How CEOs are using AI
'The AI bubble is ahead of us': Bridgewater exec
How CEOs are using AI
‘The AI bubble is ahead of us’: Bridgewater exec
Bridgewater is building an AI run fund
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How CEOs are using AI
During an interview published in May, CEO of Microsoft said he enjoys podcasts but doesn’t listen to them. Instead, he uploads the transcripts of podcasts to the Copilot app on his phone so he can discuss the content with a voice assistant during his commute. When he reaches Microsoft’s headquarters in Washington State, Nadella uses Copilot to summarize his Outlook and Teams messages. He utilizes at least 10 custom agents from Copilot Studio to help with meeting prep and research. “I’m an email typist,” Nadella told the outlet.
It’s unsurprising that Altman of OpenAI uses AI to streamline tasks his his personal life. Altman appeared on Adam Grant’s “ReThinking” podcast this January, saying, “Honestly, I use it in the boring ways.” Altman said the AI bots help him process emails or summarize documents. The tech has also helped him with fatherhood. During an OpenAI podcast interview published in June, Altman said he used AI “constantly” after welcoming his first child in February. “Clearly, people have been able to take care of babies without ChatGPT for a long time,” Altman said. “I don’t know how I would have done that.” Now, Altman said he mostly uses ChatGPT to research developmental stages.
Cook, who became Apple CEO in 2011, publicly spoke about how he uses AI day-to-day in a 2024 interview with The Wall Street Journal. He said Apple Intelligence helps him summarize long emails. “If I can save time here and there, it adds up to something significant across a day, a week, a month,” Cook told the outlet. “It’s changed my life,” he says. “It really has.”
During the 28th annual Milken Institute Global Conference in May, Huang CEO of Nvidia told the audience he uses AI programs to learn new concepts. “I use it as a tutor every day,” Huang said. “In areas that are fairly new to me, I might say, ‘Start by explaining it to me like I’m a 12-year-old,’ and then work your way up into a doctorate-level over time.” AI’s ability to rapidly collect, analyze, and communicate information could close the tech gap, according to Huang. “In this room, it’s very unlikely that more than a handful of people know how to program with C++,” Huang said. “Yet 100% of you know how to program an AI, and the reason for that is because the AI will speak whatever language you wanted to speak.”....
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‘The bubble is ahead of us’: Bridgewater exec
Investors who are convinced the AI boom has gone too far should brace for what’s about to hit the market, Greg Jensen, co-chief investment officer at Bridgewater Associates, said in a recent interview. Jensen — who said he has spent more than a decade working with machine learning — said the market still hasn’t grasped how transformative the technology will be or how much capital is about to flood into it.
“The bubble is ahead of us, not behind us,” he said in an interview on the “In Good Company” podcast on Wednesday with Norges Bank Investment Management CEO Nicolai Tangen. While some business leaders and investors, such as Bill Gates and Michael Burry, have said that the AI boom resembles the dot-com era, Jensen said the world hasn’t even reached the speculative phase.
Instead, he said, we’re still in the phase “where people have no idea what’s hitting them,” and that most investors don’t yet understand how radically AI will reshape markets, geopolitics, and economic growth. That has triggered what Jensen calls a “resource grab phase,” unlike anything the tech industry has experienced before. Jensen said one reason the cycle is different from past tech manias is that AI leaders, including Elon Musk, OpenAI’s CEO Sam Altman, and Google, believe the stakes are existential. They “believe that the power to control Earth and the universe is only a couple years away,” he said, adding that “they’re not motivated by this normal profit incentives of the typical cycle.” That mindset means capital expenditure won’t slow just because valuations look stretched or funding gets expensive. “This money is going to get spent,” he said....
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Bridgewater is building an AI run fund
Bridgewater, the world’s largest hedge fund, is building a machine-learning engine to predict global economic events and invest clients’ money accordingly. The efforts have been led by a new group at Bridgewater, called the Artificial Investment Associate (AIA) Lab. It’s made up of 20 investors and machine-learning scientists on the mission “to do everything that we do via machine-learning techniques,” Jensen said.
For Bridgewater, the largest hedge fund in the world, that means replicating every step of the investment process with AI and machine learning, from understanding global financial and economic patterns, to creating investment theories, and plugging those theories into machine-learning models to check if the theories are accurate or not. Risk controls and oversight will still be in the hands of humans, Jensen said, and there will be a kill switch if there’s ever a need to turn it off. Jensen will have oversight over the fund. But the rest, from idea generation to testing and the models used to make trades, will all be developed through AI and machine learning.
Bridgewater’s so-called “artificial investor” is exceeding expectations by making solid predictions about what’s next for the euro, or what’s next for inflation, Jensen said. And once the fund launches, Jensen is hoping the AI investor will get “much more powerful” as a “loop of learning” mints more data. “In some sense, I feel we’ve been able to create the bones of something that will be more than the sum of its parts,” Jensen said. “We won’t describe specifics, but I do expect we will be able to generate a unique source of returns. AIA Labs will play a critical role as Bridgewater looks to transform itself with AI. At AIA Labs, much of the work is focused on combining statistical models with language models “It’s really that this moment is the integration of language models, with the type of time-series models Jensen has been working on a long time, combined with how far — in part by our own pushing — but how far diagnostic tools have come to understanding machine learning algorithms,” Jensen said. “Those pieces coming together is what has made this point so incredibly special.”….