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Bloomberg


Bloomberg's Joe Weisenthal and Tracy Alloway explore the most interesting topics in finance, markets and economics. Join the conversation every Monday and Thursday.


Odd Lots

New York City is about to elect a new mayor, and whoever it is will have to address growing challenges like unaffordability, homelessness, and other basic quality-of-life challenges. Very few of these challenges are distinct to NYC. San Francisco, in particular, has also faced this weird tension, where it's incredibly dynamic and wealthy, and also famous for its obvious symptoms of dysfunction. The city is one year into the new Daniel Lurie administration, and many of the quality-of-life statistics have been improving (which is the case in other cities as well). The city is ground zero for the world's AI industry, which is heavily concentrated in SF, rather than the Bay Area writ large. So we spoke with Lurie about his approach to city management, what he's learned in his first year on the job, his vision for improving zoning, and what, if any, advice he'd offer to the next NYC mayor.
 
Read more:
Uber to Take on Waymo in San Francisco With Lucid, Nuro Robotaxis
Trump Cancels San Francisco Raids After Benioff, Huang Calls
 
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San Francisco's New Mayor on Homelessness, Unaffordability, and AI

Unfortunately, it doesn't seem as though you can get great stock picks just by going to ChatGPT and asking it to recommend some investments. And yet financial firms of all sorts — including trading firms — say they're increasingly using AI. But are the tools actually being deployed? And how do these tools differ from traditional machine learning or algorithmic approaches to trading, the likes of which have been used by quant firms for decades now. On this episode of the podcast, we speak with Iain Dunning, the head of AI research at Hudson River Trading, a major US market maker. We discuss the firm's attempts to use AI not just for more efficient trading, but also to make short-term predictions about price, which further gives its traders an edge. Dunning walks us through his work, his views on the main constraints facing the space (labor, power, chips, etc.) and how his work is both different and similar to what's happening at the major cutting edge research labs like ChatGPT.

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How Hudson River Trading Actually Uses AI

You hear a lot about AI safety, and this idea that sufficiently advanced AI could pose some kind of threat to humans. So people are always talking about and researching "alignment" to ensure that new AI models comport with human needs and values. But what about humans' collective treatment of AI? A small but growing number of researchers talk about AI models potentially being sentient. Perhaps they are "moral patients." Perhaps they feel some kind of equivalent of pleasure and pain -- all of which, if so, raises questions about how we use AI. They argue that one day we'll be talking about AI welfare the way we talk about animal rights, or humane versions of animal husbandry. On this episode we speak with Larissa Schiavo of Eleos AI. Eleos is an an organization that says it's "preparing for AI sentience and welfare." In this conversation we discuss the work being done in the field, why some people think it's an important area for research, whether it's in tension with AI safety, and how our use and development of AI might change in a world where models' welfare were to be seen as an important consideration.
 
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The Movement That Wants Us to Care About AI Model Welfare

Everyone has an opinion on why housing is so expensive in America -- and to be fair, there are probably a lot of reasons for it. But one simple factor is that homes are expensive to build. Unlike many other physical objects, they haven't gotten cheaper over time. So why is this? And why haven't we found a way to bring down the cost curve by building modular housing in factories or on assembly lines? On this episode, we speak with Brian Potter the author of the new book The Origins of Efficiency. Potter also worked at a modular homes startup that failed, and is also the author of the excellent Construction Physics newsletter. So we talk about what he's learned about housing, as well as broader questions about how operational efficiency is achieved over time across a range of industries.
 
Read more:
Austin, Salt Lake City Top Global List of Most Affordable Cities
Affordable Housing Left Vulnerable After Trump Fires Building Inspectors
 
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Why It's Still So Expensive to Build Homes in America

If you go out to eat at a restaurant, whether it's a fast food chain or a Michelin-starred bistro, there's a good chance the ingredients on your plate came from the same source. Sysco is the dominant foodservice distributor in the US, using its massive logistics network to quietly supply the food that goes into meals in thousands of restaurants across the US. Sysco's scale and product standardization have helped define what American dining tastes like -- sometimes literally. But critics say its power has gone too far, leaving chefs and diners with fewer choices and blander outcomes. In this episode, we talk with Austin Frerick, author of Barons: Money, Power, and the Corruption of America's Food Industry, about how Sysco became the middleman shaping America's menus.
 
 
 
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The Hidden Supply Chain Making Every Menu Feel Familiar

A few years ago, governments and corporations were brimming with optimism about the prospect of getting to net-zero in the efforts against climate change. Today, you hear a lot less about that. And while there's renewables getting added to the mix all the time, one energy source that's really booming is natural gas. And coal is booming too. So what happened? And is there any prospect of the world getting back on track? On this episode, we speak with acclaimed energy historian Daniel Yergin, current Vice Chairman of S&P Global. He's also, of course, the author of the Pulitzer Prize-winning book The Prize, as well as, more recently, The New Map. We talk about all of the factors that changed the energy picture in recent years and the energy priorities of nations right now.
 
Read more:
Russia’s Crude Shipments Climb Close to a Post-Invasion High
Trump to Buy 1 Million Barrels to Help Refill Oil Reserve
 
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Daniel Yergin on What Happened to the Energy Transition

Some economists expected that the dollar would strengthen when the tariffs were imposed. Instead, the opposite happened. The dollar fell sharply and it's been a poor performer all year. Concurrently, it's been a great year for a lot of dollar-denominated assets, like stocks. Even US Treasuries have rallied this year. So what's going on? On this episode, we speak with recurring Odd Lots guest Hyun Song Shin, Economic Adviser and Head of the Monetary and Economic Department at the Bank for International Settlements. Per his work, the world didn't abandon the US dollar, but it did start hedging exposure to it. We discuss this phenomenon, as well as other risks on the macro landscape.

Only Bloomberg.com subscribers can get the Odd Lots newsletter in their inbox — now delivered every weekday — plus unlimited access to the site and app. Subscribe at bloomberg.com/subscriptions/oddlots

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Why The World Started Hedging Its US Dollar Exposure

The 2010s saw economic weakness across Europe's periphery. Countries like Greece, Spain, Italy, and so forth were the sites of so much stress. In the 2020s, however, it's reversed. The periphery is holding up well, but the industrial core is facing stress. Germany, in particular, the old powerhouse of the continent, has been slammed by the surge in electricity costs and competition with China. Other Northern states have felt similar pain. So what is the future for Europe? Can the EU project itself continue to evolve and integrate? On this episode, we speak with Olli Rehn, governor of the Bank of Finland and a member of the ECB's Governing Council. We discuss the near and medium-term challenges facing the EU and the prospects for finding a robust growth path in the future.
 
Only Bloomberg.com subscribers can get the Odd Lots newsletter in their inbox — now delivered every weekday — plus unlimited access to the site and app. Subscribe at bloomberg.com/subscriptions/oddlots

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Olli Rehn on the Big Competitiveness Challenge Facing Europe

Gold has been surging. Risky assets (with a few minor hiccups) have also been surging. And yet, central bankers (most notably the Fed) are in rate cutting mode. Why is this? And what kind of risks are being conjured up? On this episode of the podcast, we speak with Raghuram Rajan, a professor at the Booth School of Business at the University of Chicago, as well as the former Governor of the Reserve Bank of India. Rajan famously was one of the first to raise alarms prior to the Great Financial Crisis in 2008. We discuss why financial markets are doing what they're doing and whether central bankers are sufficiently attuned to the growing risks.
 
Read more:
Gold Holds Drop as Traders Focus on US-China Trade, Credit Woes
AI Stocks Are in a Bubble, Most Investors Say in BofA Survey
 
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Raghuram Rajan on Surging Gold and Growing Risks to Financial Stability

Make sense of the world with one essential conversation, every week. Mishal Husain, one of Britain's best interviewers, brings her signature blend of curiosity and tenacity to weekly conversations with world leaders, business titans, and cultural icons, revealing who they really are and how they see the world changing around them.

Follow the podcast wherever you listen, so you don't miss an episode.
https://link.podtrac.com/iu94w2n4

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Introducing: The Mishal Husain Show

Earlier this year, markets were spooked by blow-ups in a number of volatility-linked products. But dealing with volatility is the foundation of risk management on Wall Street and there's a particular model that's become pervasive among big investors and banks -- so-called Value-at-Risk (VaR) models seek to gauge how much a portfolio might gain or lose based on historic price movements. On this week's episode of the Odd Lots podcast, we speak to one of the original creators of VaR. Till Guldimann explains how he came up with the model while at JPMorgan, plus how it works, its limitations, how it can be gamed, and what he thinks of the volatility landscape now. 

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The Creator of VaR Explains How Large Banks Measure The Risk Of Their Own Portfolios

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