Krys Dolega, a philosopher of mind and cognitive scientist, dives into the influential works of Daniel Dennett, exploring his contributions to the philosophy of mind. The conversation spans the role of attention in shaping our phenomenal experiences and the complexities surrounding the concept of Markov blankets. Dolega examines the intersection of free energy principles and active inference, offering fresh insights into reality's nature. The discussion highlights the evolving understanding of consciousness and the nuances of predictive processing, challenging traditional views.

Thomas Metzinger, a contemporary philosopher renowned for his work on consciousness, explores fascinating concepts surrounding self-models and pure awareness. He dives into the interplay of consciousness with individual experiences, highlighting significant philosophical debates. The discussion reveals how our understanding of selfhood evolves through novel insights from cognitive science and the intricate relationship between subjective experiences and wider realities. Metzinger also touches on altered states of consciousness and their philosophical implications, making for an enlightening conversation.

Kathryn Nave, an expert in the Free Energy Principle and active inference, discusses agency, teleology, causality, constraints, predictability, attractor sets, memory transformation, human agency, perception, predictive processing, and consciousness in living systems.

Conor Heins, Senior ML Research Engineer, discusses collective behavior in complex systems, including emergence, social priors, and top-down causality. They explore mesmerizing biological phenomena like schools of fish and Starling Flocks, evolutionary pressures in the free energy principle, state-based vs path-based active inference, scene construction in inference, belief-free model selection, and the guest's learning journey in mathematics and physics.

Join Sanjeev Namjoshi, a textbook-writing, Bayesian-educating enthusiast, in a discussion covering the teaching of active inference, its relation to evolution, and learning mechanisms. Explore topics like unsupervised learning, Bayesian inference, survival strategies in a dynamic world, expectation maximization, simplifying mathematics for active inference, using Python, R, and MATLAB for simulations, the influence of priors in Bayesian modeling, mathematical concepts in active inference, phenotypic priors in AI, and cutting-edge topics on intelligence and gratitude.

Psychoanalyst and neuropsychologist Mark Solms discusses affect, consciousness, dreams, interoception, and more. Topics include subjective nature of affect, prioritization in consciousness, semantics of feelings, and the role of consciousness in adaptive behavior. The conversation also touches on Markovian monism, precision optimization, affect perception, and the complex relationship between dreaming and REM sleep.

Philosopher and cognitive scientist Wanja Wiese delves into consciousness, self-modeling, and ethical AI. They explore the intricacies of self-models, reflective self-awareness, epistemic agency, and the irreducibility of conscious experience. Discussions also touch on information geometry, belief dynamics, and the challenges of multiple levels of recursion in understanding and controlling systems.

Biologists Michael Levin & Franz Kuchling discuss morphogenesis, selfhood, and teleonomy. They explore how cells navigate complexities in achieving target morphology, beliefs and agency in active inference, metamorphosis in caterpillars, neuropsychospin, and bioelectricity in biological systems.

In this episode of Active Inference Insights, Darius invites philosopher and machine learning expert Alex Kiefer onto the show. Together, they tackle the big issues, from the role of representations in Active Inference to Bayesian structural realism, Helmholtz machines to POMDPs.

Neuro-computationalist Ryan Smith discusses empirical computational psychiatry, in-silico simulations, and the role of aberrant precision-weighting in neuropsychological disorders. The podcast delves into optimizing well-being through free energy, decision uncertainty in mental health conditions, exposure therapy, preferences in active inference models, emotional granularity, and future work in the field.