 Good morning, everyone, and welcome to the first panel of the Tech and Innovation Summit 2021. In this session, we are going to look at deep tech and its impact on the future. Artificial intelligence, machine learning, SaaS, cloud, these are possibly omnipresent, but users may not even realize at the ease with which they found a solution on the Internet because of one of these technologies. And increasingly, these will have more stay and impact on our lives. In this panel, our esteemed speaker will help us understand how the future is going to be shaped by this technology. I am Saurav Kumar, editor special for this entrepreneur media. And with me today, we have Mr. Sopnil Jain, co-founder and CEO also.ti. Mr. Rupan Aulak, managing director of five ventures. And Mr. Sandeep Ardova, managing director of Asia Pacific and Japan at Raksit State College. Welcome, everyone, and thank you for joining us today. Thanks, Saurav. Good to be here. Thank you so much. Rupan, I'll start with you. Just on a light note, as I was mentioning that recently I've noticed that as a journalist, most startups include these words AI, ML, deep take, clouds, somewhere in their pitch notes. Now, maybe they're just using it deep tech service somewhere in the system. So have you also noticed the same? And if so, why is it so? Is it because it's inward right now? And how do you, as an investor, separate what is read and what is shared? Sure, Saurav. First of all, thanks. Yeah, I think it's a very pertinent question. And to address this, let me first tell you a little bit about five ventures. So we are a deep tech fund. So we have actually since 2017 been investing in AI-led companies. And over time, we've also started looking at other forms of deep tech innovation. So this context is important because we are a specialized fund. So we understand AI. So to your point, yes, over the last few years, when we felt we were sort of like the pioneers in AI and we used to see a few companies in AI, but over the last two, three years, it's like every pitch deck has AI in it or other deep deck mentioned. So it has become sort of like a buzzword. I think the trick here is to understand first thing, what is the problem being solved? And is AI really needed for it? So it's not needed for everything. Of course, you can really bring in a lot of efficiency, scale and other advantages using AI. But what's important to understand is how this technology is solving the problem that the startup is claiming to solve and is it really necessary? So that's the first level of understanding that one needs to have. Next is, I think as a, you know, since we've met so many companies, we know how to, let's say, you know, separate the from the shaft and be able to understand the nitty-gritty. So and we do that by feeding layers, trying to understand at a high level, what are the kind of models being used? What are the kind of architecture is being used? So you get to understand a little bit from those discussions, how much, where exactly AI is being used and how much is actually being used and how much does the founder really know about it? So that's the approach that we have and we do have an advantage there. But for anyone else who probably doesn't have that advantage for them to understand whether, you know, the whatever is being claimed in the pitch deck is actually true or not. There are a couple of ways in which one can actually, let's say, hack and understand. So one would be to look at the background of the founders or let's say the founding team and understand where all, you know, people have actually used AI in their past experiences and whether that was a critical role. So that's something, you know, is certainly can be helpful. Second way of understanding that is just talking to experts and, you know, external experts because now there are a lot of people both in academia as well as, you know, in the industry who understand AI pretty well. So that's another way of just reaching out, getting help from people to understand whether AI is actually being used. But to your point, yes. And what about ordinary laymen, consumers like me? How do we, like someone says that, you know, we're offering an AI based solution and a middle based solution. What do I do? I mean, do I go to you? Do I ask for food? Do I ask something? What do I do? As a consumer, you don't need to understand. As a consumer, it doesn't matter what's in there. Right. As a consumer, you need to understand that your problem is being solved, whether it is being solved or not is what is critical and whether it is easy, the product that you are being sold. Whether it is easy for you to use or not. That's all. What is, you know, making this possible engine at the back is, I mean, not the consumer's problem. So, you know, something Rupan said that, you know, they look at whether AI is required to solve a problem or not. And you provide those solutions. So, how do you determine that, you know, whether if someone has approached you, whether you really require it or not, because your business requirement would say, okay, let's give him a solution, you know, for whatever he needs. But that may not be needed. So, do you ask him that you don't really need it or you customize it? How do you decide on where to, you know, just switch? You know, absolutely. And I think Rupan put it in the right way, which is go with the problem, not with the solution. So, what's happening these days? At the end of the day, like, you know, when you talk about technologies, right? Technology is a means to an end, right? People confuse this. Me telling you that M&EI company doesn't really do much, versus I would rather get, and you will also get a lot more value if I told you, you know, what problem I'm solving, right? Versus saying, like, yeah, I'm a SaaS company. I'm a cloud company. I'm an AWS company. It doesn't really matter to you. You're like, okay, sure. You might be deployed on AWS or you might be deployed on GCP. Who cares, right? It doesn't really matter to you. So, going back to, you know, how we make sure that, you know, we are using AI when it's needed is we always have this five-by process in the company, right? Whenever someone comes with us, with any idea or any approach, like, hey, let's do this, right? There's a natural tendency, and this is humans, right? There's a natural tendency for us to talk about ideas and solutions, and less about problems, right? So we start working backwards from there. The first question we ask is, like, why do we need to solve this problem? And then you keep peeling back to five-wise, and you will get to a stage where we start talking about the problem, right? Instead of saying, hey, let's build a great model which detects sentiment from the speech, you start working backwards to what user problem and then what business problem does it even solve or it doesn't even solve. And when you do this exercise, you realize, do you even need to build something? That's number one. And then if you need to build something, do you actually need AI? Or, you know, someone started with AI because that was really cool. So I think the five-by process is something that we use at Observe to make sure, you know, we don't focus on, you know, humans always start in the rear end, so features and functionalities. And we work backwards from five-wise to get to the problem of it, right? So we don't become a company which uses AI as a hammer, and they're trying to find nails versus we work backwards, which is, like, hey, we have this problem. It could be a nail. It could be a screw. It could be something. And then we find the right solution. So that's how we at Observe make sure that we don't end up using AI for everything when it doesn't even matter. And Sandeep, apart from these words like AI, ML, robotics, there's another word which I often come across as cloud-based convention. And we have integrated it. So the same question. Do you also, you know, kind of see these words being used or are they actually being deployed and they're actually required to be deployed for any problem to be solved for any company to maybe move to the next level? So actually, you know, we've been in the industry now for 23 years and we kind of created the whole web hosting category. And we've seen the startups kind of, you know, move through the value chain, right? And, you know, it kind of tells my age, but ten years ago I was in a symposium where this person said, let me start with mainframe and then mainframe to client server architecture, right? But that's really stuck with me because, you know, the way the person was talking about and he was coming to a particular point in time of a particular technology. That, you know, in the same way you can start thinking about the evolution of cloud, right? So people talk about being on cloud, especially, you know, if you're a younger company, I wouldn't even say younger company, but you know, even the whole, there's another buzzword that has got created, which is digital native. And every company wants to be digital native, right? The most traditional of companies want to call themselves digital native, right? And one part of that is are we cloud based, right? At the end of the day, it is really about the customer problems that you're trying to solve, the kind of applications that you're using, and hence the underlying infrastructure that you need, right? Hey, quite a number of companies still host their infrastructure on mainframe. You know, we thought ten, fifteen years ago that mainframes would die, but mainframes still exist and the sales are still growing, right? They're not going anywhere, right? It could be that. It could be any other high-performance compute solutions, or it could be more and more, it could be a cloud-based solution from one of the hyperscalers, right? And of course, cloud-based solutions, you know, have the advantage, and Swapnil would know this. He can put in his credit cards, spin up an environment, and off he goes. You know, I started my life as a SAP consultant, and I remember that every time we had a new project, we had to wait for three months, because we would wait for the server to come in, and then everything to be built up. These days, you know, in eight hours, you can get the environment set up, and then you can start doing what you need to do. So the time to outcomes has become much, much faster in the world of cloud, right? And in the way you use technology. And that's why everybody wants to say that they are cloud-ready, or they are hosted on cloud, but there's scenarios out there that are using a lot of other technologies, right? So it's really the kind of problems that you're trying to solve, and hence the kind of underlying infrastructure you need, that really determines what is the right solution for you. It might be a cloud from one of the three or four or five hyperscalers now, like if you count the Chinese ones, or it could be still that old mainframe on your data center. Any trends that you've observed in the previous adoption in the, especially in the past two years, we were stuck with, you know, when the pandemic started because, you know, everyone knows that everyone's digital transformation plans have been, you know, fought forward by ages. So have you seen any change, distinctive change, especially regarding to any particular sector where you have seen something that, you know, they have started adopting more and more of these solutions? Actually, I would say, you know, that changes across sectors. So, you know, there were people who are very attached to the data centers because that is one thing that they could point and say, in this company, in IT, I own this data center. There is that space, there is the power and cooling, right? And people could touch and feel, right? And there were a number of customers, especially in India, who said, you keep talking to us about cloud, but can you touch and feel it? I have this and that if nothing else remains, at least this plot of land will be mine, right? That mode has changed across the country, right? As people have not been able to reach to that, those plot of land to do the things that they wanted to do. And people have started realizing how easy and simple it is to operate, you know, on one of the hyperscalar platforms that that barrier has really gone down significantly, right? Now, of course, the regulatory environment has to catch up. So there are still industries where you know, data privacy, data security, compliance, governance are still big issues and the people are still reluctant, though they're trying, but they're still reluctant to move to, you know, public cloud platform. But even there, the barriers have got lowered, you know, because of what people have seen over. So I wouldn't say and it's one particular industry and it's, you know, it's a transformation that you see across industries that is also driving up the skill shortage because suddenly you need so many people in that skill set that all around the world that you're seeing that shortage and you're seeing that shortage in India as well. Yeah, we're seeing the shortage and we're seeing the kind of the kind of things people are doing to attract talent right now in India. That's crazy. I mean, offering opportunities and everything. So Rupan, I'll come to you. You know, Sandeep just said that you know, it's a cross the sector where, you know, this adoption is going up. So and that, but there are regulatory hurdles still that needs to be taken care of before we need before any small company large company whatever thinks about what has been your experience who do you really see companies which are which do have a solution but still are reluctant because they think that there could be this regulatory or there could be these problems they might face. Yeah, so that sort of totally depends on the industry the sector itself. So if we talk about enterprise sector right so there's so much of acceleration of transformation, digital transformation that has happened but no no real regulatory hurdle except for making sure that you know, you're adhering to privacy related compliances regulations and all localization localization all those things but which are let's say I mean still in progress but more or less standardized so today you can go for certain certifications where you can claim that you know, the data is safe or you know, the security everything the frameworks are being adhered to right so that's from the enterprise perspective but if we look at other sectors for example healthcare right their regulatory challenge of course becomes more important especially if you want to go global in India it's it's still something that you know people can commercialize their products you know if they have let's say a no objection certificate from the market but if they have to target the global market then it becomes very difficult because you have to go through the C or FDA approval which actually also has become much more streamlined and let's say the process has in itself become much easier and quicker then what it would have been pre-COVID days so that acceleration has happened even from the regulatory front so so just going a little bit deeper into let's say a case like healthcare so there in you know you see a transformation both from what the companies are offering to what the consumers are ready to try and adopt so pre-COVID there was a lot of hesitation towards going for online consultations or let's say prioritizing your health but now all that has changed because we see a lot of telehealth platforms that have come up and are becoming very successful there is a growing need for telereporting where a doctor doesn't have to be present in person to be able to come up with a report or certifier report and all this is being you know enabled by DTECH so technologies which are not just you know of course cloud and everything really is important but also being able to digitize if it's pathology being able to digitize the slide so that a pathologist who is sitting in a remote area is able to come up with a diagnosis so those are the things that are happening and there is also from consumer perspective a lot of focus on wellness and that's why you have a lot of these companies that are doing fairly well in terms of both fitness, nutrition and all the preventative healthcare angle so yes there has been a very good let's say push for you know transformation in healthcare as well as other sectors and regulatory will continue to be a little bit of a challenge in these sectors but we are seeing really good progress from that angle as well. You operate from so do you think these are problems specifically for this geography or do you think it's easier to operate from there and then enter this geography yes I think I'll caveat that answer by saying that we don't have too much experience selling into the Indian market but I can give you perspective on selling into the US market so similar to Indian market the US market you won't have a lot of resistance on cloud some of the big banks like Capital One is actually one of the biggest customers right out there. One of the biggest streaming service around the Netflix is built on AWS right Dropbox used to be built on AWS so the US market has seen a lot of I would say sensitive industries such as banking healthcare data in terms of Dropbox being on cloud right so people here and businesses understand that cloud is safe cloud is secure cloud provides high SLA so people here understand a lot more and then I would say maybe in India it's my guess but so US you don't see hesitation so much of you know on premise versus the cloud but that being said you still have to go through a bunch of certifications right so if you're selling into the healthcare market you have to make sure you know let's just focus on the US market for a bit that you have to go through HIPAA compliance your HIPAA compliant you know you have to deal with if you're dealing with medical records you have to be extra careful around them and then when you're selling to these customers one of the things we see is they require us to make sure that none of our employees outside of US access this data right so there's two parts to data residency which is they require the data to stay in the US servers and then also no one can outside of US can access this data right so so while the people here are a lot more open to cloud you know the the regulatory bodies have done a good job of like if you want to sell in healthcare go and make sure you have HIPAA if you want to sell in financial services make sure you have SOC2 and you have your ISO 270001 and you are ready for that right if you want to go into outside if you're going to go into Europe your GDP are ready and your data residency in the Europe so I think there's as I think Rupan mentioned this you have these certifications and compliances that you can you can get which allows you to seamlessly sell into the US market so we have not run into too much hesitance I would say the cloud versus on-premise in the US until now what do you think you know Sopni said that US is not that independent so in this part of the geography do you think it's more lack of understanding or it is the regulatory issues that really affects the growth or I would say adoption yeah so you know look I'm based out of Singapore and I kind of sell all across Asia so in India specifically you know I would say about two three years ago the hesitancy was more around latency you know network connectivity you know like I said attachment to your own data center and your own kit right next to you but in the last 12 months 18 months and especially you know with the kind of I would say entrepreneurship activity that has happened in India right the number of unicorns that have emerged the number of companies like I see a lot more activity around people adopting public cloud and that goes across and they're using use cases even in regulatory industries even bank like you know have kind of re-ridden applications not gone with package application re-ridden an app for their own need which is getting hosted on cloud right one of the famous banks in India have the whole CRM system which is not a packet software so there is you know at least I've seen in the last 12 to 18 months I've seen quite a bit of traction in India in the public cloud space and I would say that some of the same factors that were there in India are also applicable in let's say South Asia where a number of countries have the challenge on around data sovereignty because not each country has data centers right and data connectivity but slowly as you know as hyperscalers kind of invest money and take care of those technical challenges more and more those barriers are getting you know lower one big example is as Google set up its instance in Indonesia we've seen some of the largest customers starting to adopt and Amazon is a bit behind but they are also trying to catch up and create an instance and that is you know and you can see Indonesia where and I've done Indonesia for 15 years 10 years ago I wouldn't have thought that Indonesians would adopt cloud but you can see that there is definitely a large, large fraction so those barriers to entry for using public cloud is dropping in all the major markets in Asia back I have one question if it you can say not to answer it but you know I was talking you just talked about data residence the term here in India is localization, how are these two different if the US is saying that residence is particular and India is saying that has to be localized, what is the difference from any other I think it's the same I believe so I mean we understand data residency because that's what our customers say and you know this is pretty famous especially after Europe launched UDPR and then California here and they launched CCPA the California Privacy Act so that's what we hear like you know data residency where is your data resident I believe I think what you're referring to is the same thing which like if you have the data for the Indian consumers you want to make sure it is in India it should not be accessible it should not be accessible from anywhere else that would be correct this was the whole fight you know that Indian government was going on with Twitter right like you know making sure the data for the Indian consumers is inside inside India and I think that gets really tricky for your global business and your global global provider like Twitter or Facebook and for companies like this making sure the data for India is in India and the other data outside the US and all the processing happens in India it just gets harder and harder with more countries but I think it's the same term I'm sorry I believe so Rupan I'll come to you and you know I'll say some questions that have come so I'll you know finally speak some questions related question I have you know I want to ask you with all these like we just talked about this they're coming into probably everything else everywhere does it really you know is it like our privacy somehow is a thing which at least here in India we still have not been able to address to ourselves so there are still there's still some way to go ahead before we ensure that we hear about you know these data by from some startups you know what do you think it's interesting so short answer it's work in progress I think we've made a lot of progress but you're not there yes today as a consumer I have no idea where all my data is sitting to be honest right it's in apps that you know maybe I'm using it's probably also in some applications which I probably used so many years ago and it's still there right all the GDPR and all those compliances require give you the right to be able to you know that right to forget it all but we don't know who's exercising that who's complying with that right so yes there is infringement of data that is happening and I think what's important is to have certain regulations and laws in place which ensure that the data privacy is held without compromising on the startups progress right it should not be like let's say any company right today you do need data to be able to make progress right you need to be able to get to certain insights which you would not if you don't understand your customer well enough but what we've seen so far the way the laws those certain bills have been written is just way too stringent and could really hamper startups utilizing the data in a you know in a good way in a beneficial way so there is a balance that needs to be you know built in from the government side it should not be there's nothing in place it's free for all versus you know just becoming too much of a watchdog on technology or innovation with data being you know the scapegoat so to speak so yeah we are still I think making a lot of progress but yet to get to that holy grail and to be honest we also see a lot of deep tech startups that are targeting this problem right from data privacy perspective so a lot of companies are working towards ensuring that within the organization companies are complying with these rulings so that's that's also helping okay let me put it this way so you said that we are working so there are two ways to go about it one is that we are working from it so let's have very stringent rules right now and let's see that what passes the passes faster and then it becomes or we let it very loose and let everyone do whatever they want and there is a mess created and then we kind of funnel then try to you know have a top down what which one do you think is better I mean which which would work better especially for for India you know people are still not still do not understand where they are sharing their data and how can they be you know where where it can get comparable so let me just quickly sort of like reiterate what I said I would go for the balance and you know there's always when there's something new that's happening there's always a lot of pain there's a lot of let's say flux before we get to a stage where everything is streamlined so unfortunately I think we are going through that fluidic situation right now in a couple of years or so we will get to a stage where things are streamlined and everyone knows what needs to be done so I would say this is a temporary phase but balance is where what I would aim for what do you think I mean I think we have extreme examples right so I'll give you example of US and China so the whole the whole data play and how consumers data could be leveraged by businesses to either provide them ads to provide them recommendations to either sell their data to resell the data and a bunch of other things that could be done with the data site right if you look at US stand right US stand has been because the rules and compliance is a lot more clear US rules are more on the stranger side right like you know consumers have a lot more control over data privacy I see some deep smiling because I think even the US stringent laws are not stringent enough with the amount of data that is further being generated by more and more sensors and the devices you are using right so even in the US even with stringent law there is a work in progress for example like you have now an IoT driven microwave what happens with that data like where is that data going IoT driven fridge that is generating data about what is inside the fridge let's say and it is understanding what you buy where does that data go who controls that who has access to it what can the fridge manufacture do with that data you are running into all of these challenges because there is so much that is being generated because all of these sensors around humans and obviously phone is getting more and more sophisticated and you are getting more sensors there but going back to key so US was always on the stringent side consumers and businesses businesses have a lot more they would like to provide a lot more clarity consumers have a lot more control and what it meant was maybe Ruben was sharing about this is not so great for AI companies because AI companies the foundation of AI is data you learn based on data you need a lot of data to build the initial models to even get into the market so if you are so restricted that you can't buy data you can't store data you can't use it to build models you have a problem if you look at what China did China went on the extreme side like no loss no crazy I shouldn't say crazy but no privacy stringent laws you could use as much as you want and that's where you saw everything around facial detection and face detection technologies for different use cases and it has both you see both sides of it so China on the other side went on the other extreme which is use as much data you want for whatever use case you want we don't really care so much about it now the positive side of that is when you leave it when you were describing open for all it leads to a lot of innovation because people have so much data imagine all the amazing innovative applications that could be built on top of this but at the same time with the challenge of this data could be misused this data could be abused use cases that are not good for everyone out there so that's sort of like the US and the China version and then India we heard Rupa and I think the compliance and government and regulatory bodies are still catching up but what is even going on here what kind of data is being collected how is it being used I think in my mind India and regulatory bodies are not even up to speed on what data how data, why data I don't think we are there yet and I think the US is being taught a lot with companies like Google like they were the first one at a mass scale to say I'm going to I'm going to use all this data for expertise and then more and more ads like Facebook and now people understand data being used to send you more stuff or to show you recommendations I think India is not there yet in terms of even knowing what is going on with my data so I feel it will take some time for India to catch up on you know and get the confidence and and policies and compliance on consumer privacy laws if I was not too scared of my phone and I'll know you've made me scared that my definitely can do that also with someone they know what butter I am using what bread I am using this is the new thing unfortunately whatever I think more convenience you want to talk to your fridge I'm going to talk to your microwave you want sensors all around you I think there is this data on an average, I think you have like 10 to 12 devices per person at home these days, like Alexa, Google Home, Twitch sensors, TV sensors, your Wi-Fi, your round-the-clock. Air-conditioners. Air-conditioners. And then now we have this Zumba which runs with Wi-Fi connected, it's like, so we are living in this world where like everything is, every, every device that we use is internet connected and it is generating data, storing data, hearing, hearing all day, seeing so there is data everywhere. And if you were, you were, you were, you were smiling when someone was speaking about this thing. I was, you know, but you know, we have three, we have three different models, like we have the US, which kind of started, you know, in a bit looser manner, but the rules of the game were pretty much kind of set over the period of time. But still supports its companies, you know, wholeheartedly. And then you have Europe, which is gone really, really privacy and privacy first. And then China, which kind of allowed everything and now is raining back in and is realizing the problems that happen when you start to rain back in, right? When, not that I have any influence on any regulatory body, I would like, for India, I would prefer that we kind of go in, you know, a little bit of the China approach, a little bit of like, you have to let the innovation happen. You have to let the innovation, you know, you have to let people kind of build things. And then you learn along the way and you figure out which ones you control and how you control them, right? Rather than putting those controls and then giving it in the hands of the bureaucrats and the judiciary and then stabbling up, you know, competition, right? I would rather competition is out there and then you learn along the way, right? A little bit like, like artificial intelligence, you slowly learn what rules you should put in. So, we have a question for our audience right, Rupan, this is this one's for you. What are, what are the trends that you're seeing in India, Indian community around clean them, beyond carbon capture, do you see new trends around capturing, measuring emission and footprint via IOT and AI? What would you, what would be your big trend of the future? Yeah, so clean tech, I think it's a very broad subject and there are like so many, let's say, sub-sectors around it. So the kind of innovation that we are seeing in clean tech so far in India is a lot of it, a lot of it focused, of course, on the TV side, even infrastructure side, rapid charging, because those are the main bottlenecks that are hampering the adoption of EVs. The other thing that we are seeing is battery innovation. So today we have a lot of dependence on certain raw materials, which we don't have, let's a supply chain control over. We've seen so many companies that are coming up with alternate bio-degradable materials or materials that are easily available in India. So a lot of innovation happening there. Then I think also on power drives for EVs because they're very different from what a NICI engine would have. And also we're seeing in waste management, which is also under climate change, we're seeing robotics companies that are coming up that are looking at sorting out waste at source without a human. Today, a human has to separate the wet waste from dry waste and dry waste. Actually, both of them have a lot of value. But how do you do the segregation in an automated fashion? So very interesting companies coming up with robotics education that can do that. So very broad spectrum of technologies and applications within climate change, yeah, climate tech that we are seeing. I think this segregation of dry and wet has been one of the biggest challenges for energy to waste plan in India, which we have not been able to take off because of an exception. It's like those come in, I think that could be a big thing. Another question that we have is for the Agnetech, is it possible to use AI and ML to the grassroots level since our farm size is too small or it is a far cry? I don't know if you think for small Agnetech people having a small business, they can integrate AI? Yes, I am not able to hear you well. I think if I understand the question correctly, are you referring to use AI in Agree? Yeah, in small Agritech. Agritech, but yeah. I think, you know, one, I don't have too much experience into that market. So please take that with a sort, but from whatever I'm aware of, there are applications being built. I can use some of the examples of what's being done already in the US, right? So from drone monitoring, where you try to understand, you know, what stage your crops are and is it going to harvest? Is it going to seed? Is it a time to, you can understand, you can detect insects being created by understanding the texture, by understanding the size of your soil. So there are lots of innovation already happening that I'm aware of. But I think I would actually ask Groupon, she might be seeing a lot more then. I think we have companies which are into these things. Yeah, yeah. So, Sapna, you got it right. So there's a lot of technologies that are being used for making Agritech, you know, agriculture, let's say improving the yield, reducing the cost and, you know, a lot of startups and some successful startups. But the challenge is, of course, like you rightly, it's there in the question itself that for in India, the land holding is much smaller, right? So the business model in India is what has been, let's say, the challenge to crack. So who's going to pay for all this? Yes, farmers will be happy. There is a little bit of a change in, let's say, the behavior for them to adopt these technologies. But beyond that, who's going to pay for it, right? So that's been the key challenge at least from what we've been seeing in this space. But there are alternate models, for example, let's say the input providers, for example, the fertilizer companies, the seed companies, because they want to promote their products. So they end up being the source of monetization for some of these startups or let's say insurance companies, right? I was thinking about the insurance, yeah. It sounds a lot like, you know, it's like vaccines, right? Insurance companies won't even have vaccines, so you don't fall sick and you don't, the insurance doesn't have to pay. So it's a lot like, if I give you these tools to have better yield, you're not going to come back and ask for the insurance money, so that's a good one. Yeah. So on this side, yes, a lot of technology, but business model is something that needs a little bit maturing, I think. Yeah. No, no, just that. The business models are the problem. Yes, but you know, Rupan has said we are working for this, so I'm going to do that. This question, one last question I think before we move to the watch. I think, Sandeep, for you, how can companies, storing and using data be made accountable by consumers and businesses and not only by law? See, as consumers, all of us, you know, vote with our choices, right? You know, we always have the choice of using or not using the app, right? You know, now, of course, people like Apple have shown that if you take it to the next level and give people the actual choice of not allowing the companies to track, then a lot of us will not allow the companies to track, right? So in that case, the platform, per se, also has a role to play as Apple has shown. But apart from that, you know, unless you talk about law, as a consumer, you know, I can choose which applications I use on my phone, you know, which keyboards do I allow to be inserted on my phone, right? Or how do I secure knowing, you know, what some of these things are doing, right? We all use application, which kind of tell our future or tell five characteristics about us. They're all reading our data, right? And it is a known fact, people still like it. And so this is a conversation that I have had with my relatives and my friends. The younger generation believes our data is already out. That train is already passed. The conversation that we're having is a very old generation, and do whatever, like, let's enjoy life as is. And then there are people who are very, very privacy conscious. But, you know, but in the end, it's the only choice that they have, is really how to make sure that the data is not being unfairly used around them. You know, I would love to go on and on, but, you know, we have time to speak, but we talked about Apple, suddenly, but Apple is an expensive phone, you know, the Indians use smaller smartphones and the applications, we don't really have those. So maybe we are the test cases from where this everything has been taken. And then, you know, a better product is made. So as you said, the train has already passed. Maybe it's a whole generation probably, but as Rupan said, that, you know, it's work in progress and, you know, be there. As you know, something said that there is a U.S. model and a China model for use of, you know, student clause. So where India should be, can be things in China, maybe someone thinks it could be the other way out. But yes, eventually together with the innovations, more and more innovations coming in, I'm sure that we will be able to overcome. So thank you, Sandeep. Thank you so much. Thank you.