Theory and Practice

Throughout the fourth season of Theory and Practice, we explored emerging human-like artificial intelligence and robots. We asked if we could learn as much about ourselves as we do about the machines we use. The series has covered safety guardrails for AI, empathic AI communication, communication between minds and machines, robotic surgery, computers that smell, and using AI to understand human vision. The most recent episode with Google DeepMind's Dr. Clément Farabet illuminates how computers might demonstrate understanding and reasoning on par with humans. In the final episode, we reflect on investing in artificial intelligence's future with the leader of GV's Digital Investing Team, Dave Munichiello, who has a long-standing history with AI and robotics. Dave was an early technologist at Kiva Systems, purchased by Amazon and ultimately becoming Amazon Robotics. Over the past decade-plus at GV, Dave has been leading investments across two major categories: Platforms Empowering Developers (GitLab, Segment, Slack, RedPanda, etc) and Platforms Powering AI Systems (Determined, Modular, SambaNova, Snorkel AI, etc), along with others. Dave's first AI investment, Lattice (bought by Apple's Siri team) was seven years before the hype of generative AI. We asked, from a seasoned AI investor's perspective, where does AI hold the most promise? To answer this, Dave returns to the themes we've investigated over the last eight weeks — including AI trust and safety, which Google Health's Greg Corrado raised in the first episode. Together, we explore how AI will change how we work, the nature of jobs, and how an investing team with a culture focused on having more questions than answers is well positioned for AI's future.Dave rounds out the discussion with a picture of how artificial intelligence, with real-life use cases, will move research lab theory to real-world practice. He also walks us through his hopes for AI, including a world where humans and computers exist as co-pilots.Ultimately, Dave shares an optimistic and rational view of AI's future. “AI has the potential to democratize the very creation of technology," he reflects. "With AI-assistance, folks across the country will no longer need to rely on software programmers to solve everyday digital problems – they'll be able to create these tools themselves. That is incredibly exciting, and I'm honored to be a part of that journey."

In this season of Theory and Practice, we explore newly emerging human-like artificial intelligence and robots — and how we can learn as much about ourselves, as humans, as we do about the machines we use. As we near the end of Season 4, we explore whether decision-making and judgment are still the final preserve of humans.Our guest for Episode 7 is Dr. Clément Farabet, VP of Research at Google DeepMind. For the past 15 years, Dr. Farabet's work has been guided by a central mission: figuring out how to build AI systems that can learn on their own — and ultimately redefine how we write software. We discuss the conundrum in the Chinese Room Argument to explore whether computers can achieve artificial general intelligence. Dr. Farabet outlines four modules required for computers to demonstrate understanding. These modules include a predictive model of its environment that can create a representation of its world and an ability to store memories. He also points to the ability to perform reasoning about possible futures from its representation and memories. And finally, he explains how the ability to act in the world is key to illustrating understanding.Dr. Fabaret believes that we can build computers to become more human-like than most people may realize, but the overarching goal should be to build systems that improve human life.

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.

On Season 4 of Theory and Practice, Anthony Philippakis and Alex Wiltschko explore newly emerging human-like artificial intelligence and robots — and how we can learn as much about ourselves, as humans, as we do about the machines we use. The series has delved into many aspects of AI, from safety guardrails to empathic communication to robotic surgery and how computers can make decisions.In episode 5, we explore how machine learning helped create a map of odor and how that technology will train computers to smell. Anthony Philippakis visits Dr. Alex Wiltschko's lab at Osmo, where scientists are dedicated to digitizing our sense of smell.

In Season 4 of the Theory and Practice podcast, we've been investigating the powerful new world of AI applications. We've explored how to build safety guardrails into AI-driven healthcare, what the future holds for empathetic AI communication, and how humans can control computers with imperceptible movements of their hands.For episode 4, we turn to surgical robots with the help of Dr. Catherine Mohr, President of the Intuitive Foundation, who played an integral role in developing the DaVinci surgical robot system. Before we explore the limits of robotic-assisted surgery, we discuss Moravec's paradox: computers are good at things we find complicated, including complex calculations and handling large amounts of data, but not as good at perception and mobility tasks.This context explains why Dr. Mohr does not think that haptics, and the process of providing tactile feedback, is a breakthrough — humans have a very sophisticated tactile sense. She posits that we do not need to recapitulate evolution by having robots mimic human physicality. Instead, she asks, “What is the best technology I can use to solve that problem?” She believes a promising future for surgical robotics is to augment the surgeon's hands: finding the cellular edges of a cancerous tumor by lighting up a nest of cells at its margins or helping the surgeon grasp a bleeding artery when the field is obscured by blood.Further down the line, she believes we will be able to move away from extensive surgery apart from trauma and move to maintenance surgery. For example, routinely doing “precision excision,” where tumors in their earliest form can be detected and removed at the cellular level, and “precision installment” — adding regenerative cells before organs and joints are damaged irrevocably.

On Season 4 of Theory and Practice, Anthony Philippakis and Alex Wiltschko explore newly emerging human-like artificial intelligence and robots — and how we can learn as much about ourselves, as humans, as we do about the machines we use. The series will delve into many aspects of AI: from communication to robotic surgery and decision-making.In episode 3, we explore how humans will control computers in the future with Dr. Thomas Reardon. Dr. Reardon founded CTRL-Labs and is an early pioneer in exploring the relationship between humans and machines. Now at Meta's Reality Labs, Dr. Reardon continues his work on non-invasive neural interfaces that detect activity in the human nervous system. Dr. Reardon explains how these systems encourage co-adaptation between man and machine. This human-computer interaction is core to understanding how human-like AI is changing humanity. Alex also describes the complexity of haptics — how computers try to relay the depth of human senses. He explains why understanding touch is essential for the future of human-like robotics.

On Season 4 of the Theory and Practice podcast, GV's Anthony Philippakis and Osmo's Alex Wiltschko explore being human in the age of AI. Guests this season dive into areas including AI communication, robotic surgery, and decision-making.Episode 2 explores how machine learning evolved to where it is today. Anthony and Alex's guest is Dr. Claire Cui, a computer scientist from Google DeepMind. They discuss the underlying architecture of LLMs, how self-supervising algorithms work, and the technological developments that have driven innovation. How do we empower the next generation of LLMs with greater deduction skills and efficiency? We explore a future where introspection is added to LLMs, and Dr. Cui gives broader context to our current thinking about AI's vast potential.

On Season 4 of the Theory and Practice podcast, hosts Anthony Philippakis and Alex Wiltschko explore the many aspects of what it means to be human in the new era of artificial intelligence: from communication to robotic surgery and decision-making.In episode 1, Dr. Greg Corrado, Distinguished Scientist and Head of Health AI at Google Health, explains how to responsibly introduce AI into healthcare. AI has proven itself in detecting diabetic eye disease, managing the risk of cardiovascular disease, and even encoding medical knowledge to answer patient queries, among many new and exciting applications.Greg discusses safety concepts in AI: bias, robustness, transparency, explainability, and groundedness. He also discusses developing and maintaining datasets reflecting real-world patient realities and values. Following this conversation, Anthony and Alex discuss Brian Christian's book “The Most Human Human.”

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.

What is a thought? Some may think that question is quite abstract, but it has huge implications for science and computer design.If we cannot define a human thought, how can we know if a computer can think? Only then can true Artificial Intelligence be achieved.This week we speak to the “godfather of deep learning”, Professor Geoffrey Hinton, a cognitive psychologist and computer scientist. He is now an emeritus Professor at the University of Toronto, and an engineering fellow at Google.Our wide-ranging discussion reflects on Professor Hinton's journey into this field, his instrumental role in the deep learning revolution, and an analysis of when, if ever, computers might achieve the next level of intelligence.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.

Psychiatry is changing and will be unrecognizable in the next 10-20 years, given our new understanding about the role of brain circuits in the generation of emotions and behavior.This week we talk to Professor Karl Deisseroth, D.H. Chen Professor of Bioengineering and of Psychiatry and Behavioral Sciences at Stanford University and the Howard Hughes Medical Institute. We discuss his work on optogenetics and the insights it has given into the workings of the human brain.Professor Deisseroth also explains the potential for the future of psychiatry: including deep brain stimulation, transcranial magnetic stimulation, and the use of our smartphone and digital data, known as our “digital exhaust”. Will these methods become a regular part of psychiatric practice in the future?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.

Using machine learning to predict how a protein folds helps solve a riddle in biology. But it is just the start.These algorithms open up new opportunities to explore the physiological processes that have eluded research, adapt and create proteins for therapeutic purposes, and even power nano-molecular machines.This week we speak with Professor David Baker about the enormous scope for making new proteins and how that translates into practical uses to tackle diseases, such as Covid-19.They also discuss the “technological molecular design revolution” and how nanomachines could work like tiny vacuum cleaners to clear arteries from atherosclerosis or our brains from Alzheimer's amyloid plaques.David Baker also explains why none of this is possible without a sense of community in the lab.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 the last 20 years or so, many new cancer treatments have emerged that provide greater precision and targeting of cancer cells.Today, we have a better understanding of the genetic components of cancer.Through novel technology and cutting-edge science, we're now able to understand how the accumulation of molecular alterations in the genome leads to the coding of proteins that can promote uncontrolled cell division.New treatments are emerging at the genetic and molecular level, along with novel approaches to targeting the new microenvironment that cancers create.On this episode of Theory and Practice, we explore the future of cancer medicine, and there's no better leader to turn to for that discussion than Dr. Jay Bradner. Since 2016, he's been president of the Novartis Institutes for BioMedical Research, where he leads the discovery and development of life-changing therapies to benefit patients.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.

Gene editing is the process by which alterations are made to DNA. There are three major challenges: make precise edits at a chosen site, make edits that do not result in subsequent mutations, and have an editing process flexible enough to address the mutations which cause human disease. This week we talk to Professor David Liu of Harvard University's Department of Chemistry and Chemical Biology. They discuss the progress that has been made to overcome these challenges, following the development of the base editing and prime editing methods in his lab.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.

For the third season of Theory and Practice, we wanted to ask: what lies ahead for the intersection of life sciences and data sciences in the next ten years?In this episode, we explore the vastness of the "dark genome" and why "junk DNA" has been overlooked for so many decades.Our guest is Dr. Rosana Kapeller-Lieberman, A GV Fellow and the CEO of Rome Therapeutics with over 25 years' experience in science and therapeutics. Rosana discusses her team's scientific approach, and how they have tackled investigating the 60% of our genome that we previously thought was just filler, or repeatable DNA.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.

Julia Vitarello is the mother of Mila Makovec, and the Founder and CEO of Mila's Miracle Foundation.Episode links:Theory and Practice - Tim YuMila's Miracle FoundationThis Is Today photo journalMila's story (YouTube)

Aviv Regev is a computational biologist and Executive Vice President of Genentech Research and Early Development. She was professor at the Broad Institute of MIT and Harvard and at the Department of Biology of the Massachusetts Institute of Technology, as well as investigator at the Howard Hughes Medical Institute.

Dr. Amy Abernethy is an oncologist, specialist in palliative care medicine, researcher, previous Professor of Medicine at Duke University School of Medicine, previous Scientific and Medical Chief Officer of Flatiron Health, and previous Principal Deputy Commissioner of the FDA.

David Altshuler: Executive Vice President, Global Research and Chief Scientific Officer at Vertex Pharmaceuticals.

Dr. Timothy Yu is Attending Physician, Division of Genetics and Genomics, and head of the Yu lab at Boston Children's Hospital. He is also Associate Professor of Pediatrics at Harvard Medical School. He walks us through his experience running the first "N of 1" drug trial for a young patient with a devastating genetic mutation.

Dr. Krishna Yeshwant is Managing Partner at GV, and a practicing physician at Brigham and Women’s Hospital in Boston.

Theory and Practice speaks with Dr. Caroline Uhler, currently the Henry L. and Grace Doherty associate professor in EECS (Electrical Engineering & Computer Science) and IDSS (Institute for Data, Systems and Society) at MIT, and associate member of the Broad Institute where she is co-director of the Eric and Wendy Schmidt Center.

Theory and Practice speaks with Professor Jennifer Listgarten, Professor in UC Berkeley's Electrical Engineering and Computer Sciences Department (EECS) and the Center for Computational Biology, and Chan Zuckerberg investigator.Relevant links:- Jennifer Listgarten- 2018 Berkeley Faculty Profile - 2020: Seminar on Machine Learning- 2021 Interview for Berkeley Scientific Journal

Theory and Practice speaks with Professor Sir Rory Collins, Head of Nuffield Department of Population Health at Oxford University and BHF (British Heart Foundation) Professor of Medicine and Epidemiology. Professor Collins is also Principal Investigator and Chief Executive of the UK Biobank.Relevant links:- Sir Rory Collins- Oxford University- British Heart Foundation- UK Biobank

Dr. Anne Carpenter invented CellProfiler and designed a method for coloring and analyzing cells. She works at the Broad Institute as the Senior Director of the Imaging Platform and is an Institute Scientist.Additional links:Broad InstituteAnne CarpenterCellProfilerGVGoogle Research

One week until Theory and Practice returns! Join Anthony and Alex as they discuss cutting-edge health developments with leaders in biology and computer science.

The hosts interview a panel of distinguished guests, including life sciences entrepreneur and investor Alexis Borisy, Finale Doshi-Velez of Harvard University's John A. Paulson School of Engineering and Applied Sciences, and Pardis Sabeti of the Broad Institute of MIT and Harvard.

Zach Weinberg is the co-founder, president, and COO of Flatiron Health. He discusses his entrepreneurial journey and Flatiron Health's approach to accelerating cancer care and improving patient outcomes.

Cori Bargmann is the head of science at the Chan Zuckerberg Initiative. She is also the head of the Lulu and Anthony Wang Laboratory of Neural Circuits and Behavior and the Torsten N. Wiesel Professor at The Rockefeller University in New York. She joins the podcast to discuss advancing science on a larger scale.

Professor Daphne Koller is the CEO and founder of insitro. She joins the podcast to discuss how machine learning and biology can advance drug discovery and patient care.

David Sontag, Associate Professor of Electrical Engineering and Computer Science at MIT, explores how artificial intelligence can transform medicine, and discusses the importance of fairness in machine learning.Episode notes on research attribution: Steven Horng Yoni Halpern Rahul Krishnan Fredrik JohanssonUri ShalitIrene Chen

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

Greg Corrado, senior research scientist with Google AI, examines the impact of artificial intelligence and machine learning on medicine and delves into the future of biological neuroscience.

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.

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.

Jessica Mega, Chief Medical Officer at Verily, discusses her career path, the intersection of data science and healthcare, and how medical tools can augment positive health outcomes.

In this episode, Princeton University’s Barbara Englehardt reveals what she’s working on in epigenetics and exploratory data analysis, and examines the theoretical foundations for machine learning and how they are applied in practice. Barbara is currently on leave from Princeton University and is a principal scientist at Genomics Plc.

Theory and Practice explores the cutting edge of biology and computer science through conversations with leaders in the field. This week, your hosts Alex and Anthony introduce themselves and discuss the origins of the show.