
Exploring informational models of consciousness, their methodological contributions, and limitations in guiding mechanistic research. Critiques panpsychist interpretations and discusses quantitative recharacterizations.

Categorical formulation of Predictive Processing and Active Inference using string diagrams, clarifying key concepts and enabling comparison with Integrated Information Theory.

Explores puzzling phenomena of consciousness using the Conscious Turing Machine model, including pain's impact on sleep, experiences vs. simulations, illusions, dreams, and free will.

Exploring brain dynamics through evolving informational structures, linking to consciousness theories and providing insights into disorders of consciousness with high-precision classification.

Explores Brainish, a multimodal language for AI consciousness, building on the Conscious Turing Machine. Discusses its syntax, semantics, and implementation for advancing machine intelligence and consciousness models.

Explore mathematical representation of consciousness through Quality Spaces theory, examining methodology, pros and cons, and potential improvements for a comprehensive understanding of qualitative properties.

Explore mathematical phenomenology's role in consciousness studies, examining how objectivity emerges from subjectivity using category theory and mathematical invariants.

Explore a substrate-independent model of consciousness inspired by Turing's computation model and Baars' Global Workspace theory, offering insights into conscious experiences across animals and machines.

Exploring the connection between consciousness and intelligence in humans and AI, examining theories and proposing a unified model for developing more advanced artificial agents.

Exploring connections between consciousness and AI, combining theories like Global Workspace Theory with deep learning to develop a new paradigm for general-purpose intelligence and brain-to-brain communication.

Explore the concept of emergence in consciousness theories, examining its meanings, applications, and implications for understanding the nature of consciousness.

Explores a novel model of visual perception using gnomonic projection to map objective 3D space onto a curved subjective space, explaining phenomena like foreshortening and straight line perception.

Exploring computational complexity of consciousness, analyzing arguments for non-computability, and proposing conditions for implementable conscious systems in artificial intelligence.

Exploring conscious agent theory, polytope dynamics, and their connection to particle physics, offering insights into the mind-body problem and emergence of spacetime.

Explores a formal theory of consciousness, proposing that agent interactions create complex structures and fuse subjects and qualia, with spacetime as an interface for these interactions.

Explores model unity in consciousness research, examining mathematical formulations and experimental results to understand phenomenal unity and its implications for unified experiences.

Explore a novel model of human cortex using range-dependent networks of phase-resetting clocks, offering insights into consciousness and cognitive processing with simplified simulations.

Explore the intersection of psychedelics, free will, and consciousness. Discover how serotonergic pathways may influence volitional capacities and adaptive flexibility in human cognition and behavior.

Explores how the geometry of internal world models affects behavior, focusing on the Projective Consciousness Model and its implications for understanding consciousness and designing social robots.

Exploring machine consciousness: challenges, theories, and implications. Analyzes information, computation, and phenomenal experience in AI, discussing strong vs. weak machine consciousness and their achievability.

Explore the intersection of AI, creativity, and consciousness with Oxford professor Marcus du Sautoy. Delve into the potential of machines to think, create, and impact our future in this thought-provoking talk.