Nick Schifrin:
Perhaps the most important business and economic story this year was the development and spending around artificial intelligence.
AI spending is driving one of the most explosive periods in the tech industry and is playing a major role in overall U.S. economic growth. A few companies are making huge profits, especially Nvidia, which posted record profits of $32 billion, up 65% in one year. But there are very real questions about whether this is a bubble.
Geoff Bennett elaborated on this in a conversation he recently recorded.
Geoff Bennett:
Experts say this boom exceeds almost anything imaginable, and the spending goes beyond what was spent on the Manhattan Project and the Apollo missions to space.
But some experts worry that the trillions of dollars being spent and fierce competition are creating an AI bubble that won’t support the kind of profit growth that can match all that investment. And if the bubble bursts, it could impact more than just Silicon Valley.
For more, we’re joined now by Cade Metz, technology reporter for The New York Times covering the world of AI
Thank you for being with us.
Cade Metz, technology reporter, The New York Times:
I’m happy to be here.
Geoff Bennett:
So let’s start with the basics. What’s driving this explosion of AI investment? Why does it seem like all these companies are piling up at once?
Cade Metz:
Since the advent of the ChatGPT chatbot about three years ago, we have seen this technology steadily advancing and slowly working its way into people’s lives, into the lives of office workers.
In many ways it is a transformative technology. It helps people search the Internet in new ways. And in offices, it helps transcribe meetings, perhaps allowing doctors and other professionals to do their work a little faster.
But Silicon Valley sees much bigger things ahead. They see this technology continuing to improve and becoming more powerful in the coming years. So they invest those hundreds of billions of dollars in the data centers that not only allow them to improve this technology, but also offer it to a much larger portion of the population.
Geoff Bennett:
And overall, trillions of dollars are flowing into AI. Is this growth sustainable or are we in bubble territory here?
Cade Metz:
That’s the question everyone is trying to answer and no one can quite answer.
These are enormous expenses, to say the least. And it’s a gamble on the future. These data centers are not only expensive. They take years to build. So all these companies that don’t want to miss this big boom have to bet two, three, four years into the future that they’re going to be able to bring in the revenue to pay for this.
Maybe. Maybe they can’t. No one can completely agree. It’s really a matter of timing. For many of these companies, revenues are already coming in. The question is how quickly it will come in and how many companies can bring in that revenue. There are so many companies participating in this race. Many people believe that they can’t win all.
Geoff Bennett:
Is that why it is so difficult for these companies to establish AI dominance?
Cade Metz:
Partially.
You have a lot of big players. The Googles, the Microsofts and the Amazons of the world do this. And then you have more agile start-ups like OpenAI and Anthropic. Meta recently doubled down on this, the company that owns Facebook and Instagram. They built a new AI lab. Elon Musk is in the mix.
People in the Valley here talk about FOMO, the fear of missing out. No one wants to miss this technology. So the race has even expanded in the past year.
Geoff Bennett:
Let’s get back to the data centers you mentioned, because the spending there has just been enormous. What risks does this pose for markets, energy systems and the wider economy?
Cade Metz:
For the broader economy, the concern here is that so much debt is being taken on to build these data centers. For years, the big players I mentioned, the Googles, the Amazons, and the Microsofts, have built these massive data centers largely with cash on hand or primarily with cash on hand.
These are companies that bring in billions of dollars in revenue per year. They can afford to build these facilities. But there is so much demand for this extra computing power that so many other companies are now building these data centers for various reasons, for themselves or for their partners.
And those companies are taking on much more debt than we’ve seen in the past. And that’s where the risk comes into play. Ultimately, that debt must be repaid. And if the revenue isn’t coming in from these companies by then, you’re in trouble.
Geoff Bennett:
So it’s this idea of a circular loop. You have the tech giants investing in the AI companies, who then use that money to invest in the infrastructure of those same tech companies. Is that why people are raising a red flag?
Cade Metz:
Well, that’s part of what’s going on. All these companies are working together, hoping to get the entire industry going and moving forward. And so you have those kinds of deals, where, for example, a company acquires investments from one of the big giants and then immediately spends that money on the same company.
They see that as a partnership. Others see that as a sign that the market may not be as healthy as it seems.
Geoff Bennett:
What about the content, the concerns about the way AI is deployed, often poorly with little regulation, a flood of low-quality misleading content on the internet? How are the companies responding to these concerns and concerns?
Cade Metz:
In some cases, they’re working to address the disinformation problem you’re talking about. These systems make mistakes. They do cause problems. We have three years to document all that.
And there are ongoing efforts to improve that problem. But you have to realize that this technology is fundamentally flawed. This is a technology developed by analyzing massive amounts of data collected over the Internet. We look for patterns in that data. And so it learns its skills.
But that also means that as it learns, it will make mistakes. It will learn from bad data, but it will also make mistakes just because these are probability engines, right? They do something based on what they saw in the data. And that essentially means that they will make mistakes a percentage of the time. People need to realize that that’s always in the mix.
And that can also — in addition to causing all kinds of problems in — just in the information as it’s distributed across the Internet, it can also cause problems in other ways that these systems behave. The hope is that these systems will perform increasingly important tasks in the coming years.
But as those mistakes occur over time, it becomes more difficult to complete those tasks.
Geoff Bennett:
Problems, for sure.
What about the promise, the promise of AI? What have you encountered in your reporting that you find most exciting?
Cade Metz:
The most exciting part of this, I think, is healthcare.
What we’ve seen is that the technology that powers something like the chatbot ChatGPT, which many people are now familiar with, the same technology can be used to support drug discovery. Essentially, it can help design drugs and vaccines that can help deal with diseases and ailments. That’s the most powerful aspect of the technology, in some ways the most promising, and in others the most important.
Geoff Bennett:
Cade Metz from The New York Times, thanks again for your time. We appreciate it.
Cade Metz:
Thank you.
