The Indicator from Planet Money

-: - NPR. [COIN SPINNING] DARIAN WOODS: This is The Indicator from Planet Money. I'm Darian Woods. WAILIN WONG: And I'm Wailin Wong. Until recently, Google was the king of the internet. WOODS: Yeah. You google information. That is the verb. You don't Yahoo the web. WONG: You don't AltaVista the web. WOODS: No. WONG: [LAUGHS] No one's ever done that. Yet, with the rise of AI, Google has invested a ton in the technology. But that hasn't kept its crown. Like, Google isn't synonymous with chatbots. WOODS: That is ChatGPT. WONG: That's right. And it's not the go-to tool for coding either. WOODS: That is Claude Code. WONG: And in a recent presentation, it kind of appeared like Google was throwing everything AI at the wall to see what sticks. [AUDIO PLAYBACK] DEMIS HASSABIS: Give it your own videos-- for example, this selfie-- and change reality in a really fun way. [END PLAYBACK] WOODS: Demis Hassabis is the CEO of Google's in-house AI group, DeepMind. And Demis was showcasing a seemingly quirky video generator that could give you a new outfit or background. But then the next minute, he was speaking with extraordinary technological ambition. [AUDIO PLAYBACK] HASSABIS: Our mission is to reimagine the drug discovery process, with the goal of one day solving all disease. [END PLAYBACK] WONG: Yeah, solving all disease-- pretty ambitious. WOODS: And yet, despite these stratospheric goals, Google never seems to quite get to the front of the AI race. That's according to journalist Sebastian Mallaby. SEBASTIAN MALLABY: Google looks like the lab that is just fantastic at coming second. WOODS: Today on the show, we talked to Sebastian about how Demis Hassabis made incredible breakthroughs at Google, yet the company is only fantastic at coming second. And we about what's been called a triple innovator's dilemma. [INTRIGUING MUSIC] WOODS: Sebastian Mallaby writes books featuring titans like former Fed Chairman Alan Greenspan and investor George Soros. And he figured out that Demis Hassabis was another powerful person in one of the most exciting industries today, AI. So Sebastian pitched him. MALLABY: There is going to be a book about you. You're cooked. It's done. WONG: Demis acquiesced to having Sebastian be the one to write that first book. Sebastian spent over 30 hours interviewing him, mostly in a London pub. MALLABY: There was this possessed scientist staring at me and saying, at 2:00 in the morning, Sebastian, I'm reading a scientific paper. I can feel reality staring at me, calling out to me, waiting be discovered. That's why I'm building AI. We need to understand these things. And then he would bang the table and say, why is this table solid? It's a bunch of atoms jumping around with gaps in between. Why is that laptop, Sebastian-- why can it think? These are mysteries that we have to understand, I need to understand before I croak. WONG: Why is the table solid, Darian? WOODS: Is that a threat? [LAUGHS] WONG: At 2:00 AM, everything sounds like a threat, I think. WOODS: Never before has a conversation over beer seemed like it had such high stakes. So what's happening here is, Demis wants to understand the universe, so he's building AI. And to build AI, he studied for a PhD in cognitive neuroscience. And then he co-founded DeepMind in 2010 in London. WONG: By 2013, Demis was being courted by various tech leaders who wanted to acquire DeepMind-- Mark Zuckerberg, Elon Musk, Google's Larry Page. There were pros and cons with each. Eventually, he agreed to a purchase by Google. WOODS: Under Demis Hassabis's leadership, Google has made some incredible breakthroughs in AI research. Google DeepMind successfully predicted how amino acids form three-dimensional shapes, which is a fundamental process known as protein folding. That got Demis a Nobel Prize in chemistry. MALLABY: He tells me that that one Nobel Prize was a nice start, but he'd quite like another one. WOODS: Yeah. The buzz of the first Nobel Prize wears off pretty quickly, I hear. WONG: Yes. I know the feeling well. But an incident in late November 2022 revealed a potential downside to being part of a behemoth like Google. Even though Google had the technology ready, the famous AI chatbot ChatGPT was first launched by OpenAI. MALLABY: The question was kind of, why did Google not release a language bot? Because it had the technology. It could have done it. Why did they not release it first? WOODS: Sebastian believes that Google suffered from what he calls a triple innovator's dilemma. MALLABY: Innovator's dilemma basically says, look, if you have a successful incumbent company with a very good product that's making a lot of money, it won't want to back an innovation that will cannibalize the existing product, because the status quo is too sweet. WOODS: That's why Kodak failed to seize the digital camera market, because it was set up for the analog era. It's also why Xerox couldn't profit from personal computers, even though its researchers pioneered the technology. MALLABY: Google was making a ton of money from search. Why would it want a rival product, like a large language model, that would disrupt and destabilize search? WONG: That's the standard innovator's dilemma. Sebastian says, for Google specifically, this innovator's dilemma came in three forms. MALLABY: First of all, you know, its dominance in search depended on a reputation for providing reliable information. So it couldn't afford to release chatbots that hallucinated. WONG: Remember when it was saying that you could put glue on pizza to keep the cheese from sliding off? WOODS: I mean, it does work. WONG: But at what cost, Darian? WOODS: It does make it inedible. And Google's second force working against AI was that it was unclear how to make money from it. MALLABY: Google's revenues kind of depended on serving ads alongside the search results. And it wasn't so clear how you would integrate ads into the chat. And then thirdly, Google's, you know, market share was so big that politicians, journalists, even lawyers, described it as a monopoly. And so that position, which was kind of politically precarious, would be untenable if Google alienated politicians and journalists and advertising partners by putting out a model like ChatGPT, which, in the early days, spewed toxic results and hallucinated and appeared weirdly sentient to some people. I mean, that would have been a shortcut to business suicide. WONG: So yeah, political risks was barrier number three. WOODS: Google did eventually release an AI chatbot in March of 2023, thanks to Demis Hassabis and his team, that's morphed into Gemini today. It's not the leading model, but it has, at some points, been right at the frontier on various benchmarks. WONG: Yeah. We use Gemini at work at NPR. WOODS: Yeah, not for writing, obviously, but sometimes for sorting through numerous documents in our research. Google's also a financial supporter of NPR. WONG: And so where does this leave Demis Hassabis and Google, or its parent company, Alphabet? Will it end up like a Kodak or Xerox, consigned to the history files as a cautionary innovator's dilemma? WOODS: If you had to put your money on one company to be in the lead in a few years' time, which company would it be? MALLABY: I would say Alphabet and Google, because I think being the best at coming second is a very good strategy for, you know, surviving the distance. You know, there's so many people in the world who are touched by some kind of Google product, whether that's Maps or Search, Google Drive, Gmail, that they are just going to roll it out at a scale that nobody else can match. And in the long term, being able to make money from that is what you need to stay alive in this very capital-intensive race. WOODS: There's a sense in which all of this talk of business dominance and capital and competition might seem a little at odds with Demis Hassabis's scientist persona. MALLABY: He's always had that duality, right? He spent some of his time building video games, which are kind of trivial compared to the grand ambitions of solving science. And he's got space in his head for both. Like, you can't pigeonhole him. I mean, it's not detracting from his fascination with, what is the nature of information, what is an emergent property, and can we understand the fabric of reality? WONG: And those lofty ambitions include that pronouncement to one day use AI to solve all diseases. WOODS: The goal of one day solving all disease-- does that ring as completely absurd to you? MALLABY: [LAUGHS] He likes to make these very sweeping claims. And all disease feels a bit much. But I do think that if AI is a super tool with which to sort and make sense of information, you should be able to understand the origin of disease quite minutely through very advanced AI. WOODS: Are you sold, Wailin? WONG: Yeah. Maybe advanced AI could explain this to me over a beer. WOODS: AI's pretty good at explaining AI. [LAUGHTER] WOODS: It knows itself well. This episode was produced by Julia Ritchey with engineering by Travis Hagen. It was fact checked by Sierra Juarez. Kate Concannon edits the show, and The Indicator is a production of NPR. [CONTEMPLATIVE MUSIC]