Microsoft Research Podcast - What’s Your Story: Ranveer Chandra

Episode Date: October 19, 2023

In this new Microsoft Research Podcast series What’s Your Story, Lab Director Johannes Gehrke explores the who behind the technical and scientific advancements helping to reshape the world. He talks to members of the research community at Microsoft about what motivates their work and how they got where they are today.Ranveer Chandra is Managing Director of Research for Industry and CTO of Agri-Food. He is also Head of Networking Research at Microsoft Research Redmond. His work in systems and networking is helping to bring more internet connectivity to more people and is yielding tools designed to help farmers increase food production more affordably and sustainably. In this episode, he shares what it was like growing up in Jamshedpur, India; why he focuses his efforts in the areas he does; and where the joy in his work comes from.Learn more:Ranveer Chandra at Microsoft ResearchFarmBeats: AI, Edge & IoT for AgricultureProject FarmVibes6G | Space

. If you're a professional, one of the things I would say is try to go after your passion. If you give your work a bigger meaning than just making money, you'll go beyond the nine to five or nine to six schedule. You'll give it a lot more than just thinking about it as work. . Microsoft Research works at the cutting edge. about it as well. Microsoft Research works at the cutting edge. But how much do we know about the people behind the science and technology that we create?

This is What's Your Story? And I'm Johannes Gehrke, Lab Director of Microsoft Research Redmond. I'm excited by the people I work with and I'm curious about how they became the talented and passionate people they are today. So I sat down with some of them. Now I'm sharing their stories with you. In this podcast series, you'll hear from them about how they grew up, the critical choices that shaped their lives, and their advice to others looking to carve a similar path.

In this episode, I'm talking with Ranveer Chandra. Ranveer is the managing director of Research for Industry and head of networking research in Redmond, and he has been with the company for almost 20 years. His work in systems and networking is helping to bring more internet connectivity to more people and is yielding tools designed to help farmers increase food production more affordably and sustainably. Here's my conversation with Ranveer, beginning with his childhood in India and his experience applying to and studying at one of the prestigious Indian institutes of technology.

So I grew up in India. I grew up in a city called Jamshedpur in India. It's a steel city. It's the only city in India without a mayor. So the Tata's... What does steel city mean? Steel, that's the first steel plant in India. A lot of the steel comes from there. The Tata's, which are the big industrialists in India, they run the city. So it's, I grew up with 24 hour water, 24 electricity, trees on both sides. It looks like a mini Seattle or a mini Palo Alto in India. It's a beautiful city. And I did my schooling there in one of the schools in that city called

Jamshedpur. I did my undergrad in IITs, one of the IITs in India. And then I came to the US to do my PhD at Cornell. So my childhood, we are three brothers and a sister. All three brothers went to, all four of us studied engineering. The three brothers all went to IITs, different IITs, and we studied hard, played hard. We did spend a lot of time in villages, though. Every summer and winter vacation,

we would go to my grandparents' place, which was in another state in India called Bihar, which is one of the poorest states, but my grandparents, place, which was in another state in India called Bihar, which is one of the poorest states, but my grandparents, they were farmers and they had a lot of farmlands in those villages. So I did spend summer and winter vacations in those villages. And how did you end up to study engineering? How did you decide on that? Yeah, so in India, as it happens, these IITs are very competitive exams. So in around during our time, close to half a million people gave the test, students gave the test, and the top 2000 got into IIT. There was a test of physics,

chemistry, and math. Those are the only three subjects. And among those, the top few would try typically computer science. So, it was more, I enjoyed math. That was my, that was what I really enjoyed. And then because I got selected into the IITs, that was, of course, a kind of a dream for many people to go study there. The education level there is really high, really good. And that is how I ended up in IIT. It was kind of unplanned. It wasn't, you know, when I got my, when I got through IIT, I wanted to go to another IIT because the one I went to, Kharagpur, it was close to home.

But I wanted to go to Bombay because it's a big city, Mumbai. It's a big city. Bollywood runs out of Bombay. I thought I could get into Bollywood. Not really. But I did go to Kharagpur, which is closest to, this is the one where it's the oldest IIT. And it was very close to home. So I ended up going there and studying computer science.

And why computer science? Yeah, so computer science, because it had a lot of math. So the way I got exposed to computers was I was in high school. I studied the theory before I got to touch a computer. There was one computer in school. One computer? One computer, and everyone had to go there and see what a computer. There was one computer in school. One computer? One computer and everyone had to go there and see what a computer is. But we did get, we had books

to teach you everything about what binary is, how computers were invented. That was not the time I enjoyed reading about computers. So you did like algorithms on like sheets of paper? Yeah, so you draw the flowcharts. I enjoyed some of the flowcharts. I remember some of the flowcharts like

how do you have the greatest common factor and things like that. I enjoyed some of the flowcharts. I remember some of the flowcharts like, how do you have the greatest common factor and things like that. I enjoyed doing those algorithms and there was that similarity with math. You need to have a good math background to enjoy those things in computers. So I did a lot of programming on pen and paper and someone would correct it. And then we got to start

learning BASIC was the first language that I learned. I really liked coding. What kind of computer was it, actually? So this was, you know, these dumb computers with one mainframe behind. So this was one of the Sun computers back then. Oh, wow, okay. And we had just these dumb terminals

through which you would get access to these. And that was BASIC, not Pascal or anything? No, it started with BASIC. Yeah, BASIC and then Fortran was the next one, then C. So those are the languages that I learned. And computers, because I just enjoyed. I would have picked either math or computers. Those were my two things.

And computers was just fun. It was more, and that was just the time, you know, when you would reserve some time to play a computer game. Pac-Man and things like that. So those things were fun back then. This was late 80s, early 90s. And then what I've heard is that to get into the IITs is super competitive. So did you then study a lot or you played a lot?

That's a funny story. So, you know, when I went into IIT, the interesting thing is once you go there, everyone who comes there is from all over India. These are the people who are top of their class. So everyone else is as good as you. So you then end up studying very hard because that's the culture everyone is coming in there and in the first semester at at IIT I was number one in the IIT all across IIT and then it was like whoa that was that was easy I did a lot of effort my elder brother was there too he was in the last year and he was he was more the

fun kind i was more of the you know the studious kind he came and told me don't do thing a thing b thing don't get into alcohol or party and all of that stuff i ended up doing all of that don't run for elections i ran for elections oh really where did you run for election within the institute within the institute so i was uh the secretary, volleyball, and all of that stuff. So I did a lot of fun as well. So in the end, I was like number three graduating. But I did have a lot of fun too. I did a lot of social cultural things.

I was in the volleyball team and things like that at IIT. Wow. And coming once more back, I mean, sort of get into the IIT. I mean, for me as a German, this is so unusual because we don't have the centralized entrance exam except for medicine. But I heard the test is really, really hard. And actually in your last year of high school, you don't really study for high school anymore. You just study for the test. How is that actually? Yeah. And now it has become even more competitive. During our time, there were fewer seats. There were like 2,000 people from all across. There were five IITs, six IITs back then.

And yeah, studying towards the end. So you start studying just physics, chemistry, math. Back during our time, we didn't have as much tuitions and stuff. I didn't have many, anyone like the last six months, I've had something. But now people go to these other towns, which are meant for coaching people for IITs. And they have these different sections. They go away from their parents. They live in a hostel and all they're preparing for is the IITs.

We don't have that. I didn't have that during our time, but now it has become so much even more competitive. More students take it. And it's like a centralized exam for studying. But it does, you know, in the end, the experience was worth it. If you ask me, hey, was all this studying worth it? I think getting into IITs, of course, the professors are good,

but the students are exceptional, the kind of people you're interacting with, that ambience. And now when I look at my classmates, everyone's doing well. And you find people doing different things. So not everyone is in tech. They go to different things and they excel in that field because of the kind of people that they select into these IITs. So I think in the end, it was stressful, but it was worth it. That's a great opportunity. Yeah, I mean, and then you made sort of the decision not only after

the IITs to stay in India and to take probably a very good job, but to come to the US and learn even more. So what drove you to that decision? Yeah, that was kind of like the way I studied computer science. It was not, at least I had a passion for computer science. I didn't want to do a PhD, by the way, when I was coming here. So you would ask why. So when I was graduating, I got the highest paying job that year among all the undergrads.

And that was a big deal. That was back then Synopsys, one of the EDA companies, the CAD companies, the VLSI companies. So I would have taken that. But as it happens, usually the people who are at the top of the class, they would apply outside and they would come here to study. And that was the reason I had applied. But then the thing I really wanted to do in my career was to be in business. I wasn't really looking to be an academic back then. I was like, you know, I'll go study an MBA. And you started to get a PhD instead? Yeah, no, so I was like, you know, I'll apply to PhD programs and they give a master's anyways.

And after that, I'll go do an MBA. I wanted to be the business guy. So that was the reason I applied. But the reason, the person who had convinced me to come here was a professor at Cornell I had other top schools but there was a professor at Cornell who was a networking guru at that time I won't name him he's still a very good friend of mine so he convinced me to come there I was a fan of his work and I decided to come to Cornell for him I said no to other schools the and then I land here this This was 1999. I send a message as soon as I get to Ithaca saying, hey, I'm here. I would love to meet you. And he says, well, you know, I'm really sorry,

but I left Cornell to do a startup. And then I was a bit, I was very upset. For a few months, I didn't know what am I doing here? I gave everything up. I had other colleges where I could have gone. But over here, I came to study computer science and the person I came here for is no longer here. It was disappointing. But then I was lucky that Professor Ken Berman adopted me. He was like, hey, you have a fellowship. You do what you want. I'm not going to interfere. You just do what you want. And that's what convinced me to do a PhD that in the sense, the first few months were disappointing. But then once I got the freedom, I really, I was like, I was getting paid some money for just learning.

And that bit really got me very excited. The fact that I had all the independence to pick what I want, to work on the things that I want. And that's what convinced me that I don't want to do an MBA. I can do what I would do with an MBA after doing a PhD. So that's what got me to do a PhD at Cornell. It's super interesting because, I mean, if you hear that story for many people, it would be kind of frightening, right?

You come there, well, you have this person who you wanted to work with, and maybe he, there was sort of a plan set up or so. And now, I mean, you have to switch advisors. Okay, that's one thing. But the second thing is, a PhD sounds so frightening to many people because it's like a step into the unknown, right? So your PhD, by definition,

you don't know whether you're going to get there, right? Because it's research. And research sometimes leads you into the wrong path. And sometimes you don't get the result that you want. So how do you deal personally with that uncertainty? For me, it is more, I like the unstructured part of it. I like the fact that I could take it in many directions and grow it. And I want that level of flexibility. And the more I realized, I think problem picking becomes important and can help me a bit with it. So initially I told him I want to do wireless.

This was back in 1999. It's six months into a course. I want to do wireless this was back in 1999 it's six months into a course i like i want to write a paper this is what we want to do on reliable multicast but for wireless systems that time wireless was very new people didn't have cell phones and such so and he said go for it it was worth it and then i started exploring it with another grad student we wrote a paper on it and that was a good learning experience, which I really enjoyed, the fact that I'm venturing into the unknown. And Ken was explicit. He was like, I'm not the expert in wireless. You have to learn it yourself. We did it ourselves. We wrote the paper. It got accepted. And all that really helped me, gave me the confidence that it is possible to explore and do new things. And that's what got me excited. And that's what kept me into the space of networking as well.

It's all about wireless and getting people more connected at low cost. How do you get everyone connected to the internet? And that's the space. I think there is a passion within me around that as well. And the fact that during my PhD, I got the opportunity to go explore, just try everything. And we just kept making the right bets as well with respect to papers and what got accepted. I did an internship at Microsoft Research as well during my PhD. This was three years into my PhD. I came here a few times and that helped me as well. That helped me further. I worked with Victor Ball, who was my intern manager. He was my mentor. And that

helped me further go towards my career goals. And Victor is now a technical fellow in Azure, where he's the CTO of our Azure for Operators effort. And maybe one thought about networking. So networking seems to me like this

field, which is pretty hard because without the hardware, networking doesn't work. But without the right kind of network protocols and software, it doesn't work. So you cannot only do one thing, right? You cannot do only just the software and you also have to do the hardware and they have to sort of co-evolve. How does this work in networking research? Explain that a little bit to our audience. How does networking research actually make progress if both of these have to sort of work in lockstep?

That's a great point, Johannes. And that is one of the things with networking. Right when I was an undergrad, I started getting excited by this layer diagram of networking, the seven-layer diagram, the seven-layer OSI stack. Oh yeah, I never understood that completely. Yeah, it's all the way from the physical. So if you think of the physical layer as one hop, Mac layer. So networking is all about how do you send bits across two computers anywhere in the world.

And at the lowest layer, it's about how do you send the bits across. The layer above it makes it reliable over one hop. That's the medium access layer. The layer above that ensures that you can communicate

not just over one hop, but anywhere on the internet using IP. The level above that, with TCP, communicate not just over one hub, but anywhere on the internet using IP. The level above that, with TCP, you make sure that end-to-end communication is more reliable. So every step, every layer that you go above, helps to make sure that your network is better. Now, of course,

once you start layering things, it makes it harder to interoperate. It makes things inefficient because you're adding headers per layer, which makes it, well, you're consuming bandwidth. You're introducing extra latency. But that's an opportunity. At the very least, what this layer diagram has done

is that it has ensured innovation across different layers as long as there are good enough APIs for each layer to communicate with the next layer. So that is the key part of networking research where over the years it has kept evolving. Every layer has changed. The hardware, we've seen Ethernet go from bits per second to kilobits to megabits, gigabits now it's hundreds of gigabits, we'll soon hit terabits as well, which people are talking about with 6G, to every layer.

When we think of the MAC layer, the TCP layer, all of those have been evolving and that has led to applications. A lot of times, a lot of people just worry about the applications. Is my media application, can I watch things on Netflix? Well, underlying that is all the bandwidth that the network provides. Got it. So one way to think about this is that as long as I make my hardware have the same APIs, I can even go, I can sort of significantly evolve my hardware and all the other parts of the network stack will work. Exactly. So you could be innovating on the radio, you make that radio faster, but as long as you keep the APIs the same,

the TCP layer would work as is with the layers in the bot. So I hear this magic word 6G from you a lot these days. Can you just explain a little bit what is 6G all about and why is it interesting? Yeah, so with the network, we've seen these standards evolve over time. Every 10 years, we see from 2G to 3G to 4G. Why 10 years? 10 years is usually the time it takes to come up with a new innovation, drive the standard, drive alignment across different stakeholders to see this is what the next standard should be. Because then once you finalize the standard is when you'll have all the other vendors,

like people who build the hardware to base stations, to cell phones, to modems, everyone can then align and build something. That is, you have your Qualcomm modem talking with, say, an Ericsson hardware with the AT&T carrier, which is running on Azure Cloud. That's why you have the standards. Yeah, so that's why we have the standards, which have all been a 10-year timeframe. With 6G, we are looking at 10x more bandwidth.

Your throughputs will go much higher. And one-tenth the latency. Can you get to sub-millisecond latency? And the kind of scenarios that we are thinking of are, we can think of completing the feedback loop, like robotics and so on, where you're getting the information, you need to send all this to the cloud

because this is huge amounts of information. You need to act on it using AI and you need to send the feedback so that your robot can perform in time. This could be something in a racetrack, something on the roads, or it could be in the middle of a farm. So this is what the vision is.

And along with that, the other vision that we have with 6G is to bring internet all over the world. That is right now, still around 40% of the population in the world, that's close to 3 billion people in the world, doesn't have internet access. They just don't have access to the internet. And why does 6G help with that? 6G should make connectivity more affordable.

So 6G is also cheaper, even though it's faster and low latency? That seems contradictory. Why is that the case? No, so I think it'll be high speed and low latency in areas where it is needed. But the other feature it should bring in is affordable connectivity in regions that are not connected. And a lot of it is in the emerging markets where the that are not connected. And a lot of it is in the emerging markets where the people are not connected. And it is not just people. Now we're also talking of people and things.

Because if you think of the entire world's surface, close to 80% of the world's surface, which includes ocean and land, doesn't have terrestrial internet. So how do you bring internet connectivity throughout the world? That's one of the challenges that people are looking at with 6G, along with some of the other things

around sustainability, security, trust. These are all issues as well. But at an underlying layer, the fundamental thing we want is high speed, lower latency and connectivity, affordable connectivity everywhere. We can't be leaving 3 billion people in the world behind with no internet

when it is so central to the way we are. It defines everything we do. And yet there are so many people in the world who don't have internet access. You mentioned one word, farm, and we'll get to that in a second. I just wanted to ask one more question because it just sounds a little bit like magic to me

that you get lower latency, higher bandwidth, and lower cost. Why don't I get this with 5G if I just push the hardware along? This is where the research would come in. When you think of the standard, we think of different components of the standard. One part of the standard

is the spectrum. Which part of the spectrum do you operate on? That could define the throughputs that you get. Now, the high speed usually comes with a limited range as well. Like, you know, like one of the technologies that people are talking about, we're investigating here at Microsoft Research as well, is terahertz networks. This is a part of the spectrum where you get huge amounts of bandwidth. It's still following Shannon's law, but it is just in that part of the spectrum that until now people said

couldn't be used for communication. But what we're showing is that, well, you could. You could use it for communication in that part of the spectrum. Once you get that bandwidth, it also helps us reduce latency by a significant amount. So that's one thing people are looking at. Along with that, another technology people are looking at to overcome this problem of short range, like 100 meters, to go beyond that is smart surfaces. So one of the things we are building is rather than just have these base stations, what do we, if we have smart surfaces, which are programmable and can then make sure that wherever people are, wherever things are, you can provide connectivity there by channeling the signals in that particular region. Along with that, people are also looking at for affordability people are looking at different

other forms of community previously we've looked at other parts of the spectrum like lower error hertz is going further closer to light that part of the spectrum the other part of the spectrum is lower in the tv spectrum for example a radio spectrum once you go lower in the spectrum your connectivity can just go really long distances so one of the innovations that we had done a lot at Microsoft Research was on using TV spectrum to send and receive information. The benefit is this spectrum is not being used in many places, and using that, you can provide very low-cost

point-to-multipoint connectivity in different regions. Makes sense. And so 6G encompasses all of those? 6G would encompass. Right now, it's still being defined. It's still early. But as far as research goes, we are working with the community on all these aspects. The other aspect about 6G is AI-driven networks. So can you make your networks much more intelligent? Right

now, you define these networks in standards, and the standard is written, and that's what is implemented. But you could adapt parts of it based on what's happening around you. And you can use the spectrum better. You can use it to make sure that you're getting much more efficiencies in your system. You can prioritize things better. So that's, again, one of the other themes that we're investing in and a few of the other research labs are investing in as well. Super interesting.

And I mean, you mentioned this word farm before. You're, of course, known for farm vibes. And maybe just explain very briefly what Farm Vibes is. And then also explain, you know, you started out here doing this in Microsoft Research, but then you actually went to a product group. What made you take that decision? And, you know, you're actually now finally here in Microsoft Research again. So maybe tell us a little bit about that journey. Yeah, so I'll start with why did I even pick agriculture, right? So as I said, I did spend a lot of time in my grandparents' farms in Bihar. This was in North India. So they used to farm

wheat, sugarcane, rice, and they had farms there. And back then, I did not like anything to do with agriculture. So I used to go there with my brothers and sisters and you know i i did do a like i played kabaddi there i learned how to ride a bicycle with the people kabaddi is like a it's a funner form of rugby not not even you know it's it's uh there are two teams and you essentially have to bring the other team down so uh and it's you play it in the sand you get really dirty playing it. Growing up in those villages, it was fun. But spending time in those villages,

I didn't really look forward to them. The reason was that, you know, the rest of the year, you are in the city, which is maintained by the Tatas, which has water, electricity, clean roads, everything. And then the rest of the three,

four months I was in this village, which did not have electricity. They didn't have toilets. If you have to go to the bathroom, you have to go out in the fields in the middle of the night, in the winter, it wasn't what you'd look forward to. But that's one of the things that I grew up with. But one of the things that really stuck with me was the poverty that exists in these villages. Like one of the times my mom, she did some prayers. She had an offering and she left it outside. And there were

a group of kids. They hadn't had anything to eat during the day. They were just there to grab something to eat. And that has been something that has really it's been in my mind. It's during my undergrad and even over here. One of the one of the things I always want with any project I'm working on is this bigger mission. Things that can impact the people I grew up with and be it with TV white spaces for providing internet connectivity to what I saw was very primitive forms of agriculture. These farmers, they would do hand-based seeding. Over here, you use tractors that they would go with the hand and put the seeds. They would use bullock-driven

tractors. Till they would just go with a bullockock they'll put this hitch on it and then go till the fields and though this it's very primitive so what we what we want to do is to enable data driven agriculture and the bigger goal here is to help address the world's food problem the world needs 50 percent more food compared to today's levels and in order to grow that 50 percent more food we need to get there not just food we need to grow good% more food, we need to get there, not just food, we need to grow good food, nutritious food. And we need to get there without harming the planet. Soils are not getting any richer, the water levels are receding. So that's the big picture of what we want to do with FarmBeats. Our goal is, one of the most promising approaches to get there is that what we call data-driven agriculture.

That is, can farmers use data and AI to remove guesswork as part of their farming operations? You know, the farmers that we work with, like even when I was doing networking here, I would actually go and volunteer in farms here and cold call various farmers. What I realized is that these farmers... Like here in Washington State, right? In Washington State. In fact, there's a Starbucks right here. There was a barista who knew me. She said that, hey, I'm going to Spokane, Eastern Washington this weekend. If she's in Eastern Washington, maybe they farm. Who farms there?

She said, my grandfather. I was like, can you connect me to him? So I just cold called them. I talked to a lot of farmers. And what I realized is that these farmers, they know a lot about their farm. They've been farming there for a long time. Yet a lot of decisions they make is based on guesswork. That is where all the data-driven farming piece came in. So through FarmVibes and previously FarmBeats,

with FarmBeats, we built a data platform for agriculture. Then I had moved over to the product side. We shipped it as a product. We announced partnerships with Lando Lakes. We announced partnerships with Lando Lakes. Their agriculture platform is now running on that. We announced partnerships with Bayer Corporation, with USDA and other organizations as well. Then while I was there, what I realized is that the engineering team is now on track. They are delivering this product, but that's not enough to help us address the world's food problem. We need to add intelligence on top of what we are building. We need to bring all the innovations that we're doing in AI for this field. And that was one of the reasons.

And of course, working with you and the fact that networking is one of the key components that can help us, networking and AI. So that was one of the other reasons why I came back. And with FarmVibes, that's the problem that we're addressing. With FarmVibes, it's the farm intelligence feeds. It's the intelligence that sits, that's the problem that we're addressing. With farm vibes, it's the farm intelligence feeds. It's the intelligence that sits, that can light up scenarios, these scenarios that we talk of when we think of data-driven agriculture, sustainable agriculture. The kind of things we want to do is help a farmer take the right decisions for what will make them more

productive, what will make them reduce their emissions, what will help them sequester more carbon. These are the kind of questions we want to have a farmer answer. And some of that is very fundamental research. We've come up with ways to see through the clouds, to do very hyper-local microclimate prediction, to combine different models to make much more accurate predictions to poor farmers. And that's the kind of thing we're enabling as part of Farm Vibes.

Well, and so just curious, I mean, here in Washington State, what has grown on those farms and how have you helped so far? Yeah, so there are farms here. There's one farm in eastern Washington. We work with this farmer, Andrew Nelson, who's a fifth generation wheat farmer. This is an hour east of Spokane. So if you go to Spokane, you have to drive another hour. It's interesting when you go to Andrew's farm,

like we're about 15, 20 minutes from his farm and you lose internet cell connectivity. It's interesting, when you go to Andrew's farm, like we're about 15-20 minutes from his farm and you lose in an air cell connectivity. It's completely gone. Yeah. So you're like off the grid. And then you reach his house and then he set up

this TV white spaces thing. He has some connectivity in his farm. Through satellite or TV white spaces? TV white spaces and a fiber to his home. So there's a fiber

that he's paid to bring fiber to his home and then that lights up the area around his farm using some of the technologies that we have been inventing here. And with andrew this is just one use case but you could replicate it across other farms as well he uses some of the techniques throughout his farming life cycle all the way from planning what to farm to planting what to plant where to plant

to in production like for example doing chemical application where do i apply herbicides do i need to spray pesticides where do i spray iticides? Do I need to spray pesticides? Where do I spray it? Rather than spraying it throughout. To harvest, that is, when should I harvest? How should I, what route should I take? To post-harvest, monitoring things and deciding when and where to sell certain things to gain, to get more profit.

So he uses it throughout his farming life cycle. And he's seen a lot of benefit. Like Andrews talked about how in one part of the farm, he could double his yield life cycle. And he's seen a lot of benefit. Like Andrew's talked about how in one part of the farm, he could double his yield. Double. I was just going to ask actually how much benefit he got from it.

Double the yield. And in another part of the farm, he's talked about 40% reduction in chemical costs. You know, for a farmer, one of the input costs is chemicals. And using this precision techniques that we built,

Andrew's been able to save 40%. That's huge. It's probably also good for the environment. It's good for the environment as well. He's not putting in more chemicals than are needed. So these are real use cases with farmers in Washington state. We're also working, for example, we announced a partnership in India, in Maharashtra. This is one of the centers of excellence that's being put up for farm vibes.

So this is, again, they are building AI capabilities. This is across Oxford University. There's an organization in India called Agriculture Development Trust and Microsoft. And working with, of course, Microsoft India, our sales team there, they've set up the center of excellence in a village called Baramati in India, where they are going to be taking the same techniques we built and adapting it for smallholder farmers in that region. So really excited about the value it brings. Ranveer, it seems like you, you know, here at Microsoft, you had the amazing opportunity to really have huge impact.

You know, you started on research and delivered a product, now even extending the product to more use cases. Do you have any career advice for our listeners, given where you are and where you're going? Yeah, and as a student, if there are students listening to this, I would say consider going after a PhD. It gives you that exposure, the opportunity to learn, to dig deep, to know a lot about the field. If you're a professional, one of the things I would say is try to go after your passion.

If you give your work a bigger meaning than just making money, you'll go beyond the 9 to 5 or 9 to 6 schedule to make that happen. Like, you know, Johannes, one funny incident is over here. Working at Microsoft, most people sit in front of the computer. When I had started working on FarmBeats, every day I would be driving to this farm. There was another farm about 40 minutes drive from here. Every day, summer or winter, I would be driving to this farm. There was another farm about 40 minutes drive from here. Every day, summer or winter,

I would be driving there to do the experiments. And I would go there and a few days, especially when it rains, it gets really gloomy. And you have to go in booths to a farm that is muddy, half flooded. I'd be like, why am I doing this? I could be sitting there. And then the way I would argue to myself is,

even if 1% of what I'm doing works, it will help the lives of so many farmers worldwide and then that just gave me the extra energy to go even more to to just give it everything that i have to make that difference so that's something which i tell students as well give whatever work you do you're working in ai you're working in systems you're working in in building the next plane or building the next ship, give your work a bigger meaning, you will enjoy it. You'll give it a lot more than just thinking about it as work. And you're right that at Microsoft, we get that opportunity to make that wholesome impact. That

is, as you did as well, we get to go to the products. If something ships as part of a Microsoft product, it touches the lives of so many people. Like one of the projects I was with was Xbox. For the Xbox, when I designed that Xbox wireless controller protocol,

now over 100 million people use it. And one of the most common congratulatory messages I get is still around the Xbox. When I'm giving a talk, someone will come and say, my son said thanks to you because you helped make the Xbox successful. So that's one of the opportunities

we get. But not just that, we get the opportunity to come to research and think bigger about the problem, take it to a different level, and then influence the next generation of product. So this is, thank you. I think this is an awesome place to work, to realize that mission, that vision of what we want to achieve in our lives. Yeah, I think, I mean, it speaks so much to me because there's something that I was also really excited about, making the transition from a university here to Microsoft as well. Thanks again, Ranveer, for the great conversation. Thank you, Yannis. you