Today, I’m talking with Google and Alphabet CEO Sundar Pichai, in a conversation we recorded just after the Google I/O developer conference. This is the fifth year Sundar and I have sat down after I/O, and it’s become one of my favorite Decoder traditions.
There’s always a lot of news at I/O, and this year was no exception — Google has powerful new Gemini models, it’s putting AI agents in everything, and it’s making huge changes to Search on both the web and YouTube that will once again reshape the information ecosystem.
That’s a lot to talk about, and Sundar and I got into all of it. But I also realized it’s been a long time since I’d asked Sundar the Decoder questions about structure and decision making, so I started there. You’ll hear Sundar say he realized he needed to rethink how Google worked a few years ago in response to ChatGPT, and he made a lot of executive changes and big decisions to get the company in a more aggressive posture.
Of course, we also talked about all those search changes, and how it seems obvious that the real future of Google Search is bringing things like the new intelligent search box together with the company’s new Gemini Spark agent platform. That way, searches can set off tasks, not just deliver results. That’s exciting, but it seems likely to yet again change the dynamics of the open web.
If you’re a Decoder listener, you’ll know that I coined the term Google Zero a few years ago — that’s the idea that Google traffic to websites would fall to zero as the company answered more and more queries directly on the search results page. That’s gone from an idea Sundar batted away in previous interviews to something the entire media industry is grappling with. Even the CEOs of major publishers like Condé Nast are now publicly saying they’re planning for a world of zero search traffic from now on.
Google is also training its models on YouTube videos, and changing YouTube search to summarize and index videos so you get dropped right into the relevant parts. That’s sure to cause some creator angst, so I asked Sundar if he’s ready to fight the same battles with YouTubers as he currently is with publishers.
Finally, I asked Sundar about Google DeepMind CEO Demis Hassabis ending the I/O keynote by saying we’re “in the foothills of the singularity.” It’s no surprise that Sundar agrees with Demis, but his thoughts on the timeline to AGI are worth paying attention to.
Like I said, it’s one of my favorite episodes to do every year, because Sundar is always game to actually take the questions — and even look at search results on my phone with me. I think you’re really going to like this year’s conversation.
Okay: Sundar Pichai, CEO of Alphabet and Google. Here we go.
This interview has been lightly edited for length and clarity.
Sundar Pichai, you’re the CEO of Alphabet and of Google. Welcome back to Decoder.
It’s great to be here. Nice to see you again, Nilay.
This is one of my favorite yearly conversations. I think we’ve done it at I/O now five times.
Wow. I didn’t quite realize it’s been five times, but I enjoy it. Thanks again.
I want to start with a little bit of a lightning round. I was thinking about this. We’ve talked a lot. We always get deep into the weeds of the web and search and big, heady ideas, and I realize I have not asked you the Decoder questions in quite some time.
I was just looking back at our previous conversations, and at Google itself, and you’ve made quite a lot of changes to Google. I think a number of your direct reports have changed over time. You’ve obviously restructured DeepMind, platforms and devices, and Android. Tell me how Google is structured right now.
Okay. It is Google and Alphabet. Obviously we have Alphabet as well, but broadly I think about it as there are three main businesses in Google: Search, YouTube, and Google Cloud. There are enormous platforms we run, which is Android, Chrome, and the whole area to do with it. And powering it all is all these important technology areas, which is AI and our infrastructure work. And then you have the functions to go with it.
But at a high level, you can think of it as Search, YouTube, Google Cloud, and then our big computing platforms. Those are the main groups, and obviously powered by Google DeepMind and our infrastructure teams. That’s one simple way to get a mental model around it. And of course, we have other bets beyond that, Waymo being the most prominent of them all, but there are many, many other bets, like Isomorphic Labs and so on.
I want to stay focused on the Google of it. I feel like we could do an entire hour on Alphabet and how that’s structured and how that works as a public company with many bets. But just to stay focused on Google for one second, the knock on Google historically is this is a company that ships lots and lots of products. You can’t sell lots of products. There’s not tons of focus. There are thousands of names of different products that are overlapping in different ways.
Where that comes from, at least in my view, is that you do have these big infrastructure bets. You have all these capabilities, and the people running the businesses can use those capabilities to spin up products. And there’s maybe not a lot of overlap or central planning like, “Did we launch two of the same thing?” How do you resolve that tension? It does seem like Google has gotten a little more focused, but that is the company’s culture: “We’re going to make a lot of bets and see which ones work.” How does that resolve for you?
There’s a lot of intent in what we do too. I think it’s not an accident we have 13 products with a billion users each, and we’ve been committed to those products longer term. You can go back and think about when Gmail launched or Maps launched or Google Docs launched or Search launched or Chrome launched. We’ve been deep and consistent in many, many areas over a long period of time as well.
One way I’ve internalized it in the AI moment is for the first time, we have such a common infrastructure powering all of them with our Gemini models and the underlying AI infrastructure. So we are more able to, with intent, do things which cut across things. Personal intelligence is a great example of it. It’s one effort. Users get a choice to turn it on in each of the products, but it’s built with one common infrastructure so that it works consistently across our products.
The underlying Gemini model itself is an example of it. We are able to bring that model in the context of the products, like Ask Maps in the context of the Maps product. But a lot of the technology powering it — the voice tech, the model, the intelligence — is all one work, which is why I think the AI moment offers us a new way to think about it, and not just across Google, but across Alphabet too over time. What makes this moment so uniquely powerful is that you can invest so much in R&D and infrastructure and develop a technology, which then you can apply across all these areas, obviously in a context in which they are useful for users, but the underlying technology platform is common. There’s a lot of intent that way and so on.
You have to give room for innovation, so allowing room for innovation where teams on the margin are able to ship some new features. Sometimes you later work to harmonize them. Take NotebookLM. Notebooks are now showing up in Gemini, and it’s effectively projects as Notebooks. And you can create a Notebook in Gemini, you can go to NotebookLM, you will see the same Notebooks, vice-versa. So that’s an example of where you innovate it first, and then you’re harmonizing later.
I was watching the keynote yesterday and I saw a lot of intent and confidence from Google: “We have this core technology. We can express it in lots of ways. It’s still essentially Google-y.” There are lots of products, lots of Gemini words. I’m going to figure them all out, I promise.
I would contrast that with… I don’t know, three, four years ago when there was the ChatGPT moment, everyone worried about what Google would do. Could OpenAI show up and take your market share in search away? Between that and now, you have changed Google. You have restructured it. There are new people in leadership roles. Connect those dots for me. How did you think about, “I need to actually change how the company works,” with the competitive moment you were in that got you here?
That’s a great question. I always internalize that moment. It was tough to convey it outside, but I pivoted the company to be AI-first. We had all the ingredients, so in some ways I felt like the Overton window had changed. People were adopting these technologies faster than we had expected. To me it was a way to go and actually express ourselves through our products, but I realized we had to organize ourselves for it. And going back to my earlier point, I realized we need a core model and a core infrastructure team to power everything we are doing across Google. A lot of my initial energy was to go set that up.
To get one AI team, we had world-class research teams in Brain and DeepMind and brought those together as Google DeepMind, which was harder than it sounds because it’s like saying, “Go put Stanford and MIT together and create a department out of it or a university out of it.” So I think we’re doing that well. At that time I also set up with Amin Vahdat, who’s now our SVP of AI infrastructure, a centralized infrastructure team, which has paid great dividends. Another evolution was realizing we need a chief AI architect to architect this technology across Google, and Koray Kavukcuoglu took on that role as well. Those were important changes.
Search needed to move faster, and Search was split across many leaders, so we put it under Elizabeth Reid, with Nick Fox being responsible for the overall area, Josh Woodward coming to help with our Labs product and working on Gemini later and driving innovation. I have other extraordinary leaders in the company as well, leaders like Philipp Schindler who runs all our operations and so on. So it is stepping back, and thinking end to end about the structure and making sure we are set up well for this moment where we need to move faster as a company, which means we need to make faster decisions.
I set up these new product reviews once a week. They were AI product reviews, making sure we are intentional about how we apply this technology, where we apply it, and to review everything firsthand, that anything to do with AI, which we were shipping to users, went through that channel. I spent time directly with whoever was working on it.
The other Decoder question I ask everybody is about decisions. You’re describing a lot of big decisions, some of them uncomfortable as you change people around. How do you make decisions? What’s your framework?
A big part of my framework is over time understanding that there are very, very few decisions which are really consequential, and most decisions aren’t. What matters much more is that you make the decision, because that’s what determines the velocity of an organization. The more you’re able to make those decisions and keep the company moving forward, you’re generally better off.
Of course, there are a few decisions like combining and setting up Google DeepMind that are more consequential, and you want to take your time deliberating and doing it. But a lot of decision-making is about just making them. The more you’re able to do that, the more you do develop over time some pattern matching and you’ve seen a version of the problem before. So I think it’s good to rely on that and separate the signal from the noise so that the signal is that this is a really important decision and you want to really deliberate around it versus it may look big, but it is more a normal course of action you need to take.
Looking around the industry, your peers in Big Tech have some of the wildest org chart ideas I’ve ever heard in my entire life. I think Meta wants to have 50 engineers report to a single manager with the power of agents. Jack Dorsey at Block wants all 6,000 people to report to him. Are you having similar thoughts that you should invent some of the craziest org charts with AI ever?
Leaders and people are incredibly important. And it depends. Some companies have a much narrower suite of products, and so different structures may work. When you’re running something at the scale of Google Cloud, it’s important that there is a CEO in charge. We are serving all the top enterprises in the world at a scale, and so how do you set up for that? Great leaders end up mattering a lot, like we have Thomas Kurian there. I do think about it.
But what I do think about it is how we are using AI more effectively, and we’ve seen the transition internally, particularly amongst our developers where we have transitioned from using AI tools to assist coding to them, a portion of the engineers directing teams of agents effectively more and more. Those are transitions underway, and that will flow beyond just engineering into the rest of the organization. It’s already happening. Even the work we are doing in Gemini Spark is to put that superpower in the hands of consumers, and what you can do with these agentic workflows, et cetera.
I’m more focused on making sure we are actually deploying that capability in a native way and that it’s working well, because for us it’s more than just making the company efficient because it’s the products we provide to others. I look at it with a very different lens. How we do it internally is what we are giving to users outside. We use Antigravity internally. That’s what we are providing outside. So the agents in Antigravity are what our developers are using, and so that’s what we are trying to put outside. It has that extra dimension to it.
The number one question Decoder listeners want me to start asking CEOs… I’ll just ask it straightforwardly. How close is AI to replacing you as the CEO?
I just think the CEO job is not that complicated. There are aspects of it where I think it’s going to be very, very helpful in terms of decision-making. I joke around that — partially joke around — that I have to spend a lot of time allocating compute. And I’m like, “Well, that seems like the AI is going to make more rational choices over time,” because I deal with a lot of appeals and emotions as part of working through a process like that.
Everywhere, what I see — which is maybe a bit different than how I think — is that done correctly, these tools are going to allow us to operate at the next level in everything we are doing. It’s not like you won’t do what you were doing before. You will start from a higher foundation. I wasn’t there when, I don’t know, spreadsheets rolled out to companies. I have to think back to how did people do all this financial analysis before? And I’m sure it changed over a period of three to four years fundamentally, and we got used to it.
I think agents and so on are a version of it. It’s not like you’re not going to plan birthday parties. Let’s say you’re planning a trip somewhere. Maybe you’re actually spending your time thinking about the actual things you want to do with your time versus chasing opening times and how to get tickets and so on. It elevates everything to a different foundation is how I think about it.
Let me ask you about that and agents. Some of those demos are fascinating. The idea that Search is going to build custom software for everybody seems like an idea in software engineering, a first impression. The idea is that you’re going to ask the computer a question, and the response will be for it to make you software that helps you get to an answer. I’m fascinated by this idea, but that is fundamentally changing Search.
And then you look at Gemini Spark, which is your agent platform in the cloud where you will say, “Go book me some tickets,” and Spark might run around and book you some tickets or do some task for you. And then there’s Antigravity, the agentic coding platform. Broadly, every year there’s a new paradigm for AI. There were LLMs first, and then maybe we’re going to chain some LLMs together, then there’s reasoning, and then now we’re at agents. Is this the foundation, or is there another paradigm shift to come?
It’s a great question. We are laying most of the building blocks in place. Fundamentally being able to reason, use tools, and code is a lot like having intelligence and reasoning — being able to plan, being able to look up things, use tools, and, if you need as part of that, to build something. You are laying all the primitives. Antigravity is for developers, but the Antigravity engine, the harness, is built into Gemini now. And Spark is just a mode of Gemini. Over time, it’s a feature. We are positioning it, but it’s just a tab within Gemini.
So you’re bringing that agentic harness. Users don’t need to think about it. Developers will understand it. Over time, in Spark, they can code powerful things. But as users, you may be building something, creating something, planning a trip, and all that is working behind the scenes.
We are laying a lot of the primitives of what we need for agents to work end to end, and more importantly, for AI to work. This long-running vision of Google Assistant we’ve all had and worked through myriad forms of it and failed to fully do it well, we are closer than ever before to delivering on that promise. We haven’t delivered it yet, but that’s the journey which I think is now closer than ever before.
I look at all the products, and they do seem like they should converge. You have the new Intelligent Search box, and I definitely want to talk about Search in more detail. But you look at that search box and then you look at, say, Canvas which makes you the apps. You’re planning a wedding, and it’ll just make you an app to help you plan a trip or a wedding or something. And then you have Spark which can go off and do things. I looked at that and I was talking to people yesterday, and it just seems obvious that that should be one product.
It will. I gave the earlier Notebook example of like, you’re creating Notebooks… but what are Notebooks? You’re effectively putting all the context you want in one place and then working off it. It’s folders as they’ve always existed for people, and Notebook should be a consistent primitive across the Google products you use. I just view agents that way. It shouldn’t matter. When you’re at the earliest stage of innovation, you create the capability. Teams are experimenting with it, but for a user over time, if you fire off planning a trip, it should work across both places is how I would think about it. You’re right in that.
There’s something very important about Google Search — it is a source of truth for people for however many years or even decades now. Go Google it, and you’ll get an answer, and that that answer is the same for you and me generally has been a very important idea. It is, I think, a fixture in the culture. Maybe Google is the last company saying it will just tell you the truth, out of all the companies out there.
Okay, but now we’re going to infinitely personalize the search box, and we’re going to infinitely personalize the Search experience. We’re all going to get different answers to queries. We’re all going to maybe even look at different interfaces depending on what we’re asking, what our personal context is, how much data Google has.
Do you think about that profoundly? How much can you destabilize the last common source of truth most people experience on the internet?
Look, there are factors well beyond our control, which is that people today have a wider variety of sources than ever before. People are getting content from so many different sources. But within the world of Google, I still think we deeply care about this being a source of knowledge and information. There are objective experiences and subjective experiences. What’s the capital of the USA? It’s not going to be custom-created for anyone. These are objective things. “Help me plan a nice trip to Montreal for a weekend” — naturally, the answers don’t need to be the same for everyone. There is a continuum there.
We deeply care about it. For certain categories of information, we do still anchor around authoritative information to present as much of an objective view as possible. And if it is health-related queries, we naturally tend to show more authoritative answers than if you’re saying, “What’s better? Should I go buy?”
Can I show you a search result?
Yeah.
A few years ago, I showed you a search result. I’ve been tracking this one for years.
I always love it. Amongst the 10 trillion queries…
Yes. Well, this one’s a favorite.
We have a very scientific, statistical way of doing this.
I think this is important, and I want to get into how consumers might be experiencing these products. So this is a search I just do all the time: “best Chromebook.” I’ll just show it to you. There it is.
So it starts with an AI overview. It just very confidently tells you the answer, and then there’s a bunch of sponsored boxes. And then the one that gets me is right below that, I believe the result is Reddit, and it has a top result in Reddit. It’s actually a different answer than the AI overview. And then there’s The New York Times, which has a different answer.
You scroll this and you’re like, “The AI overview is telling me one thing, the first organic result is fairly down the page, and all of these are different answers.” I hear what you’re saying about objective results and subjective results. “What laptop should I buy,” is somewhere in the middle of those things. I’m just curious how you think that experience for consumers is today in AI Mode and where you think it should go.
Look, to be very clear, in the world of AIO, we use an AI mode. We are organizing and giving context, but there are sources throughout, so you’re still presenting organic content in a different way. There are links and sources you’re given, but there is an opinion to go with it too, which is what you’re talking about.
Some of this will be iterative with users. One of the great things we find with search is it’s easy to measure user satisfaction. Over 25 years we’ve learned to measure user happiness, user satisfaction in a correlated way with improving the quality of the product, not for short term. That’s why we do these long-term studies. If we get any experience wrong, it shows in the metrics and we course-correct. We pride ourselves on the ability to track this over the long term — be it engagement, sessions, returning to a topic, the number of bounce-backs they do. It’s a very, very sophisticated way of looking at it. In some areas like that, the experience will continue to evolve.
Do you think that experience is good today?
It’s probably more opinionated than it should be for the particular query you showed me. That was my reaction as a user. That’s the scope for improvement is how I would say it, in a fast-evolving space, but I would expect that to happen in the product. My intuition there is, “Oh, that’s way more opinionated.” There is some chance that’s personalized to you. You may be testing it in a way that you’re uniquely personalizing. The reason that query might not be exactly representative, though, is that I know how you review all these things. There is some chance you’re in the .0001 percentile–
This is kind of why I’m asking about infinitely personalizable results, right? And I’m also asking if the experience is good, because I would bet that most people experience AI in Google Search all the time. They have that experience where they’re kicked to AI mode. There’s the stuff you can measure about user satisfaction, and then there’s how the public feels about AI.
I think there’s a pretty yawning gap between, “There’s these user numbers going up, and we’re close to a billion users, and the free products people are experiencing, how good they might be,” and then just the polling data. Young people dislike AI. It’s as objective as that gets. You can go ask them, and they will tell you in measurable ways they dislike it.
Eric Schmidt, the former CEO of Google, was booed at a college graduation speech he was giving. Seven in 10 Americans oppose data center construction. There’s some gap between the product experiences people are having and how they feel about the technology. Do you think you can close that gap? Do you think these products are good enough?
It is a very profound topic, and you’re linking the two things. AI is the most profound technology humanity’s going to deal with. It’s happening at a very fast pace. I don’t think humans have evolved to process this much change, and the rate of change particularly over the last few years is incredibly high. And particularly with all that they’re hearing, people are trying to understand the future and in the personal context of their lives, including what it means at an economic level and so on.
It really makes sense why there is anxiety around this technology, and we should be very attuned to that. That’s an important topic, and that’s much broader and bigger than the facets of what’s happening. People don’t directly associate these two all the time. In some cases, yes, they are linked in certain ways.
People experience the free versions of these models in various products. They open their social media feeds and they see slop. They see headlines about all that stuff. They have the tools just presented to them. The Gemini sparkle shows up in all the Google products, whether you ask for it or not. And then I do think you link it to, “They’re asking for a lot of electricity, and maybe my rates will go up. And maybe all the jobs will go away,” and that’s pretty scary, and I don’t know if the value exchange is there.
These are good things to study. You’re being too specific on what’s happening versus I’m just broadening it out and saying that might be part of the explanation. I do think there are other cheaper factors too.
Do you think it’s just a marketing problem? I’ve heard your peers say that AI just has a marketing problem.
No, I don’t think so. That’s the point I’m making. I’m in fact arguing against it. I think it makes sense to me why people would feel concerns about it. It feels natural to me. People are talking about how AI could make a lot of jobs go away. Why wouldn’t you feel a sense of anxiety about it? I think those are deeper issues which we have to tackle as a society. Yes, there’s concern about AI slop at a product level. All that is true. All I’m pointing out is it’s a multilayered problem. But I don’t think all the source of the data center angst is directly related to one specific experience you’re having in a product or something alone like that. That’s all the point I’m making, right? It is broader and bigger than that.
There’s a lot of AI slop out there. I feel it. In an early phase of technology with the competitive dynamic that exists, a lot of things are getting rolled out. But we also see empirically how people are using these products in very deep ways. If you go to a place where Waymo hasn’t come and you’ve just polled people, talking about self-driving cars, what you get in the polls is different from how they feel when they use these cars. Technology also goes through these things. People have pretty negative views of the internet too, by the way, if you ask about the internet. But it’s a fabric of our lives, and we have to adapt to it. All of that is simultaneously happening.
It’s a complex topic. To me, it feels like people are worried about rising energy prices, and if so, they want to make sure AI is not exacerbating the problem, and that’s a valid concern. And it’s up to us as an industry to make sure that if you’re building data centers, what can we do to make sure we aren’t contributing to that problem? I view it as our responsibility, not just us. And the government, there are bipartisan concerns around some of this stuff. For example, there’s a rate payer pledge we all signed up to with a set of commitments. Maybe there needs to be more done. All of that goes hand in hand. It’s important to talk about topics like skilling, workforce adaptations. We are driving a lot of change very fast through society. Those end up being very important topics as well.
There are concerns at all those levels, and I expect those concerns to be meaningful as we go forward. Many years ago I said, “This is more profound than fire or electricity,” and so we have always felt that. Or think about deep-fakes and how do you know whether something is real? These models are getting better at simulating reality. This is why we’re working so hard. We are open-sourcing it, we are pulling many, many partners together, and it’s great for me to see the industry collaborate on a topic like this. Cybersecurity is another good example. These are all real concerns.
As an industry we need to do more. Governments will have a stronger role to play, and the public needs to be involved. You cannot have the most consequential technology rolling out the world in a way in democracies without public citizens rightfully having a voice around it. It is really important that we go through this phase, and that’s how we learn how to adapt.
My argument is that the products do the marketing work. That’s my push. I’m still waiting to see the killer app for consumers that does it. I think we have the killer app for enterprise.
One point, there are times I’ve gone through a health journey in Gemini. It feels more than like a killer app to me, better than anything I’ve ever done before. People are going through those experiences too.
I want to talk about the web, the health journey in Gemini that requires a rich data set of health information on the web to exist. You’re training Gemini on YouTube videos, right? Veo requires the YouTube ecosystem to operate and to be fruitful, to make new work in. You and I have discussed the concept I call Google Zero for many years, the idea that you will stop sending traffic to the web. You’ve disagreed with me that this is real.
Very much so. It hasn’t happened in the last many years.
Well, I’m just going to read you a quote. This time it’s not me, and I didn’t feed this to him. Roger Lynch, the CEO of Condé Nast, did an interview with TBPN last week and he said: “Every year our search traffic was down more than we had forecast, so last year I told our teams, ‘Assume there is no search. You have to have your businesses planned as if search is zero.'”
That is Google Zero. Condé Nast is saying, “We’re assuming that search will go to zero.” How would you respond to that, the idea that one of the biggest, most iconic publishers in the world is saying, “I can’t depend on this anymore”?
Look, first of all, the information ecosystem is so much broader beyond Google, by far. We see it in the data, you see it everywhere. So if any publisher over the last 10 years… I would look at The Verge and I would say where you were when you first took over, how much it’s evolved since then, the types of content you make, where all you put that content out, how all users are coming to you. It’s exceptionally dynamic, and so it makes sense to me every publisher is adapting to this new world.
We are adapting to the evolving world and how users are consuming technology. We had to do this when the world shifted from web to mobile. We are shifting it from a world of mobile to people having ongoing conversations, chatting with these products, talking to them, consuming it in voice and many different form factors.
People are expressing preferences for various types of content. They’re looking for user-generated content. They’re looking for podcasts. They’re looking for that. Through it all, we are very committed to both meeting user expectations, and also connecting them to what’s out on the web. Just even in the last year, even since we’ve launched these features, we’ve gone back and added more links. Another area where behavior is changing is that many publishers, rightfully so, are thinking about subscription models.
Sure. But I’m just saying Condé Nast is saying, “We’re going to assume our search traffic is zero, given the trends that we see.” Should they assume that?
Look, I always view… People understand their businesses better… I mean, I’m not in a position to tell such an iconic publisher what they should think about their business or plan. If they are building content that is high-quality and people like it, I expect us to reflect that in our products. That much I can commit to them.
But I think more than any other company through this evolution, we are working very hard to make sure people can get connected, and we are planning to do it in Search and Gemini, and that still underpins a lot of what we do. But there is evolution. As the technology improves, low-quality clicks get filtered out. That’s a natural evolution we see. We see it in our metrics. Bounce clicks are going down. And so those are all dynamics.
People are going to a wider array of information, and there are more people producing information than ever before. That pie is growing. All these dynamics are happening. It’s a complex ecosystem, but our commitment is to make sure we reflect the vastness and diversity of the content, and we do think people want to connect ultimately to these sources, but we are trying to meet them in those moments, and people come with very different intent and very different moments.
One of the small features we have done, but very important I think, is if you’ve subscribed to something, we reflect that as a preferred source for you as a user. But that’s a new change which we didn’t have before. We are adapting to the fact that publishers are increasingly turning to subscription offerings too.
Publishers and YouTube creators, should they be able to opt out of training to get surfaced in Search?
This is a much broader topic. Both laws and regulations will have to evolve. The courts will have to weigh in. It’s important to protect copyright. It’s important to protect fair use. And so these are constructs which will evolve dynamically through that.
But do you want to be in a bunch of lawsuits with YouTube creators? You’re in a lawsuit with publishers in the UK. That rhetoric in that lawsuit is getting increasingly heated. Google has said that the proposed solution is a “free rider charter.” Every year the News Media Association sends me a quote to read to you, and they say, “Google calling us free riders is obviously ridiculous. It’s basic supply chain economics. If the value were really all on Google’s side, they would simply allow publishers to opt out.”
Do you want to be in that same fight with a bunch of creators on YouTube about opting out?
Look, we are constantly — as part of Gemini developing…
We did offer a new opt-out with Google-Extended, and we are in conversations with publishers. We’ll take feedback and over time work through what makes sense. Obviously we are not the only player in a big ecosystem. We are also trying to put out products which are competitive to other products out there. All the publishers will also write an article saying the product is not very good. So it is more complicated than it looks.
You have spent more time thinking about the web and the health of the web and the necessity of the web. Paint me the picture for what a healthy web looks like in an agentic search world.
One of the arguments I’ve made over time and I actually see it playing around a little bit more, is I’ve started using the web more again over the last year to year and a half. All these AI experiences have brought the web back more. There was a time when it felt like… But I always felt the web would be vibrant. In fact, I’ve argued the web is going to be vibrant every year, and I would still argue it today. The web is constantly evolving. I’ve never seen anything as dynamic as the web, which is why it’s been such a privilege to be part of that evolution.
I look at agents, and that is the next evolution of the web, which we will deal with, and I think it will evolve the web pretty profoundly. There will be a lot of debates about what’s okay, what’s not, but people want to put out information, to connect with other people. People want to be connected. People aren’t trying to be in a siloed world, detached. That doesn’t reflect the reality of the human experience. I think the web is going to play as central a role on it as ever before. In fact, the Universal Commerce Protocol, if anything, what we announced yesterday, I think people are slightly underestimating the impact of it.
Actually, can I juxtapose that? There are a lot of muscular announcements about new products, new features, and agentic tools you can use, and UCP and Amazon and Walmart and everyone saying, “We’re going to use a new standard we’re building for shopping,” and all that is very tangible.
And then I/O ended with Demis Hassabis, the CEO of DeepMind, coming out, and he said this thing that I have not been able to stop thinking about. He said, “Google’s cutting-edge research and products will help unlock AGI’s incredible potential for the benefit of the entire world. When we look back at this time, I think we will realize that we were standing in the foothills of the singularity.”
Can you tell me what it means to be in “the foothills of the singularity”?
Demis and I have had long, deep conversations on this topic. In this context, the advent of AGI is what he thinks of as the singularity.
Do you have a definition of AGI? Have you debated it? Do you have an agreement?
We debate it a lot. I think both Demis and I are very close in how we think about things. There is a harder definition of AGI, which is that it has to be more comprehensively able to do a wide range of tasks, including cognitive tasks, in a way that’s comparable. We’ll at some point actually put it out as a company, and we are working on that. But that’s what he’s talking about in this context.
By the way, I think it’s important for us to understand that this technology is progressing very rapidly. Later today, I’ll be going and spending time with our AI researchers, not just in our company, but also amongst the frontier labs. There’s wide consensus that this technology, AGI, is… people may quibble around whether it will be three years, but the technology’s coming sooner rather than later. It’s more important to communicate that because — to an earlier part of the conversation — it’s important that we as a society understand it and are preparing as much as possible.
I asked you this question maybe the first time we ever talked about AI. I asked you if language was intelligence. And the progression here is we’re layering more and more on LLMs. We’re doing longer chains of reasoning, we’re building harnesses, we’re doing all this stuff, but the core technology is still transformers. It’s still the thing Google invented so long ago. Can LLMs get you to AGI? Is that path clear?
The trajectory over the last three years has been incredible. The LLMs of today have evolved in many ways too. We are constantly evolving it. To me, it’s like asking, can computers get us to the way—? The von Neumann architecture is still what powers most computers today, but he won’t recognize the modern one of our TPU pods. Or maybe he would. There’s still a lot of commonality to it. The underlying technology keeps evolving so profoundly. I look at every year we have had major breakthroughs. I mean, you just saw us demo in Antigravity an ability to prompt and create an operating system.
It’s very dangerous for Google to be able to make new operating systems.
We’ll have to make sure we don’t token max on creating… I’ll give you that. It’s fair, but that is the power of what these things are doing, right? There are the top mathematicians in the world, top physicists in this world who are interacting with these tools and using them in important ways, but can these tools fundamentally make novel scientific discoveries on their own? Not yet.
It’s remarkable how much it’s progressed. I do think it has important evolutions to happen, and then there are strong opinions out there in the world about how much of a real understanding of the world you need to take that next leap. I’m pretty optimistic that we will continue to make a lot of progress.
What is your timeline? Is it three years, or five years, to AGI? Where are you at?
I have always answered it this way: I think that timeline doesn’t matter because the rate of progress means you’re dealing with ever more intelligent systems in a profound way. So the way I would answer that question, three years from now, whether you and I call it AGI or not doesn’t matter because it’ll be very, very powerful, and we have to prepare for it.
Sundar, this was great. Thank you so much for taking the time yet again.
Yeah, thanks, Nilay. Pleasure.
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