Silicon Valley Girl: AI, Tech and Career Growth - How AI Is Solving Problems We Thought Were Impossible | Yossi Matias, Google VP of Research

Episode Date: April 15, 2026

AI is already solving problems scientists said were impossible — and we're just getting started. In this episode, Yossi Matias, VP of Engineering & Research at Google, explains why we're living through the golden age of research and what that means for your career, your kids, and your future.We cover:Why AI agents and vibe coding are actually underhypedHow Google's AI co-scientist cracked a superbug hypothesis in 3 days (vs. years of lab work)Flood prediction in 150 countries — from "impossible" to deployed in 7 yearsWhat Google is building for education, healthcare, and climate resilienceThe one mindset shift to stay relevant in 2026 and beyondYossi also shares what Google looks for when hiring today — and why the ability to adapt matters more than any specific skill.More from the Silicon Valley Girl: Newsletter:⁠⁠⁠⁠⁠⁠⁠ https://siliconvalleygirl.beehiiv.com/⁠⁠⁠⁠⁠⁠Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/siliconvalleygirl/ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/@SiliconValleyGirl⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠linkedin.com/in/marinamogilko⁠⁠⁠⁠⁠

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Hello, everyone. Welcome to Silicon Valley Girl. I have an amazing guest today. And we're going to talk about AI and what's going on in the world. And I think you're the best people to talk to. Could you please introduce yourself? And for anyone who doesn't know you, why should they be listening to you? when it comes to AI in our future.

Well, thanks for having me. It's a pleasure to be here and talk about AI and the amazing things we can do with that. My name is Yossi Matias. I'm head of Google Research. And I'm looking to how to advance research and AI for the benefit of so many amazing opportunities. And you launched one of the tools I absolutely love using

called Google Trends. It's where you go and see what billions of people are searching for. And you also see how they search for these terms based on the season, for example, because I'm in part of my business's language, and sometimes people want to study more, and in August we see that they don't want to study it all like December. So I really like that tool. So before we go into details of research, based on purely trends that you're seeing, what is the thing that you're seeing already, what we're still underestimating, but it's going to affect

our lives in the years' future? Yeah, first we're perhaps in the most exciting time ever, because we're seeing that. you know, in a way, a dream come true of how to take an advanced research in a way that impacts reality in a pace that is faster than ever. One thing I like to call the magic cycle of research is, you know, looking into how to drive research breakthroughs that matter. I like to call it as intentional curiosity. And then taking that research results and applying it back to reality and going this circle and something that, as somebody who, who's been both a, you know, a researcher, scientist on my life,

and also a product guy, you know, Google Trans is actually, was my first project at Google, actually. That's awesome. When I just started. I love the fact that we can now actually identify opportunities, make the scientific progress, and then applying back and have impact. Now, the fact that we can do that at scale, at pace, and at impact that is unprecedented, I think,

makes it the golden age of research. And when I think about how we can take AI and, for example, use it for accelerating scientific research, empowering healthcare workers, empowering teachers, practically empowering everyone in what we are doing, I think this opportunity is greater than ever, and we are beyond an inflection point

of actually seeing this acceleration. So do you think we're going to see some... It's like we're talking a lot about it, but in terms of seeing tangible results, Because we've seen what I've read about as one of the various diseases was cured with AI because they were able to modify the gene. Do you think we're going to see something like that in 2026? Oh, definitely. So, for example, one area that I'm really excited about is how we've built a system called AI coscientist,

which essentially is a way to empower researchers in their own scientific discovery. And the way it works is that a scientist can pause a question and the system which is based on AI agents, can essentially do the work that today you expect typically, you know, research lab assistants, graduate students, postdocs to do literature research, looking into generating hypothesis, ranking them, trying to validate them, and then proposing back to the researcher. And what we found out is that this actually can play a role of an amazing collaborator. So, for example, in partnership with Imperial College,

they were looking into a super bug and looking into some hypothesis of what's actually making it more infectious and they came up with a hypothesis over many years that was not yet published they used our system and they got a similar hypothesis

in just about three days and the system also provided another hypothesis and when I was speaking with one of their investigators the researchers how does he see the experience he said this is an amazing collaborator for him And similarly, we had partnerships with researchers in Stanford and other places on areas such as drug repurposing for AML or hypothesis for novel hypotheses for liver fibrosis.

And when you think about the opportunity for having AI to be practically a virtual lab for every researcher. So you don't need to be ahead of lab after 20 years of research, established research, in order to actually have your own lab. because in the future, every junior researcher, perhaps even a grad student, can have their own virtual lab that helps them ask bigger questions, make progress faster. That's why I think about AI as an amplifier of human ingenuity. It's really a tool that is going to enable many more actually doing that. And we'll already start seeing that. There's a lot of interest in this. There are additional AI tools in advancing researcher, advancing research.

And again, this is something that is already happening. So I certainly expect to see more of that this year and suddenly have impact on areas such as health care and certain other areas. And I certainly expect that to help in material design, in finding new sources of energy in the future, and amplifying both human capacity and AI is an amplifier of human ingenuity.

100%. I'm hoping we're going to get more discoveries because of that because we're enabling basically more people at different levels to do their own research with the help of AI. When it comes to AI being a collaborator, do you think trends like agents and vibe coding are overhyped? Because from my perspective, everyone's talking about AI agents, but making it work for you, like a non-technical person, really hard. Same with vibe coding, right? Yes, you can vibe code a simple website, but have we actually used a product that was vibe coded?

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We're the Hartford with decades of experience ensuring millions of unique small businesses. When it comes to your small business insurance, Thank you. One size absolutely does not fit all. Get a quote or find an agent today at thehartford.com slash small business. I think they are underhyped. Oh, you think so? Yeah, definitely.

And here's my. So first, we should always keep in mind that what we're seeing today is not the future. We're just seeing today. I mean, many of the things we're just discussing now were not even considered just a couple of years ago. So things are making progress very fast. It's true that some of the interface still requires more work. In fact, if anything, you know, conversational experiences,

is the ultimate user interface. So I've been actually passionate about conversational experience for years now, you know, developing at Google, an early AI system called Google Duplex and looking into other conversational experiences because ultimately this is the most natural user interface. In fact, we're all familiar with those who struggle to learn how to use new systems, but anybody can just say what they need and what they want and get the system to do it for them. We start seeing that with the day-to-day consumer part.

And, you know, having been working for over a decade on search, in search, we suddenly take the user intent and we try to give the best information. Now with AI systems, we can actually understand much better user intent and let them actually express what we do. Now, vibe coding is a great example where people can now actually say what they want to be developed. And you can already, everybody can now develop an application that previously required a team. Of course, typically it's not yet ready application to be used and there's more that need to be done. There are actually companies out there that are providing tools to develop those applications in an easy way and we're obviously making a lot of progress on that. Even we recently shared something that we call generative UI that enables you to actually, for any prompt, get a result out of, we have an experiment within a Gemini app called Dynamic View. that gives the full interaction, full interactive user interface

in about a minute for any prompt that you ask, as if somebody was developing an application on your behalf. So only you need to say what you'd like to learn about, and it will sometime even give all the buttons and simulation. And in fact, the technology is now available also in search AI mode. These are, in a way, it's a nascent space. These are first technologies. But if I try to do a little fast forward,

and we make some of those experiences that you highlighted more intuitive, more accessible, more easy, we're actually getting to a stage that every person can actually translate their ideas, their creativity into something that is workable. I think it's extremely powerful. Obviously, for those who are going to go deep into technology, those who are going to spend time on science, those who are going to do additional degrees, there are also many opportunities to amplify. But even for those who don't,

who don't necessarily all have all the technical background, they are going to be able to actually build on these tools and fight ways to innovate and address problems or just objectives that they have. So do you think we're entering the age where everyone is just vibe coding tools that they need every day? Or do you still feel like, because when I think about this, right,

would I, if I need a jump on a call, for example, and I don't know, I have some idea in mind. It is still easier for me to use Zoom or any other tool Google Meet, right? Because it was created by professionals who spent hours and hours and hours building it. Do you think AI is going to get to that stage where a vibe-coded app will be similar to what's on the market? So one notion that I've been quite passionate about for quite some time is what I would call ambient intelligence, which is that, You have technologies that you just use. You don't think about them. They're becoming so available and so intuitive that you actually don't,

you just assume they work, right? Think about Auto Complete, which I also had the privilege to develop with my team over the years in search. People just assume that you start typing and it will just suggest to you. And I remember that people were in the early days, what about this magic? Wow, how does it make a guess? And today you just expect it to be the case, right? And similarly, you can think about so many other technologies.

Think about voice technology, the fact that now you can speak and, you know, you expect what you're speaking to be understood. You can take text, you can listen to it. I remember actually working on these technologies in the early days. This was the aspiration. And now you just assume this is the case. Think about multiple languages. I still remember the day that one of my kids came from school and say, hey, dad, what's going on with? or translate, that line, that sentence was not translated very well. It's actually quite

bad translation. And I was thinking to myself, you know, just a few years ago, having automatic translation of a page was a science fiction, and he assumes this is just available. Now we're much further. Now we're getting to the stage that we can actually hold a conversation. We can consume media in a different language and it will sound in our own language, perhaps the same voice, perhaps the limbs are going to sink. It's not entirely perfect yet, but if you do a little fast forward, it's going to be the technology and AI are removing all these barriers of modality, languages, even interactions. You know, education, which is one of theirs, I think is highly important, is a way that is really poised to be transformed. And we have a recent experiment of

asking ourselves, can we reimagine the textbook? Instead, can we take a textbook and use AI in order to actually give it in different experiences that are going to be personalized and contextualized? So, for example, can I have an immersive, can I take the text and make it immersive? Think Harry Potter. Can I make it conversational? Can I have a sketchbook with that? A podcast.

And by the way, can I have it in a level that is suitable for the audience? So, for example, can I explain gravity? to a 10-year-old who like soccer so that a textbook can actually be releveled to 10-year-old kind of language and give examples from soccer. The answer is yes, we actually have some experiment. And these are early days. So I expect that in the future it's going to be seamless. It's going to be kind of just available to us.

What is the time range that you think is going to be critical when we won't be able to recognize the reality? Because from what you're saying, right, it seems like in five years, What is the timeline, do you think? For all these, for AI to be intelligent enough to, you know, pose questions for research, create those apps on the go, adjust education for anyone according to the level. So I think in a way we're leaving that, right? I mean, we're still early, right?

We're still seeing the worst version of it. You know, there's the saying that advanced technology is indistinguishable from magic. But the flip side of that is. is that what appears to us magical now, we're getting used to it very quickly, and we just assume it's working. So I would argue that there are many things that we're already doing,

that, you know, they were very novel and revolutionized, perhaps at some point, and I would just assume they're working. And we're already in the midst of doing that. Think about the fact that you can actually today use generative AI in order to, you know, express some thoughts and get a summary.

you know, we think of this sort. Think about the fact that you can actually take text and just listen to that. I use that a lot, by the way. I love this multimodal approach for consuming information. And so, in a way, we're in the midst of that, and this keeps advancing all the time. And what do you think is going to happen to our lifestyle? So, for example, let's take, I don't know, social media marketer today, nine to five, doing the tasks. Of course, a lot of them are being automated.

AI can now write text, create scripts. what do you think their life is going to look like in five years? Do you think we're going to slow down, like, do more hobbies? Or because we have more tools, because this is what I feel. When I see how I can 10x myself with AI, I'm now 100x myself, because it never stops the ambition, right? Yeah, so in a way, I remember I was asked, so how do you think things are going to change five years?

And I thought about it, in one hand, everything is going to be different. On the other hand, nothing is going to be different. I've heard that at Davos this year. In a way, I mean, we're humans, right? And what's motivation for what we're doing? It's not really to fulfill a particular predetermined task. We define our own ambitions, our own tasks. Same with learning.

I remember the early days when suddenly Google was made possible for everybody to get facts. And people say, wait a minute, what's going to do for kids? Because we ask them to do homework and collect facts in the library, and now it's easy. Are they going to be lazy? Well, no. because now this is a given that's a tool. So now we expect them actually to go to the next level.

We expect them to synthesize. And now with AI, of course, there's another conversation. What is it going to do? And my prediction is that, in fact, we're just going to up level what we expect. That's why I'm thinking about AI as an amplifier for human ingenuity. Now, what are we going to do with that? That goes back to the motivation. Why are we doing what we're doing?

what do we, probably most of us are spending more time in our work than we should to fulfill the tasks just because we're ambitious about what we are excited about what we can achieve. These motivations are not going away. So in a way, our lifestyle going to change, definitely, but the basics are probably not going to change at all, which is about people working with other people, about solving important problems that they're excited about. The trend that I'm seeing now as a mom, though, is that, that now kids are expected to know how to read when they start school, right? Because back in the day, you're like, your kid goes to school, no letters, no numbers.

Now they're like, oh, I actually have the classes already reading and they're five years old. And you're like, well, okay. You know, kids are already smarter, I think, than the older generation. And I think that the next generation is going to be even smarter because they're going to have AI in their disposal. Yeah. So, and by the way, you know, typically we had to, most people had to focus and learn certain subject and focus mostly on that one. And when they wanted to work across disciplines, they had to meet with other folks and try to somehow do that together. We're going to have, everybody's going

to have a polymath in their pocket. Now, if you want to understand how something you're doing is related in another field to chemistry, to biology, to physics, you can actually get this advice right away from the AI in the right level. And in the future, it's going to be even smarter connecting it to what you want. So thinking about this cross-discipline, and I'm a great fan of, you know, cross-disciplinary, connecting world between science and technology and the arts and philosophy and so forth, I think that we are all going to benefit from actually having kind of everything in our fingertips and also be adjusted to the level that we're familiar with that.

So I think there's a great opportunity here for, if you will, not only, formal learning, but learning for all of us and evolving and a richer experience across everything that we do, hopefully. Yeah. And as a person who's constantly hiring, can you talk about the skills that you're looking for, both technical and non-technical? Yeah, I think it's a great example. So a great question. So for example, when I think about, in a way, we always looked at Google for people who have very strong foundations. And when you think about what are you looking for in terms of skills and in terms of education, one thing that I always thought is critical is the ability to think, the ability to adopt,

the ability to evolve, the ability to actually think about problems and then try to solve them. Now, today, these are more important than ever, of course, because, you know, technology is moving fast. people need to adjust their learning even no matter how experience they are there are new technologies engineers need to relearn you know how to use AI in order to be more productive and people are doing it so the ability to adapt to learn to have a strong foundation is more important than ever how do you how do you learn any tips how do you learn to adapt and yeah I think I think it's something that is inevitable for all of us to learn and certainly if there's

there's one skill that is important for younger generation is to learn how to learn. To some extent, this is not different than I remember years ago. There's a question of saying computer science. Should one learn more programming languages or more foundations, more algorithms? I always thought that it's not necessarily the specific language that is important, but more the foundational principles of how to think about matters. Now, the good news is that we can also use technology to help learning and to help adapting. So, for example, when I refer to AI as an amplifier of human ingenuity and the opportunity for every researcher to be able to use AI in order to actually ask your questions,

it's important to also adapt and learn how to do that. you know, if we really want people to be able to do the kind of roles that today we expect many more senior, people who are much more senior to do, obviously we need them to learn how to do that much quickly. The good news is that I believe that AI can help us with that as well, with kind of tutoring, with feedback. The fact that to write a paper, for example, AI can give you very, the kind of feedback in the past you actually needed the attention of your advisor perhaps to do. Oh, yeah. So I think we are going to adapt in all of these dimensions. And I think humans are what we proved over the years is that we are extremely adaptive to what's required to do.

And whenever we're set up the right goals, the right opportunities, then we see this kind of great results coming out of that. So I think we should build into that. When I say AI is an amplifier of human ingenuity, this is not only a prediction. this is a design goal. This is how I'd like us to build our systems, how I'd like us to see how we're helping the society to actually do that, how we're influencing education

so that our kids can actually grow into this future. And I'm quite optimistic about how we can actually have those next generation solve many other problems in the world. Yeah, because they have more to work with. I just wanted to ask you one last question. If somebody wants to remember, for one thing from this conversation, what is the mindset that they should adopt for 2006

to stay as positive as you are and also relevant in the job market? Yeah, so one exciting thing is about using technology and research is that certain problems that seem impossible are not necessarily impossible. In fact, I've yet to see something that is impossible to tackle. And some of them actually are quite meaningful. Here's an example.

One area that we're using AI quite a bit is on climate resilience. How to address natural disasters. You know, people are turning to Google whenever there are, if you look at Google trends, whenever there's a natural disaster, see a peak. People are coming to ask questions because they'd like to know what they should be doing. And we actually, you know, provided some, you know,

the kind of experiences in search and maps years ago in things such as we call SOS alerts. One thing I learned at a time is that one area that were not very helpful, is an area of natural disaster of flood prediction. Floods are, you know, causing thousands of deaths every year. And when I asked around, older experts told me this is impossible to solve. There are too many variables.

And we decided, well, it's important enough to try anyway. Fast forward, we now have a system that provides flood predictions in 150 countries covering 2 billion people, predictions up to seven days in advance. And from what seemed to be impossible just seven years ago, we have a system doing that. We had actually to drive the research, to work with the community, we published a paper in nature doing that. So we actually took a problem that seemed impossible and made it possible. Similarly, when we think about healthcare, they are, you know, looking into the question,

can we take these language models and that are obviously require more work about being more factual and more trustworthy? in areas such as healthcare, and showing that we can actually bring them to the level that they can pass a style medical exam in a passing score and later an expert level. But what we already saw is how this can be used in the healthcare system. So today, HCA is having a pilot of how to use this kind of language model to help out with and ship reports for nurses that can be hugely impactful for the healthcare system. And so forth, we're looking into how to use AI in healthcare diagnostics. to help healthcare physicians, or to help teachers empowering them.

So the one thing to keep in mind is that we have these technology that we can actually build and address some of the most pressing societal problems in healthcare, in science. We have work on genomics that we can actually help find, you know, the kind of mutations that could make a difference for cancer, you know, discovery and cure, material design. energy. We're working on a quantum computer that in the future is going to unlock many more opportunities. Really excited about that one. And of course, impacting everyday's experience,

how to empower everyone, how to make help address the day to day, both experience work. Also on the creative side, how to be, how to help creators, you know, have bigger impact. So I think these are all the various opportunities for us to build on what we can do. At the same time, we're paying attention also to all the implications of AI. Obviously, we need to be, we're thinking about what we're doing as important to be both bold and responsible, making sure that we're paying attention to possible risk because it's such a powerful technology, see how to mitigate those, how to work towards having a right conversation with the ecosystem. And I'm really optimistic about the fact that we can actually build on these technologies.

and advance them. And again, I mentioned earlier about the magic cycle of research, accelerating that even further. We have also a magic cycle of innovation and opening it up for many more actually to do that. It's not a zero-sum game. It's a really opportunity for innovation to create value.

By the way, on healthcare, we put out a model called Med Gemma, which now have over 2 million downloads, which enables developers develop their own applications on medical capabilities, So how to see how to scale it. Or if I might mention also when I mentioned flood forecasting, but similarly we have storm predictions.

We have a wildfire detection. We have air quality kind of understanding. Taking all these models in enabling asking given bigger questions. We have something called Google Earth AI, where we take all the geospatial models that we have, use AI agentic layer so that people cannot only ask, where is the storm going to hit, but where is this storm or floods going to heat

and what are the most vulnerable communities that are out there? What's the infrastructure that a business shouldn't need to care about? Or how can those who are tracking various diseases in Africa can take into consideration both the predictions, the weather, the census information, and be able to actually take action in a way that is meaningful for the community? So these are all opportunity for us to go on bigger questions, and try to tackle more important problems

and making progress on that. So again, when reflecting back from last year, today we can tackle problems that last year where we were still dealing with much smaller ones, anticipate that in a year from now, we find ourselves actually making a lot of progress and tackling even bigger problems. And it would seem normal.

Exactly. We just take it for granted, which is a good thing. And then we keep on asking ourselves, how can we make even bigger progress, which is a natural way to proceed. I really like the mindset. If you think something is impossible, it might be already possible with AI and all the advances. I have yet to see something that is impossible.

It's just a matter of time and pace. And of course, how to build it in the right way so that we can actually build towards that in a better way. Thank you so much, Yossi. This was really inspirational. Thank you so much. Are you enjoying this clip? On my main channel, Silicon Valley Girl, I share how ambitious people can use AI and tech as their unfair advantage. Whether it's building a business, growing a career, or just staying ahead of the curve as a mom who has multiple things to do every single day.

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