The last time the World Cup came to the US was 1994. Before then, the World Cup was an enormously popular event with surprisingly limited commercial significance; the 1990 tournament in Italy, for instance, lost money for broadcasters. But that all changed in 1994, when American companies sought to make their mark in the form of advertisements and sponsorships: firms like McDonalds, Mastercard, and General Motors saw the potential to reach a global audience through one of the world's most watched sports events. Today, we speak with Joey D'Urso — a freelance sports journalist and author of the recent book More Than A Shirt: How Football Shirts Explain Global Politics, Money and Power — about the 1994 World Cup and this year's competition, which is being held jointly, by the US, Canada, and Mexico. We also talk about other surprising stories of corporate and geopolitical influence in the world of football.

Read more:
Unilever, Pepsi Tap Celebrities, Players During World Cup
Mexico’s Sheinbaum Invites Merlín the Duck to National Palace Amid Soccer Craze

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China's AI industry has changed a lot since DeepSeek released its cheap frontier model last year, and briefly sent US tech stocks falling. After being locked out of the most advanced chips, Chinese companies are now allowed to buy some Nvidia H200s. In fact, many of the big Chinese tech companies — like Baidu — are making a push to become full-stack players, with their own chips, models, and cloud infrastructure. Today's guest is Grace Shao, an independent AI researcher and the author of the AI Proem Substack. She's a bit of an insider when it comes to China's AI industry, and when we were in Hong Kong we spoke with her about the latest in open-source models, the competition among Chinese frontier labs, DeepSeek's place in an increasingly crowded Chinese AI market, China's manufacturing edge, where bottlenecks exist right now (spoiler: it isn't data centers), if Chinese grandmas are actually using OpenClaw, and finally, of course, AI psychosis.

Read More:
China AI Lab’s 170% Stock Surge Cements Winner-Loser Pair Trade
China Plans Mechanism to Evaluate AI Impacts on Job Market

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We closed out our New York live show on May 28 with a panel that featured three of our favorite Substackers: James van Geelen of Citrini Research, Sam Ro, founder of The TKer, and journalist Jasmine Sun. They've all been Odd Lots guests before, and we wanted to get them together to discuss how journalists and analysts are supposed to cover this incredibly strange and highly pressurized moment in markets. Not only has AI basically infected every corner of the world, the media included, but there's just so much news that it's sometimes hard to figure out what the focus should be. But James, Sam, and Jasmine have all found their own niches, and cover AI in a really unique way. This panel discussion debates how the media has covered fears over the AI bubble and the possibility of mass job loss, if people in Silicon Valley are scared about the future of society, if AI can really mimic a writer's voice and personality, and (if they can) how writers can hedge against that future.

Read more:
Amazon in Talks to Sell Custom AI Chips in Bid to Undercut Nvidia
AI Company Dream Triples Value to $3 Billion in Funding Round

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There’s a lot to unpack with AI right now — everything from its potential impacts on the labor market and society to more extreme questions about existential risk. Anthropic, which builds frontier models like Mythos, Fable, and Claude, is actively grappling with these issues, including whether governments should limit AI development. Just last week, the Trump administration forced Anthropic to block foreign access to its two leading models. In this episode, we speak with Jack Clark (co-founder and head of public benefit) and Peter McCrory (head economist) about how Anthropic approaches safety and economic risks. We talk about its preparations for recursive self-improvement, the engineers it's hiring now, and why Jack left Bloomberg to enter the early AI industry.

Read more:
Anthropic Lays Out Vision for How to Bolster AI Models’ Safety
Microsoft Makes Big AI Inroads in China by Selling OpenAI Models

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Jeremy Grantham, co-founder and long-term strategist of GMO, has a long history of calling bubbles. As he recounts in his new memoir, The Making of a Permabear: The Perils of Long-Term Investing in a Short-Term World, that includes spotting the dot-com bubble of the early 2000s, which some people see as analogous to the current excitement over AI. And when it comes to today's market, there are a lot of signs of frothiness you could point to. In this episode, we speak to Grantham about how he sees markets right now, including a watershed change for Big Tech stocks, the signs he watches out for to spot when a bubble might burst, and what really keeps him up at night.

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An interim deal to reopen the Strait of Hormuz offers relief, but Asia’s economic woes are far from over. Beyond the chokepoint, the conflict has forced long-lasting shifts in Asia’s food and energy flows.

On today’s Big Take Asia podcast, Oanh Ha joins Odd Lots co-hosts Tracy Alloway and Joe Weisenthal to discuss why Asia is reeling from the conflict and what the “new normal” looks like for global supply chains.

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When we spoke to DRW's Don Wilson last year, he talked about building out a GPU market that might be bigger than oil. Now, a year later, he is working with Carmen Li to do just that. Li is the CEO of two companies — Silicon Data and Compute Exchange (where she works alongside Wilson). The former company is building the index for GPU pricing while the latter is a spot marketplace for GPU procurement. Today's episode — recorded at our live show at City Winery in New York — gets into how Li is building a whole new market for GPUs at her two companies. We talk about the challenge of standardizing compute, GPU price volatility, if used GPUs are like used cars, what goes into constructing a GPU index, and what it means to win the GPU lottery.

Read more:
Jane Street Plans New Data Center as Computing Power Runs Scarce
SpaceX Inks $30 Billion Computing Power Deal With Google

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Anjney Midha wrote the first check to Anthropic. He teaches a viral course at Stanford on how AI works. And he was, until recently, a partner at a16z. In other words, he is AI-industry royalty. Midha's new project is AMP PBC, a company that believes it can radically lower the price of compute. To accomplish that, he is working on building a compute grid that turns GPUs into a standardized utility. But right now, compute is too fragmented. It's too heterogeneous. And given the way contracts are structured, he says that labs are being forced to spend money on capacity that often goes unused. In other words, small labs are forced to pay up for big, long-term contracts, even though their own demand (particularly during model training) may be very spiky. On this episode, Midha explains how the market for compute currently works and why he believes there's a software solution that could significantly improve compute utilization. He also tells us why he does not anticipate one company will emerge as the dominate player and that instead we'll have a wide range of models, each optimally used in specific applications.

Read more:
Amazon Says Its Data Centers Use 2.5 Billion Gallons of Water
Oracle Falls Most in Six Months on Mounting Data Center Costs

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