The Indicator from Planet Money - Why Google fell behind in the AI race

Episode Date: July 9, 2026

When it comes to AI, Google’s Gemini does not have the same household recognition that Claude and ChatGPT do. One big explanation: the innovator’s dilemma. We explain how Google DeepMind CEO Demis Hassabis is trying to fight a lumbering company’s constraints to build AI superintelligence. Sebastian Mallaby’s book is The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence Fact checking by Sierra Juarez. Your Next Listen — The inventor’s dilemma Connect with The Indicator — Sign up for The Indicator’s brand new newsletter — Buy the Planet Money book — Find our socials, YouTube and more!— For sponsor-free episodes, subscribe to NPR+ See pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

NPR. This is the indicator from Planet Money. I'm Terry and Woods. And I'm Waylon Wong. Until recently, Google was the king of the internet. Yeah, you Google information. That is the verb. You don't Yahoo the web. You don't Alta Vista the web. No.

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 chat bots. That is chat GPT. That's right. and it's not the go-to tool for coding either. That is Claude Codod.

And in a recent presentation, it kind of appeared like Google was throwing everything AI at the wall to see what sticks. Give it your own videos, for example, this selfie, and change reality in a really fun way. Demas Asabas 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. Our mission is to reimagine the drug discovery process with the goal of one day solving all disease. Yeah, solving all disease. Pretty ambitious. 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 Malaby. Google looks like the lab that is just fantastic at coming second. Today on the show, we talk to Sebastian about how Demis Asavas made incredible breakthroughs at Google, yet the company is only fantastic at coming second,

and we learn about what's being called a triple innovators deliver. Sebastian Malaby writes books featuring Titans like former Fed Chair Ellen Greenspan and investor George Soros, and he figured out that Demasasas was another powerful person. in one of the most exciting industries today, AI. So Sebastian pitched him. There is going to be a book about you. You're cooked. It's done. 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. There was this possessed scientist staring at me and saying, at 2 in the morning, Sebastian, I'm reading a scientific paper. I can feel reality staring at me, calling out to me, waiting to 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. Why is the table solidarian? Is that a threat? At 2 a.m., everything sounds like a threat, I think. Never before has a conversation over beer has seemed like at such high stakes.

So what's happening here is Dennis 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 Deep Mind in 2010 in London. By 2013, Demas 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.

Under Demasasasovas' 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 Demas a Nobel Prize in chemistry. He tells me that that won Nobel Prize was a nice start, but he'd quite like another one. Yeah, the buzz of the first Nobel Prize wears off pretty quickly, I hear. 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 chat GPT was first launched by OpenAI. 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? Sebastian believes that Google suffered from what he calls a triple innovator's deliver. 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. That's why Kodak failed to seize the digital camera market because it was set up for the analog error. And it's also why Xerox couldn't profit from personal computers, even though it's research.

pioneered the technology. 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? That's the standard innovator's dilemma. Sebastian says for Google specifically, this innovator's dilemma came in three forms. First of all, you know, its dominance in search

depended on a reputation for providing reliable information. So it couldn't afford to release chat parts that hallucinated. Remember when it was saying that you could put glue on pizza to keep the cheese from sliding off? I mean, it does work. But at what cost, Darian? It does make it inedible. And Google's second force working against AI was that it was unclear how to make money from it. 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. 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 ChattieBTBT, which in the early days spewed toxic results and, you know, hallucinated and appeared weirdly sentient to some people. I mean, that would have been. a shortcut to business suicide. So yeah, political risks was barrier number three. Google did eventually

release an AI chatbot in March of 2023, thanks to Demis Asavas 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. Yeah, we use Gemini at work at NPR. Yeah, not for writing, obviously, but sometimes for sorting through numerous documents and our research. Google's also a financial supporter of NPR. And so where does this leave Demis Sassabas 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? 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? I would say Alphabet and Google, because I think, you know,

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. There is a sense in which all of this talk of business dominance and capital and competition might seem a little at odds with Demisor Sardis's scientist persona. 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. It's not detracting from his fascination. What is the nature of information? What is an emergent property? And can we understand the fabric of reality? And those lofty ambitions include that pronouncement to one day use AI to solve all diseases.

The goal of one day solving all disease. Does that ring as completely absurd to you? 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. Are you sold, Waylon?

Yeah, maybe advanced AI could explain this to me over a beer. AI is pretty good at explaining AI. It knows itself well. This episode was produced by Julia Ritchie with engineering by Travis Hagen. It was fact-tracked by Sierra Juarez. Kakin Canada edits the show and The Indicator is a production of NPR.