning, reinforcement learning, and evolutionary techniques, and why evolutionary approaches offer unique advantages for creativity, scalability, and innovation in AI.

Dr. Miikkulainen shares real-world examples of unexpected discoveries, from cyber agriculture breakthroughs to designing new AI architectures. They also discuss the future of multi-agent systems, surrogate modeling, and how evolutionary computation could help us better understand the emergence of intelligence and language. Plus, Dr. Miikkulainen previews his upcoming book Neural Evolution: Harnessing Creativity in AI Model Design.