Theory and Practice

Season 4 of our Theory and Practice podcast investigates the powerful new world of AI applications and what it means to be human in the age of human-like artificial intelligence. Episode 6 explores what happens when AI is explicitly used to understand humans.

In this episode, we're joined by James DiCarlo, the Peter de Florez Professor of Neuroscience at Massachusetts Institute of Technology and Director of the MIT Quest for Intelligence. Trained in biomedical engineering and medicine, Professor DiCarlo brings a technical mindset to understanding the machine-like processes in human brains. His focus is on the machinery that enables us to see.

"Anything that our brain achieves is because there's a machine in there. It's not magic; there's some kind of machine running. So that means there is some machine that could emulate what we do. And our job is to figure out the details of that machine. So the problem is someday tractable. It's just a question of when."

Professor DiCarlo unpacks how well convolutional neural networks (CNNs), a form of deep learning, mimic the human brain. These networks excel at finding patterns in images to recognize objects. One key difference with humans is that our vision feeds information into different areas of the brain and receives feedback. Professor DiCarlo argues that CNNs help him and his team understand how our brains gather vast amounts of data from a limited field of vision in a millisecond glimpse.

Alex and Anthony also discuss the potential clinical applications of machine learning — from using an ECG to determine a person's biological age to understanding a person's cardiovascular health from retina images.

Eric Lander, president and founding director of the Broad Institute of MIT and Harvard, joins the show to discuss human genetics and computational biology.

Former Google CEO Eric Schmidt talks about the foundations of computer science, reflects on the role of data in healthcare, and discusses his views on the intersection of technology and life sciences as the next frontier.

For millennia, humans have believed that aging is inevitable. Yet thirty years ago, the work of Professor Cynthia Kenyon and her colleagues showed that a single gene mutation in a worm doubled its lifespan and postponed the diseases of aging. Recent work on the naked mole rat, a mammal like us, has shown that risk of death need not increase with age.

In the final episode of this season of Theory and Practice, we explore the genetic, cellular, and molecular basis of aging with Professor Kenyon and ask what harnessing this knowledge means for the future of healthcare.

Theory and Practice is a presentation of GV and Google AI.

This season we'll dive deep into the languages of life through explorations of the "dark genome", genome editing, protein folding, the future of aging, and more.

Hosted by Anthony Philippakis (Venture Partner at GV) and Alex Wiltschko (Staff Research Scientist with Google AI), Theory and Practice opens the doors to the cutting edge of biology and computer science through conversations with leaders in the field.

In this episode, Sir Peter Donnelly, CEO of Genomics Plc and Professor of Statistical Science at the University of Oxford, explores the relationship between genetic variation and complex human diseases and talks about his career at the intersection of statistics and genetics.