Machine Learning Street Talk (MLST)

Connor Leahy, a prominent AI skeptic, pairs up with Beff Jezos, the founder of the e/acc movement, to debate technology's future. They tackle complex topics, including the balance between rapid technological advancement and necessary regulation. Leahy raises concerns about the dangers of unchecked innovation, while Jezos emphasizes growth and adaptability. Their discussion delves into the existential risks of AI, the ethics of AGI prioritizing well-being, and the intricate relationship between cultural ideologies and technological progress.

Mahault Albarracin, Director of Product for R&D at VERSES and a PhD student, dives deep into the realms of consciousness and cognition. She discusses philosophical concepts like panpsychism and computationalism, critiquing the Integrated Information Theory. Albarracin shares insights on distinguishing legitimate science from pseudoscience, emphasizing the importance of evidence. The conversation also explores self-awareness in AI and the significance of language and communication in cognitive processes, illustrating how these elements shape our understanding of intelligence.

William Beauchamp, founder of Chai Research and Seamless Capital, dives into the world of conversational AI and startup growth. He shares his journey from algorithmic trading to launching a successful AI platform. Beauchamp discusses the distinction between AI as search engines versus reasoning engines, highlighting key advancements and limitations. He elaborates on the importance of talent and innovation in scaling startups and explores the intersection of creativity and risk in developing language models, emphasizing opportunities for smaller teams to thrive in the AI landscape.

Join Professor Karl Friston, renowned for his work in neuroscience, and Oxford Ph.D. candidate Riddhi J. Pitliya as they dive into the concept of agency in cognitive science. They explore how agency emerges from interactions within complex systems and the role of language in shaping cognition. Discussion unfolds around the implications of digital intelligence, the intricacies of depression, and the challenges of perception in an AI-dominated world. Prepare for a thought-provoking journey into the intersection of mind, behavior, and technology!

Simon Prince, a Professor at the University of Bath and author of 'Understanding Deep Learning', dives into the fascinating intricacies of deep learning. He discusses the surprising efficiency of deep learning models and the role of activation functions and architecture in their success. Notably, he challenges misconceptions surrounding overparameterization and the manifold hypothesis. The conversation also touches on ethical considerations in AI, the complexities of human cognition versus AI behavior, and the transformative impact of AlexNet on computer vision.

Bert de Vries, a professor at Eindhoven University, shares his expertise on intelligent autonomous agents. He discusses the principle of least action, its universal implications, and how it relates to optimizing energy in systems. Bert delves into active inference's role in ecosystems and engineering, particularly in adaptive technologies like hearing aids. He highlights the importance of probabilistic inference for the future of intelligence and explores challenges of implementing these concepts in real-world applications, emphasizing adaptability and innovation.

Lance Da Costa, a PhD candidate at Imperial College London, dives into the fascinating intersection of cognitive systems and AI. He discusses his work on the free energy principle, arguing that all intelligent agents minimize free energy for perception and decision-making. The conversation covers the advantages of active inference over traditional AI methods, highlighting its potential for safety and explainability. Lance also examines the challenges of structured learning and the role of Bayesian model reduction in adapting agents to changing environments.

In this special conversation, Stephen Wolfram, a celebrated computer scientist known for the Wolfram Physics Project, and Carl Friston, a pioneering neuroscientist behind the Free Energy Principle, tackle profound questions about existence. They explore what defines an observer and agency in both natural and artificial worlds. Topics include how observers shape their perceptions, the intricacies of agency in AI, and the philosophical implications of predictability versus unpredictability in our universe. Their combined insights push the boundaries of understanding agency, consciousness, and reality.

Dr. Jeff Beck, a computational neuroscientist, dives into the fascinating world of probabilistic reasoning in both humans and animals. He discusses the Bayesian brain hypothesis and its impact on understanding decision-making under uncertainty. Active inference takes center stage as Beck explains how agents interact with their environments. The conversation also explores the philosophy behind consciousness, the integration of cognition in ecosystems, and innovations in Bayesian multi-agent systems. Expect a thought-provoking journey blending science and philosophy!

Prof. Melanie Mitchell, Davis Professor of Complexity at the Santa Fe Institute, dives into the murky waters of AI understanding. She argues that current benchmarks are inadequate, as machines often replicate human tasks without true comprehension. Mitchell highlights the limitations of large language models, noting their lack of common sense despite impressive statistical capabilities. She emphasizes the need for evolving evaluation methods and suggests a deeper, context-specific look at intelligence, advocating for more rigorous testing to reflect genuine understanding.