You have said AGI might be possible to achieve in the next 5-10 years. Give us a glimpse into how the world will change once humanity hits AGI?
Well, once we get to AGI, at least (by) definition, it should be able to come up with new scientific theories, not just prove an existing theory or maths conjecture, but actually come up with new ideas about how the world works. I think if we do that, we’ll accelerate science and human health. We’ll have incredible medical solutions and we’ll be in a world of radical abundance. I sometimes call it a post-scarcity world. That would be the dream if things go well.
2025 has been great year for Google. With Gemini models, TPU chips, Google has emerged from playing ‘catch-up’ to now being at the forefront. What changed within Google and what is the road map ahead?
We’ve always had the best and deepest research bench. Over the last 10-15 years, almost all of the inventions that the modern AI industry relies on…transformers, deep reinforcement learning, AlphaGo…these were invented by Google and DeepMind. So, I was confident, but we had to translate that into shipping faster and…combining that research with our products. I think that’s what we’ve managed to do over the last couple of years.
You’ve said China is quite close now to the companies based out of the US in terms of capabilities. How do you see this arms race playing out?
The Chinese have extremely capable teams, and also have a lot of resources. I think that they’ve caught up a lot. A few years ago, I would have said they were one or two years behind. Maybe now, they’re only 6-12 months behind. But what they’re yet to demonstrate is innovating beyond the frontier. The next transformers, the next AlphaGo, you know…so far all of that has come from the West. So, it’s easier to catch up to the frontier than it is to push the frontier yourself. That’s the part that is the unknown.
AI needs tremendous amount of investments. And only China and the US are seen as being capable of it. How should countries like India approach this era of AI? What should we optimise for?
I think each nation needs to decide that. But I feel like there’s so much opportunity in applying these technologies to revolutionise industries, to do more startups and regional versions of these technologies. So…there’s probably no point trying to create frontier models. There are maybe half-a-dozen providers of that now. One can pick which one you want and for pretty cheap in most cases. The question now is, what are the capability overhangs? I think even (for) those of us who are building these technologies, it’s all happening so fast (that) we don’t have enough time to explore what all of the possibilities are, even with existing technology. So, there’s a lot there to be explored and exploited by any country that wants to apply it to their local strengths. I think India has a huge part to play in this.
Give us a glimpse into when you and Sundar (Pichai) are chatting about AI and how to integrate it into Google’s various products. What are your top priorities right now?
We talk pretty much every day and there’s always a million things to discuss. But the main thing is, the easiest way to explain it is if you think of Google DeepMind, the organisation that I run, as the engine room of Google. That’s how we describe it internally.
So, we’re creating the engine-obviously that’s Gemini – but there are other models as well. Our world models, there’s VEO, our video models, Nano Banana, our image models.
So, these are like the pieces of the engine and our job is to give that to the rest of Google, all these amazing products and services that billions of people use every day and as quickly as possible, ship that engine under the hood into those products and features.
Two of the most important themes from a wider societal perspective: one is job displacement as a consequence of the advancements in AI. And the second is the inexorable need for energy. What do you think about these and how can the AI industry be mindful and solve as you go along on these two fronts – jobs and energy?
On energy, obviously, we’re seeing enormous demands. The AI models are getting more efficient, maybe 10X more efficient every year… The reason the demand keeps going up is we still haven’t got to AGI yet. So, you still need more energy. What I would say though is that, although they’re using some energy, the benefits are going to far outweigh the usage… (AI is working on) new materials, optimising existing grids, getting more out of the same technologies and also developing new technologies like fusion. We’re working with Commonwealth Fusion on containing plasma in the fusion reactors. So, AI in the medium term is going to more than pay for itself in energy savings and energy breakthroughs than it does today.
On jobs, there’s going to be some disruption. Usually what happens, though, is that new jobs get created…that are higher level, more creative, perhaps more fulfilling. That’s what we’re going to see, at least in the early, next five years of the AI revolution.
