Suppose you’re in the business of putting your money where everybody’s mouth is. I guess that’s kind of a strange way to say it, but investors are sort of in that business: they have the money, they hear what everyone is saying around them, and they want to use that knowledge to invest wisely.
Well, if that’s your scenario, you can get clues from places like Motley Fool with “top AI picks.” Or you can keep an ear to the ground for trends that come into play. Here’s a bit from a piece at AI Insider, about the ideas coming out of this year’s Davis conference, where I was to help run the Imagination in Action event, a free conference with lots of speakers on technology.
Others were also paying attention to this at Davos.
“AI’s next phase will be defined less by model breakthroughs and more by how effectively organizations, governments, and industries deploy the technology at scale,” reports Greg Bock, highlighting some of the avenues that investors might use to stay relevant.
Or you could take ideas from places like Ark Invest, that have become known for things like mutual fund management in today’s investment world.
“Analysts with Cathie Wood’s Ark Invest family of exchange-traded funds (ETFs) predict spending on AI infrastructure — data centers, mostly — is set to soar from last year’s $500 billion to $1.4 trillion in 2030, jibing with an outlook from JPMorgan,” writes Motley Fool’s James Brumley. “That’s annualized growth of more than 20%, offering investors an opportunity that’s just too good to pass up.”
So there’s a big pot. Startups or blue chips? GPUs or LLMs? Where does the investor turn?
More from Davos
Let’s go back to a panel at Imagination in Action’s Davos event, with David Rubenstein interviewing Bain Capital Senior Advisor Steve Pagliuca, Paul Alivisatos from U. of Chicago, Ulrike Hoffman-Burchardi of UBS Global Wealth, and Mahdi Aladel of Aramco Ventures. Talk turned to the nature of AI investing today, and the scale of it.
Economies of Scale
“1.5 trillion is the estimated investment over the next 5 years, as you build these data centers and infrastructure,” Pagliuca said. “When you think about that order of magnitude, it’s bigger than the railroads, bigger than anything that’s ever been done. And it’s going to drive a lot of ancillary businesses and chip businesses, service businesses, power businesses. So there’s a whole chain where you can make money investing.”
Quantum Computing
Rubenstein asked Alivisatos about quantum computing and how it’s treated in academia. Alivisatos compared quantum to traditional computing this way:
“Quantum takes the equations that were developed to describe atoms and molecules and applies that mathematics to any problem where there are many solutions that are very close by (sic) related to each other, but you care a lot about which one is the best,” Alivisatos said. “For example, let’s say a logistics problem: you have so many cities, and so many trucks, and so many products. How do you optimize that? That’s like the electrons finding their best spot inside a molecule that lowers the energy. You minimize a utility function for a problem like that.”
Noting the types of hardware that will be involved in adding quantum computing to the mix, Alivisatos described how these tools will affect enterprise and geopolitics, too.
“Quantum will be another layer that will solve certain problems with extraordinary precision,” he said.
AI in Sports, Oil Utilities, and Venture Capital
Later in the panel discussion, Rubenstein asked Aladel a number of questions about applying AI to oil and gas, for example, whether the technology could help humans sniff out the oil. He asked Pagliuca, as a former sports team owner, whether AI helps pick out good players. And the group talked about applications to venture capital.
Rubenstein started out this way:
“Steve, some people amazingly don’t think private equity is a good thing for society. Tell us: why is private equity a good thing for society?”
“Private equity is misunderstood. I think that’s really a misnomer. It’s been an incredible model because it brings ownership close to the businesses. It’s gone from a cottage industry to an industry that adds value, brings AI, brings finance, brings marketing, brings skills across these companies globally.”
Students Thinking With and Without Machines
Another part of the panel discussion that I found most interesting revolved around education.
It started out with Rubenstein? asking about the prospect of students cheating with AI. AAA suggested, facetiously, a “Faraday cage,” before actually explaining that a better way to approach curriculum is to help students to integrate technology into learning.
“In our curriculum, there are parts of it that we actually do decouple completely from AI, but from our perspective, we want students to learn how to think with machines, how to think about them, and also how to think without them. And you know, the cheating piece isn’t that important to us in the end. It’s really about giving them the right way of thinking about the world they’re in.”
A Stock Tip
Responding to Rubenstein’s last question, a request for financial advice on AI investing, Hoffman-Burchardi offered this:
“The last three years have all been about the AI enablers, the AI 7, whether it’s the chip companies or the hyperscalers,” she said. “And we think the next years will all be about the AI adopters, those companies using AI to drive revenue, and also lower cost. And in particular, (we’re) very excited about the healthcare opportunity where it’s trading at a discount to the S&P 500, yet we may have a chance to actually bend the cost curve from drug discovery all the way to clinical trials, and I think that’s one of the most exciting opportunities to bend that law that shows us that drugs have now doubled in costs every nine years.”
That’s a little about the investing landscape around AI. Stay tuned for a lot more from Davos.
