On Monday October 19th, 1987, the Dow Jones fell 508 points in a one day crash that will forever be known as "Black Monday". In honor of the 30th anniversary, Joe and Tracy talk to Blair Hull, managing partner of Hull Trading Co., who was actively trading that day. While everyone else panicked, Hull spotted an opportunity and won big in the chaos. On this episode, we talk about how he was able to keep his head above water and what lessons that day holds for markets today.

On Monday October 19th, 1987, the Dow Jones fell 508 points in a one day crash that will forever be known as "Black Monday". In honor of the 30th anniversary, Joe and Tracy talk to Blair Hull, managing partner of Hull Trading Co., who was actively trading that day. While everyone else panicked, Hull spotted an opportunity and won big in the chaos. On this episode, we talk about how he was able to keep his head above water and what lessons that day holds for markets today.

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

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

Bloomberg's Joe Weisenthal and Tracy Alloway analyze the weird patterns, the complex issues and the newest market crazes. Join the conversation every Tuesday and Thursday for interviews with the most interesting minds in finance, economics and markets.

Odd Lots

On Bloomberg’s Odd Lots podcast Joe Weisenthal and Tracy Alloway explore the most interesting topics in finance, markets, and economics. Join the conversation every Monday and Thursday. 

On Bloomberg’s Odd Lots podcast Joe Weisenthal and Tracy Alloway explore the most interesting topics in finance, markets, and economics. Join the conversation every Monday and Thursday.

How One Trader Won Big While Everyone Else Panicked on Black Monday

https://api.omny.fm/orgs/e73c998e-6e60-432f-8610-ae210140c5b1/clips/ff3d6294-b518-467b-b0d7-ae27005b9c55/transcript

In 2022, Congress passed the CHIPS Act, which set aside tens of billions of dollars in loans and grants in order to encourage companies to build new semiconductor fabs in the United States. We're still very early in the process. It's going to be a long time before we know if the US will become a major player again in the production of advanced chips. But the process is well underway and the bulk of the awards have been officially announced, with much of the money going to Intel, Samsung, TSMC, and others. So how did the grants get allocated — and what's next? On this episode of Lots More, we speak with Bloomberg News reporter Mackenzie Hawkins on the latest developments.

In 2022, Congress passed the CHIPS Act, which set aside tens of billions of dollars in loans and grants in order to encourage companies to build new semiconductor fabs in the United States. We're still very early in the process. It's going to be a long time before we know if the US will become a major player again in the production of advanced chips. But the process is well underway and the bulk of the awards have been officially announced, with much of the money going to Intel, Samsung, TSMC, and others. So how did the grants get allocated — and what's next? On this episode of Lots More, we speak with Bloomberg News reporter Mackenzie Hawkins on the latest developments.

Lots More on How CHIPS Act Money Got Awarded

https://api.omny.fm/orgs/e73c998e-6e60-432f-8610-ae210140c5b1/clips/2cc904d6-e7fe-45b0-b847-b164015bdf57/transcript

Breakthroughs in generative AI have created enormous opportunities for humans to learn from computers. We can use them to explain the news, understand historical concepts, fix our coding errors, and so forth. But of course, AI also has to learn from human. The technology digests enormous amounts of written text, and often relies on human feedback to calibrate its models. Luis von Ahn has been at the forefront of these back and forth interactions for years. He is currently the CEO and co-founder of Duolingo, the language learning app, but prior to that, he was one of the original developers of CAPTCHAs, the little puzzles you solve to log into websites and prove that you're a human. And of course, in the process of proving your humanity, you're also training computers to get better at identifying red lights, cross walks, bicycles and wavy letters. On this episode, we discuss the history of his work, the future of CAPTCHAs, the success of Duolingo and how he is using today's advanced AI models in aid of language learnings.

Breakthroughs in generative AI have created enormous opportunities for humans to learn from computers. We can use them to explain the news, understand historical concepts, fix our coding errors, and so forth. But of course, AI also has to learn from human. The technology digests enormous amounts of written text, and often relies on human feedback to calibrate its models. Luis von Ahn has been at the forefront of these back and forth interactions for years. He is currently the CEO and co-founder of Duolingo, the language learning app, but prior to that, he was one of the original developers of CAPTCHAs, the little puzzles you solve to log into websites and prove that you're a human. And of course, in the process of proving your humanity, you're also training computers to get better at identifying red lights, cross walks, bicycles and wavy letters. On this episode, we discuss the history of his work, the future of CAPTCHAs, the success of Duolingo and how he is using today's advanced AI models in aid of language learnings.

Luis von Ahn Explains How Computers and Humans Learn From Each Other

https://api.omny.fm/orgs/e73c998e-6e60-432f-8610-ae210140c5b1/clips/b4779adf-05bb-4420-8740-b163015097e9/transcript

In the past, the most expensive housing in any major city would be connected in some way to the economics of the city itself. If the general market was weak, the high end was also weak. If the general market was strong, then the high end was strong. But increasingly in cities like NYC, Aspen, Dubai, Miami, and elsewhere, the ultra high end exists in a different market, where the rich splash around money at levels which are completely disconnected from the local environment. At these levels, the ultra-wealthy are engaging in a global game of one-upmanship, where a higher price tag, perversely, can make a given property even more tantalizing. On this episode we speak with Hiten Samtani, founder of ten31 Media, which focuses on real estate, about how this market has developed. We talk through the deals, brokers, the buyers, and the general economics of this ultra-premium tier. We also discuss the rise of branded condos -- or those with the Mercedes or Porsche imprimatur -- and how they're reshaping the real estate landscape.

In the past, the most expensive housing in any major city would be connected in some way to the economics of the city itself. If the general market was weak, the high end was also weak. If the general market was strong, then the high end was strong. But increasingly in cities like NYC, Aspen, Dubai, Miami, and elsewhere, the ultra high end exists in a different market, where the rich splash around money at levels which are completely disconnected from the local environment. At these levels, the ultra-wealthy are engaging in a global game of one-upmanship, where a higher price tag, perversely, can make a given property even more tantalizing. On this episode we speak with Hiten Samtani, founder of ten31 Media, which focuses on real estate, about how this market has developed. We talk through the deals, brokers, the buyers, and the general economics of this ultra-premium tier. We also discuss the rise of branded condos -- or those with the Mercedes or Porsche imprimatur -- and how they're reshaping the real estate landscape.

The Ultra Wealthy Have Their Own Separate World of Real Estate

https://api.omny.fm/orgs/e73c998e-6e60-432f-8610-ae210140c5b1/clips/18457c0f-120b-4df9-a7a8-b15e01283066/transcript

How One Trader Won Big While Everyone Else Panicked on Black Monday

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