What's Your Problem?

Throughout the next few weeks, every Monday we'll be sharing some of our favorite episodes from Jacob's other show Business History. We hope you enjoy them and if you want to hear more, subscriber to Business History on Apple, Spotify or wherever you get your podcasts.

With the news of Warren Buffett stepping down as chairman of Berkshire Hathaway, we are revisiting an episode from our two-part series on Buffet.

Warren Buffett rose from obscurity to become the richest person in the world - and he did it in a unique way. As a boy in Omaha he collected information obsessively - writing down car license numbers and hoarding bottle caps. As a young man, Buffett turned his focus on scouring business accounts to find companies that had hidden value no one else could spot.

We tell the story of young Warren Buffett as he quietly worked building up the expertise and accumulating the wealth that would allow him to become the most famous investor of our age.

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Circadian rhythm isn’t just controlled by your brain. Every cell in your body runs on a 24-hour cycle, including your muscle cells.

Karyn Esser is the chair of the department of physiology and aging at the University of Florida, and she’s a leading expert on circadian rhythm in muscle cells. Karyn's problem is this: How does the circadian rhythm in muscle cells change as we age, and how does exercise help keep our system in sync?

In this episode, Karyn explains:

• How every cell in your body has a clock in it
• How muscle clocks prepare cells for work and schedule recovery during rest
• How age affects these clocks’ ability to regulate effectively
• Why exercise can improve clock function
• Why jet lag and late-night eating can put your body clocks out of sync

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Throughout the next few weeks, every Monday we'll be sharing some of our favorite episodes from Jacob's other show Business History. We hope you enjoy them and if you want to hear more, subscriber to Business History on Apple, Spotify or wherever you get your podcasts.

William Shockley was an electronics genius - he even won a Nobel Prize - but he was an awful boss. Shockley was a cruel, paranoid micromanager. And this annoyed the staff of brilliant young engineers he'd assembled in a quiet town in Northern California. In fact, they quit and set up a company of their own inventing silicon chips.

Robert Noyce, Gordon Moore and the rest of "The Traitorous Eight" transformed computing, but also blazed a trail for the tech founders who would flock to Silicon Valley and change the world. Members of "The Traitorous Eight" set up Intel and AMD, while also funding businesses such as Google and Slack.

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Note: Today’s show is sponsored by PayPal.

Kartik Hosanagar is a professor at the Wharton School. The problems he studies include: What will it take for people to trust AI agents to buy stuff for them? And how should businesses prepare for a world where their customers include AI agents?

In this episode, Kartik explains:

• Why trust in agentic shopping will arrive category by category, not all at once
• How a single old Reddit post erased a thriving brand from ChatGPT’s recommendations
• Why someone needs to take on the liability risk when purchases go wrong
• How treating AI as just another sales channel is the mistake the movie studios made with Netflix
• How to get a language model to pay attention to your brand

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Jason Ballard is the co-founder and CEO of ICON. Jason's problem is this: Can you use 3-D printing to build houses that are cheaper, better and more interesting than the houses we build now?

In this episode, Jason explains:

• Why construction methods are so slow to change
• How 3D printing opens up new designs for houses
• How building on the Moon shaped the way Icon builds on Earth
• The challenge of scaling to printing thousands of houses

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Celebrated novelists, countless students and at least one billionaire have recently been accused of using AI in their writing. The most commonly cited AI detector in these cases is called Pangram.

Max Spero is the co-founder and CEO of Pangram. His problem is this: Can you build tools that reliably detect AI-generated text and images? And a few years from now, will anybody care?

In this episode, Max explains:

• Why AI prose so often sounds the same
• How often Pangram makes mistakes
• How detectors like Pangram compete with humanizer tools
• Why the big AI companies may not be interested in detection
• The shifting norms around AI-generated writing

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I'm here with a preview of Blockers, a new audiobook from Michael Lewis, the author of Liars Poker, Moneyball, The Big Short and more. In Blockers, Lewis tells the story of a handful of people who dedicated their careers to public service—until the Department of Government Efficiency decided they were a problem. These were people who believed they had a calling—people who kept American's sensitive tax data out of the wrong hands, made sure that politicians and civil servants played by the rules, and figured out how to stop wildfires from destroying suburban neighborhoods—and then discovered they were no longer wanted.

Here's an excerpt from the audiobook. You can buy the audiobook exclusively at http://blockers.fm/.

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We’ve all heard that nothing ever gets deleted from the internet. Luke Arrigoni says that just isn’t true. His company deletes thousands of deepfakes every day.

Luke is the founder and CEO of Loti, and his problem is this: How do you turn the Internet into a place where people have more control over their name, image and likeness?

Tens of thousands of famous people pay Loti to scour the internet and take down deepfakes and unapproved endorsements. But in Luke's telling, this is just the beginning. The company will soon allow celebrities to license their likeness for use in AI videos, and it also plans to start offering its services to ordinary people.

In this episode, Luke explains:

• The harm that online deepfakes and impersonations can cause
• How Loti automates tens of thousands of takedowns per day
• Why the law may soon make it easier to fight deepfakes
• Why celebrities are beginning to license their likenesses to AI platforms
• AI’s role in the future of human creativity

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Before 1450, books were written out by hand. It was slow and expensive. But Johannes Gutenberg borrowed a ton of money to create a printing press that could crank out Bibles and pamphlets and documents in huge numbers. Science, politics and philosophy were all up-ended.

For example, the Catholic Church seized on the invention to sell special certificates absolving people of their sins – a move that made money, but caused a permanent schism in Christianity.

And Gutenberg too found himself in trouble – when a financier sued the inventor to reclaim his loan, plus interest.

Enjoy this episode from Business History, another Pushkin podcast.

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Everybody’s worried about the risks of AI. So we called up one of the most insightful writers we know on the subject: Zvi Mowshowitz. Zvi writes about AI and AI risks at his substack, Don’t Worry About the Vase. Zvi’s problem is this: How do we prevent artificial intelligence from killing everyone?

In this episode, Zvi explains:

• Why it’s often useful to anthropomorphize AI
• What this summer’s Hugging Face attack tells us about the nature of AI
• What increasing AI capability means for cybersecurity risk
• Whether and when we should pause AI development
• Why powerful pen-weight models may remove the last reliable points of control

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On this bonus episode of What’s Your Problem, Jacob talks to Christine Chase, a Vice President, Financial Consultant at Fidelity Investments. Christine’s problem is this: How do you help clients build a plan to achieve their financial goals? Today’s show is sponsored by Fidelity Investments.

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The fish we eat usually die slowly, suffocating after they’re pulled out of the water. Saif Khawaja is the co-founder and CEO of a company called Shinkei. Saif's problem is this: Can he build a machine to efficiently kill fish in a way that is more humane?

In this episode, Saif explains:

• How he came to believe that our current fishing practices are inhumane
• How he adapted the Japanese technique of ikijime for use at scale
• Why Shinkei’s process results in better texture and longer shelf life than commodity fish.
• Why Shinkei is doing its own technology development, fish processing, and consumer branding.

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Catherine Nakalembe is an assistant professor at the University of Maryland and the head of the Africa program at NASA Harvest, which uses satellite images to track agriculture around the world. Catherine’s problem is this: How do you predict when a famine is coming – and how do you convince leaders to act in time?

In this episode, Catherine explains:

• How satellite data can predict crop failure months in advance
• Why phots can convince decision-makers faster than maps or statistics
• Why imaging systems developed for US farmland often don’t work in Africa
• Why a half-page memo moves food trucks faster than a scientific paper

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When Dr. Lara Jehi began treating epilepsy patients in the 2000s, critical surgical decisions were driven more by clinician intuition and expertise than data. Today, she is a leader of IBM and Cleveland Clinic’s Discovery Accelerator, using advanced AI and quantum computing to transform how researchers analyze data, simulate molecules, accelerate drug discovery, and develop more precise treatments. Malcolm Gladwell talks with Dr. Jehi about how quantum computing is changing biomedical research, and what these breakthroughs could mean for the future of healthcare and life sciences.

This is a paid advertisement from IBM. The conversations on this podcast don't necessarily represent IBM's positions, strategies or opinions.

Visit us at https://www.ibm.com/think/podcasts/smart-talks

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Nir Barzilai is a physician and a researcher at the Albert Einstein College of Medicine in New York, where he runs the Institute for Geroscience. Nir’s problem is this: How can we use lifestyle changes and drugs to slow the process of aging?

In this episode, Nir explains:

• The search for biological markers of aging
• The existing drugs that might reduce the risk of diseases associated with aging
• The four key lifestyle factors that every researcher in the field agrees on
• What he learned by studying the genes of people who lived to 100
• What “geroscience” means, and why it doesn’t have a Wikipedia page

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Helen Pearson is the author of the book “Beyond Belief: How Evidence Shows What Really Works.” Helen's problem is this: How do you get people to make important decisions based on high-quality evidence, instead of on hunches or habits?

In this episode, Helen explains:

• How a doctor's fatal mistake sparked the evidence-based medicine movement
• Why management is so resistant to evidence-based practices
• How systematic reviews changed the way she works as a science journalist
• Why global trust in science remains high – outside the US
• What a randomized trial of pint glasses revealed about preventing violent injuries.

Check out Helen’s book here.

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In 2016, Geoffrey Hinton, one of the inventors of modern AI, predicted that AI would replace radiologists within years. Ten years later, we have a shortage of radiologists. AI has yet to revolutionize the field. What happened, and what does the story of AI and radiology tell us about AI and the future of work?

Saurabh Jha is a radiologist at the University of Pennsylvania. He's written about how he uses AI in his practice, and why radiologists have been slow to adopt AI. Saurabh has also traveled to India and Nepal to understand the very different ways AI is being adopted for radiology in the developing world.

In this episode, Saurabh explains:

• Why AI still hasn't made radiologists faster or more productive
• The risks of novice radiologists using AI versus the benefits to experts
• Why a successful AI model would need to be nearly perfect
• How AI is being used to spot tuberculosis in India
• Why diagnosing a normal scan is harder than diagnosing disease

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After spending decades as marginal players in the global auto industry, Chinese carmakers have become the world’s biggest exporters of cars. Chinese cars are some of the best cars on the planet, and they’re available almost everywhere – except in the US.

Michael Dunne is the CEO of Dunne Insights, a company that consults on the future of cars. Michael has been working with the Chinese auto industry since 1990. I talked with Michael about how China did it. The problem we discussed was: How can the United States catch up with the Chinese auto industry?

In this episode, Michael explains:

• How China went from making terrible cars in 1990 to dominating global exports today
• Why China bet big on electric vehicles when nobody wanted them
• How Tesla's arrival in China revolutionized their EV industry
• Why losing the car industry would be a national security problem for the US
• Why the future of a successful American auto industry is on the West Coast

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Phages are viruses that attack bacteria. People have been using phages to treat infections for over a hundred years, but in most cases they just don't work as well as antibiotics.

Paul Garofolo is the co-founder and CEO of Locus Biosciences. His problem is this: How do you genetically engineer phages to be more effective at curing disease?

In this episode, Paul explains:

• Why wild phages never completely wipe out a bacterial infection
• How to engineer phages with CRISPR to kill bacteria more effectively
• The clinical trial testing phage therapy for chronic, recurrent UTIs
• Why persistent bacteria may contribute to autoimmune conditions like Crohn's disease
• How to use robots and AI to create phage cocktails from wastewater

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David Autor is a labor economist at MIT. He has written about how the arrival of personal computers increased inequality among American workers. But when it comes to AI, David thinks there could be a different outcome.

Read David’s article about AI in Noema Magazine.

In this episode, David explains:

• How computers increased the wage gap between college and non-college educated workers
• Why AI’s ability to supplement expertise may open up expert fields to more people
• How AI could make healthcare and legal services cheaper
• What fields will still experience rapid devaluation of skills due to AI
• The “no regrets” policies that the US could enact to help ease the impact of AI

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