deeplearning

One of the most important skills for cultivating a satisfying and high impact life is one we rarely discuss: the art of serious thinking. In this episode, Cal makes the case for serious thinking as an ability to specifically cultivate, then describes five specific practices you can put into place to launch a crash course in developing an effective life of the mind.

Below are the questions covered in today's episode (with their timestamps). Get your questions answered by Cal! Here’s the link: https://bit.ly/3U3sTvo

Video from today’s episode:  https://youtube.com/calnewportmedia

Deep Dive: How to Think [4:07]

- Does reading count as Deep Work? [38:50]
- How do I make sense of the topics I think about? [41:48]
- How should I manage boredom in a job without hurting my ability to focus? [45:12]
- How can I provide quick answers to management if I’m a slow thinker? [50:40]
- CALL: How should I structure my Deep Holiday? [56:44]

CASE STUDY: A successful Digital Detox allowing one to think in peace. [59:55]

CAL REACTS: Does collaboration make us less creative? [1:07:29]

Thanks to our Sponsors:

https://www.shopify.com/deep
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https://www.cozyearth.com (promo code: CAL)
https://www.mybodytutor.com

Thanks to Jesse Miller for production, Jay Kerstens for the intro music, Kieron Rees for slow productivity music, and Mark Miles for mastering.

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. And 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.

A special discussion episode, where we do not cover AI news but instead chat about our experiences teaching AI classes at Stanford with Abigail See, a graduate from the Stanford AI Lab and a good friend of ours.

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Music: Deliberate Thought, Inspired by Kevin MacLeod (incompetech.com)

Gary Hoover loves books. Among the nine companies he founded was the bookstore chain Bookstop, which was acquired by Barnes & Noble. He has a personal collection of 60,000 books, which he had to purchase an abandoned medical center to house. And he's the author of his own book, which is about books, called The Lifetime Learner's Guide to Reading and Learning.

Today on the show, Gary shares how his fascination with books was born in his youth, why the collection he amassed over the decades is almost entirely non-fiction, why he prefers physical books over ebooks, and why getting your hands on old books can be particularly beneficial in enhancing your knowledge of the world. From there we turn to Gary's method for digesting a book, which allows him to glean its most valuable nuggets in just thirty minutes, without having to read it cover to cover. We also talk about whether Gary takes notes on the books he reads, and how to incorporate more serendipity into the way you do your own reading and build your home library.

Check out the show notes at aom.is/hoover

In this interview with AI expert Pedro Domingos, you’ll learn about self-driving cars, where knowledge comes from, and the 5 schools of machine learning.

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