We are seeing an incredible technology taking shape today in the world. Look at healthcare. If you look at agriculture, this technology can really help India advance in a number of different areas at pace.
If proteins were the building blocks and were the ingredients of life, the key question now is to decipher the recipe book of life, our genome. The millions of dollars and multiple years has been transformed into one click. So you go to the AlphaFold database, you put in your sort of protein and you get the structure out. Exactly, and in fact AI's biggest potential is in the democratization of science.
We are delighted to be joined today on Money Control by Pushmeet Kohli, one of the hottest researchers in the world on AI. He is a distinguished scientist and VP of research at Google DeepMind. His teams have developed many pathbreaking innovations on AI including the Nobel Prize-winning AlphaFold model for protein structures. He's done significantly pathbreaking work across biology, across materials, across fusion, math and software, and delighted to have you with us, Push, joining us from London for this conversation with Money Control.
Thanks, Nalin, for having me. It's a real pleasure. I will not describe myself as the hottest researcher, but thanks for the description.
So, Push, we are talking at a time when there's a lot of flux, the great geopolitical flux. The India-US trade deal has just been signed. There's been a lot of debates around movements, tech, around deep tech, around AI and so on and so forth. Let me begin by asking you, what is your advice to young Indian researchers? Should they come to the West to build foundational models or is it now possible to do world-class AI for science research from India?
Yeah. Nalin, I mean, it's a time of a great transformation. We are seeing an incredible technology taking shape today in the world. AI is going to revolutionize the world. It's going to sort of let us make breakthroughs in a number of different areas. I particularly sort of focus on science and we are seeing a lot of a huge transformation happening in how science is happening in the research lab today. AI is really accelerating science, democratizing science and expanding what is what we are seeing around the world. Now coming back to your question in terms of what's the advice I would give to youngsters today, the clear advice is you have to leverage this technology, you have to understand it, you have to understand its strengths, but you also have to understand its weaknesses. And in terms of how you should look at sort of AI and where you should sort of work, I think the key idea is that you can you have to think about the application. How is this technology going to affect the real problems that people are facing today? And in that sense, I think India is in a very good position. It has a lot of sort of opportunities to take this technology and bring benefits to the whole country. Like if you look at healthcare, if you look at agriculture, this technology can really help India advance in a number of different areas at pace.
Right. So, Push, Google is of course stepping up its fundamental AI research in India across a range of real-world challenges in areas like agriculture, maternal health, patient care, disease treatment and so on and so forth. So looking ahead, what role do you see India playing in Google's future research as it addresses some of the biggest challenges and within the larger AI ecosystem globally? I mean, you know this constant debate about whether India should focus more on services or more foundational models. Where do you what is your thinking on on those debates?
Yeah, I think as I mentioned, I think foundational models are a key technology. Advances will happen. We have a lab in Bangalore. Google DeepMind has a lab in Bangalore which is making fundamental sort of contributions to Google's foundational model Gemini. And not only sort of improving the foundation model, the lab is also thinking about what are the different applications that will be affected by these models. So in agriculture, we are really thinking about how do we organize India's agricultural data and building a foundation and unified landscape understanding that can help not only the planners but also sort of farmers really get the best out of this data. The other sort of opportunity for India is to leverage these foundational models to understand the different languages that India has, right, and to bring in that language into that language data into the foundational models. And that's another sort of key element of the work that our Indian lab is doing.
Right. So, Push, across biology, materials, fusion and math, where do you think AI has delivered the most unreasonable progress, for want of a better word?
So, so there I'm really partial to science, Nalin. Like, I lead the science and strategic initiatives unit at Google DeepMind, and one of the very first projects that we started almost eight years back was on using AI for this amazing problem of protein structure predictions. Now, proteins are the building blocks of life. These are the Lego blocks that make you and me, and understanding their function and shape is an incredibly important sort of problem to tackle if you want to develop new treatments for diseases and so on. And our AI model AlphaFold made a major breakthrough at the height of the pandemic, in fact, in 2020, where when we released AlphaFold 2, and since then it has been used by 3.3 million researchers across the world. People have been sort of using it from developing better vaccines to coming up with new treatments for neglected tropical diseases to coming up with enzymes that can deal with plastic pollution and making sort of breakthroughs in fundamental biology. So you can see the real impact that this kind of technology can have over a large spectrum of applications.
So what is the, in your view, what is the next biological frontier for AI to crack?
I think the key sort of challenge now is if proteins were the building blocks and were the ingredients of life, the key question now is to decipher the recipe book of life, our genome. Our genome is our DNA, is basically it captures a lot of information about about life, about how we sort of develop, how what diseases we are susceptible to. And yet scientists have over the last many decades have been incredibly sort of successful in building technologies that can read the genome. We completed the human genome a few sort of almost a decade back, but we are yet to really decipher it and understand the meaning of the genome. So that's one of the grand challenges that we are taking on. We really want to understand what is the effect of every possible change in our genetic code and what what are the implications for diseases? How can that information be used for not only diagnosing diseases but coming up with better sort of treatments?
So, Push, do you think that AI can be this great equalizer in science? In many ways it is becoming one. But are we in a sense moving to a future where a researcher in a small Indian university with just a laptop and your models can compete directly with the biggest labs in the West? Is that is that possible or is that not really, you know, there's a big gap between the rhetoric and the reality?
