1 hr 28 min

A.I. Could Solve Some of Humanity’s Hardest Problems. It Already Has‪.‬ The Ezra Klein Show

    • Society & Culture

Since the release of ChatGPT, huge amounts of attention and funding have been directed toward chatbots. These A.I. systems are trained on copious amounts of human-generated data and designed to predict the next word in a given sentence. They are hilarious and eerie and at times dangerous.

But what if, instead of building A.I. systems that mimic humans, we built those systems to solve some of the most vexing problems facing humanity?

In 2020, Google DeepMind unveiled AlphaFold, an A.I. system that uses deep learning to solve one of the most important challenges in all of biology: the so-called protein-folding problem. The ability to predict the shape of proteins is essential for addressing numerous scientific challenges, from vaccine and drug development to curing genetic diseases. But in the 50-plus years since the protein-folding problem had been discovered, scientists had made frustratingly little progress.

Enter AlphaFold. By 2022, the system had identified 200 million protein shapes, nearly all the proteins known to humans. DeepMind is also building similar systems to accelerate efforts at nuclear fusion and has spun off Isomorphic Labs, a company developing A.I. tools for drug discovery.

Demis Hassabis is the chief executive of Google DeepMind and the leading architect behind AlphaFold. So I asked him on the show to talk me through how AlphaFold actually works, the kinds of problems similar systems could solve and what an alternative pathway for A.I. development could look like.

Mentioned:

“The Curse of Recursion” by Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, Ross Anderson

“DeepMind’s CEO Helped Take AI Mainstream. Now He’s Urging Caution” by Billy Perrigo

Book Recommendations:

The Fabric of Reality by David Deutsch

Permutation City by Greg Egan

Consider Phlebas by Iain M. Banks

Listen to this podcast in New York Times Audio, our new iOS app for news subscribers. Download now at nytimes.com/audioapp

Thoughts? Guest suggestions? Email us at ezrakleinshow@nytimes.com.

You can find transcripts (posted midday) and more episodes of “The Ezra Klein Show” at nytimes.com/ezra-klein-podcast, and you can find Ezra on Twitter @ezraklein. Book recommendations from all our guests are listed at https://www.nytimes.com/article/ezra-klein-show-book-recs.

This episode of “The Ezra Klein Show” was produced by Rogé Karma. Fact checking by Michelle Harris. Fact checking by Michelle Harris with Rollin Hu. Our senior engineer is Jeff Geld. The show’s production team also includes Emefa Agawu, Annie Galvin and Kristin Lin. Original music by Isaac Jones. Audience strategy by Kristina Samulewski and Shannon Busta. The executive producer of New York Times Opinion Audio is Annie-Rose Strasser. Special thanks to Sonia Herrero.

Since the release of ChatGPT, huge amounts of attention and funding have been directed toward chatbots. These A.I. systems are trained on copious amounts of human-generated data and designed to predict the next word in a given sentence. They are hilarious and eerie and at times dangerous.

But what if, instead of building A.I. systems that mimic humans, we built those systems to solve some of the most vexing problems facing humanity?

In 2020, Google DeepMind unveiled AlphaFold, an A.I. system that uses deep learning to solve one of the most important challenges in all of biology: the so-called protein-folding problem. The ability to predict the shape of proteins is essential for addressing numerous scientific challenges, from vaccine and drug development to curing genetic diseases. But in the 50-plus years since the protein-folding problem had been discovered, scientists had made frustratingly little progress.

Enter AlphaFold. By 2022, the system had identified 200 million protein shapes, nearly all the proteins known to humans. DeepMind is also building similar systems to accelerate efforts at nuclear fusion and has spun off Isomorphic Labs, a company developing A.I. tools for drug discovery.

Demis Hassabis is the chief executive of Google DeepMind and the leading architect behind AlphaFold. So I asked him on the show to talk me through how AlphaFold actually works, the kinds of problems similar systems could solve and what an alternative pathway for A.I. development could look like.

Mentioned:

“The Curse of Recursion” by Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, Ross Anderson

“DeepMind’s CEO Helped Take AI Mainstream. Now He’s Urging Caution” by Billy Perrigo

Book Recommendations:

The Fabric of Reality by David Deutsch

Permutation City by Greg Egan

Consider Phlebas by Iain M. Banks

Listen to this podcast in New York Times Audio, our new iOS app for news subscribers. Download now at nytimes.com/audioapp

Thoughts? Guest suggestions? Email us at ezrakleinshow@nytimes.com.

You can find transcripts (posted midday) and more episodes of “The Ezra Klein Show” at nytimes.com/ezra-klein-podcast, and you can find Ezra on Twitter @ezraklein. Book recommendations from all our guests are listed at https://www.nytimes.com/article/ezra-klein-show-book-recs.

This episode of “The Ezra Klein Show” was produced by Rogé Karma. Fact checking by Michelle Harris. Fact checking by Michelle Harris with Rollin Hu. Our senior engineer is Jeff Geld. The show’s production team also includes Emefa Agawu, Annie Galvin and Kristin Lin. Original music by Isaac Jones. Audience strategy by Kristina Samulewski and Shannon Busta. The executive producer of New York Times Opinion Audio is Annie-Rose Strasser. Special thanks to Sonia Herrero.

1 hr 28 min

Top Podcasts In Society & Culture

Stuff You Should Know
iHeartPodcasts
Fail Better with David Duchovny
Lemonada Media
This American Life
This American Life
We Can Do Hard Things
Glennon Doyle and Audacy
Shawn Ryan Show
Shawn Ryan | Cumulus Podcast Network
The Ezra Klein Show
New York Times Opinion

More by The New York Times

The Daily
The New York Times
The Ezra Klein Show
New York Times Opinion
Hard Fork
The New York Times
Modern Love
The New York Times
Matter of Opinion
New York Times Opinion
The Run-Up
The New York Times