Anil Ananthaswamy

David Suh, a portrait photographer known for boosting confidence in front of the camera, discusses the transformative power of photography in fostering authenticity and self-acceptance. Dolly Chugh, a social psychologist, delves into 'bounded ethicality,' revealing how moral identity shapes our perceptions. Journalist Elise Hu explores the global influence of Korean beauty standards on self-image, while science writer Anil Ananthaswamy examines the complex neuroscience behind self-identity, blending psychological insights with cultural narratives.

Anil Ananthaswamy, an award-winning science writer and author of "Why Machines Learn," dives into the intriguing mathematics behind machine learning. He discusses the vital role of linear algebra and calculus in modern AI, tracing its historical roots. Ananthaswamy unpacks the bias-variance tradeoff, the k-nearest neighbors algorithm, and the complexities of human reasoning versus machine learning. He also touches on emergent behaviors in language models and the implications of AI in understanding identity and consciousness, advocating for a deeper societal engagement with these technologies.

In a thought-provoking discussion, science writer Anil Ananthaswamy delves into the intricate nature of identity. He explores how our sense of self can be altered by conditions like schizophrenia and Alzheimer's, inviting listeners to reconsider what makes them who they are. Anil challenges conventional views on personal identity and highlights the empathy required for those experiencing shifts in self. His insights encourage a deeper understanding of the constructed nature of the self, ultimately aiming for personal growth and a more compassionate world.

Anil Ananthaswamy, an award-winning science writer and author, delves into the intricate mathematics behind modern AI. He reveals how machine learning influences critical decisions in our lives, powered by concepts as old as linear algebra. Ananthaswamy explores the journey from simple algorithms to complex neural networks, diving into Hebbian learning and the evolution of generative AI. He also ponders the connection between human cognition and AI, emphasizing the need to grasp the math that underlies these advancements for safe and effective use.

Anil Ananthaswamy, author of "Why Machines Learn: The Elegant Maths Behind Modern AI", dives into the recent Nobel Prize awarded to John Hopfield and Geoffrey Hinton for their pioneering work in machine learning. He explains their foundational contributions and the surprising intersection of AI and physics. The conversation also touches on Hinton's warnings about AI's potential risks and the growing need for regulation, while exploring the exciting role of Boltzmann machines in generative AI and their connection to physical principles.