Betsey Stevenson is a labor economist at the University of Michigan, and she was an economic adviser to President Obama. Betsey’s problem is this: How can we create a world where the benefits of AI are broadly shared?

Betsey draws on history – including how the invention of household appliances created a crisis of meaning for American women – to understand how we should respond to the challenge of AI. And she suggests policies to help spread the wealth AI could bring.

In this episode, Betsey explains:

• How Engels’ Pause serves as a warning for workers
• How 20th century women adapted to automation
• How AI has changed life for college students
• The argument for taxing AI firms and distributing the proceeds to the public

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Maps have gotten much better over the past few decades. But they're still mostly two dimensional, and they struggle to keep up with a world that is always changing. Brian McClendon is the Chief Technology Officer of Niantic Spatial, a spinout of the company that makes Pokémon Go. Brian's problem is this: How do you build a three-dimensional map of the world that both robots and humans can use to find their way?

In this episode, Brian explains:

• What he learned building Google Earth
• How Pokémon Go players helped build the foundation for robot navigation
• What it will take to teach AI to understand the physical world.
• Why GPS is so bad in cities
•  Why trees are such a big problem for digital mapmakers

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Dan Shipper is the co-founder and CEO of Every, a company that publishes newsletters about AI, develops AI-related software, and helps other companies use AI. Dan has two problems. One, how do you build a company where almost everybody has their own AI agent? And two, how do you use AI as a tool to improve your writing, rather than as a replacement for writing?

In this episode, Dan explains:

• Why managing agents will be a core skill of the future
• Why AI agents won’t replace you anytime soon
• How writers learn faster than AI models
• How to give AI the social skills to work in group settings
• How AI can help you better understand yourself

Check out Every at their website: https://every.to/

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The apples you can buy at the grocery store have gotten profoundly better over the past few decades. It’s a kind of everyday, hiding-in-plain sight innovation.  Kate Evans is an apple breeder and professor at Washington State University. Kate's problem is this: How do you invent a better apple?

With her team, Kate has in fact invented a new kind of apple called the Sunflare. It’s arriving in stores in a few years. She also helped to invent the Cosmic Crisp, which is out already.

In this episode, Kate explains:

• Why grocery-store apples have gotten so much better
• Why some of the most delicious apples never make it into stores
• Why it takes decades to invent a new kind of apple
• How much more we have to learn about apple genetics
• How the apple industry is adapting to climate change

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Rob Meyerson is the co-founder and CEO of Interlune. Rob's problem is this: How do you help build an economy on the moon? Eventually, Rob hopes Interlune will help build a moon base. For now, he is focused on bringing a gas called helium-3 back from the moon to sell on earth.

Earlier in his career, Rob was the president of Blue Origin, the rocket company founded by Jeff Bezos.

In this episode, Rob explains:

•  Why reusable rockets are only the first step for going back to the moon
• What it's going to take to actually manufacture things in space
• How to build a business by sifting through moon dirt
• How nuclear fusion and quantum computing could rely on mining the moon

Connect with us:

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Aaron Edsinger left his job as director of robotics at Google to start a company called Hello Robot. Aaron’s problem is this: How do you build an affordable robot that people can use to solve real problems at home? The result is a robot that looks nothing like a person. In fact, it’s closer to a Roomba with an arm.

In this episode, Aaron explains:

•  Why home robots have barely progressed since the Roomba
• Why simpler robots can be more useful than complex humanoids
•  Why the physical world is so much harder for AI than language
• How robot safety is fundamentally a physics problem

Connect with us:

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Ben Christensen is the co-founder and CEO of Cambium, the largest seller of salvaged wood in America. Ben's problem is this: How can we turn the trees that are falling to the ground all around us, into usable wood?

In this episode, Ben explains:

• Why so much wood goes unused
• Why Cambium created demand before building the supply chain
• How building a data layer across the fragmented lumber industry reduces waste
• Why salvaged wood can compete on price with conventional lumber
• The best mantra to use 80 miles into an ultramarathon

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Investors are pouring billions of dollars into nuclear fusion companies. The dream: transform human civilization (and power AI data centers) by providing cheap, abundant energy. But nobody’s figured out how to make it work yet.

What will it take to make fusion work at scale – and how will the world be different if it does? To answer this question, Jacob recently hosted a conversation at SXSW between Greg Piefer of SHINE Technologies, Melanie Windridge of Fusion Energy Insights, and Luke Ward of investment firm Baillie Gifford.

In this episode, the guests explain:

• The incredible promise of fusion
• What it will take to realize that promise
• How the AI boom and the demand for power is shaping the fusion industry
• Why having a ton of money flowing into the field is not necessarily a good thing

Connect with us:

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