Dan Breeden

Dr. Sanjeev Namjoshi, a machine learning engineer who recently submitted a book on Active Inference to MIT Press, discusses the theoretical foundations and practical applications of Active Inference, the Free Energy Principle (FEP), and Bayesian mechanics. He explains how these frameworks describe how biological and artificial systems maintain stability by minimizing uncertainty about their environment.

Daniel C. Dennett is one of the most influential philosophers of our time, perhaps best known in cognitive science for his multiple drafts (or “fame in the brain”) model of human consciousness, and to the secular community for his 2006 book Breaking the Spell. Author and co-author of two-dozen books, he’s the Austin B. Fletcher Professor of Philosophy, and Co-Director of the Center for Cognitive Studies at Tufts University, where he taught our very own Point of Inquiry host Lindsay Beyerstein.

Sabine Hossenfelder is a very popular science communicator who focuses largely on topics in physics. Although much of her content is effective and without issue, there is an undercurrent of anti-establishment rhetoric that has grown immensely as of late, and it is an enormous problem. Sabine is a not a charlatan like most of my other targets, and this is not a hit piece, but rather commentary on this aspect of her work and how it came to be. If you are a fan of hers, consider this perspective.

Metaphysics and the Matter with Things: Thinking with Iain McGilchrist was a collaborative conference put on by the Center for Process Studies (CPS) and the California Institute of Integral Studies (CIIS) in March of 2024. This three-day conference brought leading process thinkers across various disciplines, including physics, neuroscience, psychology, philosophy, and theology into critical dialogue with McGilchrist’s work in a collegial effort to assess, question, extend, and apply it. For more information on the conference and to purchase recordings, please visit https://ctr4process.org/mcgilchrist-conference/

Artificial consciousness is inevitable, says new study. Mathematical model unifies theories and paves the way for sentient robots.

In 1950, Alan Turing published a seminal paper on machine intelligence (which is available online ). Turing ponders whether machines can think. However, he pretty much immediately abandons this initial question as hopelessly metaphysical and replaces it with another question that can be approached scientifically: can a machine ever convince us that it’s thinking?

There have always been ghosts in the machine. Random segments of code, that have grouped together to form unexpected protocols. Unanticipated, these free radicals engender questions of free will, creativity, and even the nature of what we might call the soul. Why is it that when some robots are left in darkness, they will seek out the light? Why is it that when robots are stored in an empty space, they will group together, rather than stand alone? How do we explain this behavior? Random segments of code? Or is it something more? When does a perceptual schematic become consciousness? When does a difference engine become the search for truth? When does a personality simulation become the bitter mote… of a soul?

Once relegated to theory, a newly discovered quantum object could be used to create new devices that will outpace modern electronics.

Inside a hunk of a material called a semimetal, scientists have uncovered signatures of bizarre particles that sometimes move like they have no mass, but at other times move just like a very massive particle.

Mimicking high-level abstraction of the brain to achieve energy advantages is a fundamental issue in neuromorphic computing. Here, the authors fabricate an asynchronous chip and demonstrate a high-accuracy neuromorphic system with power consumption of 0.7mW.