Panel Discussion Next Generation of Techies _ India AI Impact Summit

Hi and welcome a very good afternoon to all of you thank you for staying on I know it’s the last day of a long productive summit and I think maybe not the last but the second last session maybe the third last session so thank you for being here I’m excited about this discussion that we’re going to have over the course of the next about half an hour or so, 35 minutes I’ll quickly introduce myself and then I’ll get our panelists to introduce themselves. We’re talking of course about the team of the next generation of tech entrepreneurs, tech founders, tech leaders in the world I’m Anirudh Suri, I run a venture capital fund called India Internet Fund and I’m Anirudh Suri And I’m also an author of a book called The Great Tech Game and a podcast by the same name that looks at the intersection of technology and geopolitics.

So I might bring in a little bit of geopolitics into our conversation, even though we’re talking mostly about tech founders. I’ll start with my left, Malhar. Today, I earlier had the opportunity to interview a very young panelist, a young speaker, Rahul. Who’s, I think, one of the youngest speakers at the summit. He’s 16. We did a podcast with him earlier in the afternoon. And so I’m especially delighted to have another young entrepreneur, college dropout. On my left, Malhar, if you can briefly introduce yourself.

Yeah, thank you. Hi, I’m Malhar. I’m the co -founder and chief technology officer of Origin Bio. We’re a Y Combinator startup that is using AI to make safer genetic medicines for diseases. Like cancer.

Thanks Malhar. Navrina

Absolutely not a college dropout not very young but I’m the founder and CEO of Credo AI we are an AI governance and trust management platform. For the past five years I’ve also been advising the White House on AI policy and work very closely with governments across the globe to really think about what AI guardrails should look like so to your point I think there is a very strong intersection of technology and policy happening right now excited to be here. Thank you

Arvind, last but not least.

Thank you everyone my name is Arvind I’m the founder and CEO of Glean. Glean is an enterprise AI company about seven years old and think of us like Google or ChatGPD but inside your company. Glean is a place where you can go and ask any questions or give it some tasks and it uses all of the world’s knowledge just like how ChatGPD does it but also uses all of the internal company’s data and knowledge to help people with their questions or their tasks.

Incredible. I think we have a great set of panelists across various sectors and I think various angles of the AI entrepreneurship market. We’re going to have a focus on how entrepreneurship is evolving, right, in this session. I’m sure in other sessions in this summit you’ve heard a lot about deep tech entrepreneurs. You’ve heard about probably all sorts of AI entrepreneurs. Of course, you’ve heard some of the largest AI companies take the stage, etc., including our very own Sarvam out of India. But now I want to focus on how entrepreneurship is evolving. Before I ask my first question to the panelists, can I have a quick show of hands? How many of you here are entrepreneurs?

Big chunk. Wannabe entrepreneurs? Ex -entrepreneurs? People who decided to… too much and went into the corporate world, let’s say? A few. Good. So I think the biggest number is still entrepreneurs and want to be entrepreneurs. I think for some of us who’ve seen the previous waves of technology, innovation, like for example, most recently the consumer internet wave and of course there have been multiple waves prior to that. And for those of you who are not familiar with the history of technological waves, I really encourage all of you to study the previous waves because often you get to learn a lot from how the earlier waves of technological innovation panned out, what kind of entrepreneurs, what kind of companies succeeded.

But a little bit with that historical context in mind, Arvind, I want to come to you first. Compared to the wave of the consumer internet where we saw forms like of course the Googles and the Facebooks of the world, the social media platforms, but then also the cab hailing platforms and a lot of marketplaces and consumer focused platforms emerged. We’ve seen a lot of and at least in India I know this is the period over the last 10 -15 years where entrepreneurship has become a buzzword, a desirable profession, you can drop out of college and your parents will still be happy about it right, compared to that wave how is today’s wave of AI driven entrepreneurship looking to you, could you draw out for the audience and for us how these two waves might be similar for entrepreneurs and how they might be different?

yeah, so well first, you know, I think whenever there’s a new technology wave, it creates a lot of opportunities for new companies to get started that’s the right time for somebody to jump into the entrepreneurial journey and, you know, we’ve been through many of these in the past two or three decades, you know, starting with like you said consumer internet to mobile to social and of course now AI, and each one of these opportunities are similar in some ways like, you know, to start a company to be successful at it you have to have, like, first of all, the ambition to make, you know, to make one, to make a company. You have to have that sort of, you know, real deep desire to, you know, to be able to take the risk and have the courage to actually go start something.

You have to follow the recipe, the right recipes, which is finding, you know, the right business problem to solve, like something that actually creates a lot of business value in there. And it’s not so much about the technology trend. It’s, you know, you can use the technology trend as a way to see if you can solve that business problem better, but it always starts with the right business problem. And then, of course, like, you know, do the rest of, you know, the entrepreneurship journey, which is about, you know, building a great team, having a clear vision, working hard, and making things happen, right? So those are, like, you know, those things don’t change, like, you know, through these ways.

But I think one thing that is actually very unique about… the new AI wave is that it’s not only, I think we always had a blueprint in terms of what an organization needs to look like. When we went from consumer internet to mobile as two big technology trends, the shape of your company, how you build it, what kind of people you need to hire, those things were not actually changing that much. The blueprint was clear that you’re going to hire some engineers, you’re going to have product managers, some sales people. But now with AI, everything changes. In fact, the role of human itself is unclear in what roles seem to exist. In some sense, there’s some more challenge for the AI entrepreneurs, but also more opportunity to actually not know the basics.

You can actually start and chart a journey without actually knowing how to start a company. Because reinventing yourself, thinking AI first, can actually help you build an organization, which is very unconventional. And maybe that is what is going to create big success for you in the future.

Do we expect, Arvind, do we expect now startups to be even leaner given AI? Because I’ll give you a couple of examples. I have friends who are second -time, third -time entrepreneurs who successfully started, exited startups in the consumer internet wave. And now when they’re starting up in the AI era, they seem to have much lower number of team members to start with to get to that minimum viable product. They seem to have much fewer people doing the coding for them. Many, I would say, a significantly smaller requirement even for capital as a result, because of course in the early days sometimes employee costs or early employee costs are quite high. So do you expect this to continue, leaner startups?

Absolutely. In terms of the product and how far you can go with a very, very lean team, in fact a team of one person, is actually, it’s incredible. can actually build a lot with, you know, with that low cost. So certainly, like, you know, that is, that is a, I would say that, you know, but it’s not like, you know, ultimately when you build a company, you know, with scale, people actually are your asset. And at some point you’re going to start growing, but you can do a lot before. And I think one of the reasons why companies will be more lean now is because it’s always, you know, on an entrepreneur’s mind, you’re always thinking about, especially when you don’t have enough resources, enough funding, you’re always thinking about any piece of work that needs to happen.

You know, can the machine do it? Can AI do it? And so that sort of like that mindset of like, you know, like, hey, you know, I’m going to actually use AI to do most of my, most of the work that needs to get done in this company. It is actually, that is what is going to actually create significant efficiencies and a way to defeat like, you know, the incumbents.

Great. Let me move to you, Malhar. We had the opportunity to speak a little bit prior to the session. Thank you very much. And you’ve, of course, started very recently. So you started technically your first startup, I’m assuming, first startup in the AI age. And so talk to us about how you are both viewing entrepreneurship today. Is it any different than maybe, I’m sure you might have read some books or met entrepreneurs who started earlier, venture capitalists who started companies earlier in the earlier waves. What’s your sense on the question I just asked Arvind as well? And secondly, how are you being AI first in the company that you’ve started? How are you leveraging AI, not just in the product itself, but even in the sort of organization, so to say?

Yeah, I think one thing is that because of how good AI has gotten, knowledge has gotten a lot more democratized. And so there’s less of an excuse to. actually be able to work in different fields in this sort of cross -disciplinary nature. For context, my co -founder, Yash and I, we’ve never studied biology. Our team is five people. One of the people from our team has graduated. Only one person has studied biology and they’re not the same people, the same person either. So I think AI has actually allowed us to study a lot more, read a lot more papers, reach out to more scientists, learn from them, reach out to more customers, understand what exactly they want.

And we sort of use AI throughout. We do fundamental research. We train our own models from scratch. We do research in the wet lab. We’re starting a lot of wet lab work where we use AI to actually be able to predict the results of these wet lab experiments so that we can be cost efficient and ensure that we can work with a very limited budget. I think in some sense what hasn’t changed from when we grew up and we were watching movies like The Social Network is even then it felt like the people who succeeded the most were people who didn’t want permission. The example being Mark Zuckerberg. Even if you look at Jeff Bezos starting Amazon, it wasn’t like Barnes and Nobles that started a website to sell books.

I think with AI that sentiment hasn’t changed, but it’s probably easier to materialize and we’ve definitely gotten the benefit of that.

Are you finding that research is more and more critical to your work compared to maybe earlier waves of startups?

Yeah, I think it’s definitely critical. We’re working on using these AI models to actually design novel DNA sequences. They act as switches. This involves training the models from scratch, working with… public data, starting and warranting experiments to actually get our own proprietary private data. So the entire thing actually hedges on the product or our research producing an output that is biologically and scientifically viable. Even when we want to sell to biotech companies and pharma companies, or if we ever want to pursue our own therapeutic program, there are very rigorous requirements for the thing to actually work. An example, of course, being the FDA and needing clearance throughout, but even actually starting the clinical trial process is a lot of work and actually has a requirement of things actually working.

I’m going to keep coming back to this theme of research for a reason, but before I do that, Navreena, I want to bring you in. We, of course, started off the conversation saying about talking about the intersection of AI with, I mentioned geopolitics, you mentioned policy, you said you’re working closely with folks in D .C., in the White House, and otherwise. This intersection of AI and policy. while for policy wonks like some of us I also work at a think tank as a non -resident but other than for us policy wonks who are looking at that intersection of AI and policy talk to us about why for let’s say a Malhar of an Arvind who are not necessarily spending that much time in DC and with folks in the White House and the policy crowd why is understanding or maybe dealing with this intersection of AI and policy and geopolitics why is it important?

Is it? And if it is, why?

Absolutely and just by way of background I’m an engineer by training, spent 20 years building AI products in research and development at companies like Qualcomm, Microsoft so it is I do want to ground it in why I think as a technology policy is becoming really critical is going back to something that Malhar said which is really interesting right? It’s when we think about the new AI wave, to actually go from zero to one right now is very, very easy. I think what really becomes really interesting is do you actually get that product to be extremely reliable? It’s robust. Can you explain those systems? There’s a combination of, I would say, scientific measurements to build that trust that needs to happen.

But there’s another thing that needs to happen, which is all about making sure these systems work within the regulatory domains that especially require a lot of risk assessment and management. And so what we are seeing is the true moat that is happening for companies like Malhar is not just the technological innovation, because it is, you know, you’re able to do that much faster with a leaner team. But it is how do you do that consistently within the boundaries of the constraints and guidelines? That’s one of the guardrails that a regulatory ecosystem causes. So just as an example, we work with Fortune 500 companies in financial services, in health care, and they are really finding that they’re depending a lot on third -party AI, like maybe tools like Glean.

But how does Glean work in the context if you are building, let’s say, a customer service chatbot? You want to make sure that the chatbot not only is aligning to your brand guidelines, but it is not toxic. It’s highly reliable. It’s doing the things it’s supposed to do. And if it is within the context of a regulatory sector, it is following, let’s say, HIPAA compliance, et cetera, right? So as you can imagine, now it’s not just about building technology, but it is about building trusted technology that can work in the context that we are talking about. And that’s the exciting intersection of, I would say, policy, governance, and tech that I see.

If I can go a bit deeper on that. So has it changed? Because regulation, of course, regulatory risk, policy risk. all of these risks are always there. So Qualcomm, Microsoft, a Jio, a Tata, you take any large company anywhere in the world, of course they’ll have regulatory and policy risk people and of course that’s a big part of what they are tracking, etc. What has changed, if anything?

A lot has changed. And just I think another thing I want to ground us in is it’s not just about regulation. When you start thinking about AI risk, just because of the way these large language models are built, unless you ground it in real data, there are issues of hallucination. Do you actually, are you getting the right outputs? And can these systems be reliable? What kind of evaluation benchmarks do you have? Have you actually done the testing across your entire AI supply chain, etc.? So the thing is now it is not a static tech. It’s actually a very dynamic technology that when it starts to operate in e -commerce, either customer context, or it starts to operate in regulatory context, you have to prove that you can do it reliably.

So I would say that’s the biggest shift that we are seeing with AI and some of the applications.

The other theme that I want to keep going on with this, Navreena, and Malhar, Arvind, please feel free to chime in, is I think at the core of our engagement with AI on the policy front is the fact that the technology is moving so fast and governments realizing the fact that AI as a technology has massive ramifications on people, on existing structures, are saying, hey, listen, let’s rein it in before it goes out of our control. So there’s also a question of control here. So governments want to control so that for both reasons. I think one is governments generally don’t like to give up control to the private sector too much anyways, anywhere around the world.

But the other bigger piece here is when the technology, as you were saying, Navreena, is moving so fast, ultimately if some massive harm happens to people, ultimately the governments and political leaders know that they’ll have to be accountable. So it seems to me that it’s the nature of AI as a technology also, and it’s massive ramifications it’s making. policy and geopolitics risk a big part of what entrepreneurs have to keep in mind. The question I have for you though is has this become a function that every team has to have? So any startup has to have a CTO, has to have a CEO, has to have maybe a CFO and then product manager, etc. Is this becoming a role that is critical?

Malhar, do you have someone looking at this? Arvind, do you have people? Of course you’re a larger company. So let me start with Malhar. Do you have someone looking at this kind of risk?

I think we do have the benefit of being a smaller company that’s not entirely putting things out for public use where they can be harmful until we’ve gone through all of the regulatory requirements and until we have tested things out in a setting where it is safe. But I think from a research perspective people who are working on AI biology models such as us they work a lot on ensuring these models are safe whether it comes to other people being able to design dangerous pathogens and they’re not going to be able to be able to So we very actively in our entire team keep up with that research. We study that research. Everyone on our team is technical.

We study how they actually enforce those guardrails. So for when we actually need to start making things and actually turn them into products, we are actually able to implement that.

Yeah, so first, like, you know, so we are enterprise focused. And in that sense, like, you know, users of our product, they come to Glean and they ask questions which are serious in nature. It defines, like, you know, what work they’re going to do, what decisions they’re going to make. So first of all, you have to be absolutely sure that even though the core foundation of the AI technology is, you know, it’s a stochastic, you know, modeling, it can make mistakes, it’s probabilistic. You have to sort of work on top of that and ensure that you can actually deliver precise and accurate results. And like, you know, refrain from answering questions or doing tasks if you’re not sure.

So so we like it’s a big part of like our product experience is how do you actually use a safely and securely? How do you sort of, you know, do that constant sort of judgment and evaluation of the work that it produces? And do fact checking so that ultimately, you know, not only are you delivering the right answers or task execution, but you’re actually showing the full trail of like, you know, where the answers are coming from, what are authoritative information is being used that is human generated. So so that is very core to just like in terms of, you know, what product experiences that we deliver. But I think you’re also talking about the question of like is like how important it is to think about policy, to think about like.

You know. like setting, working with governments and actually ensuring that, you know, the right regulations and laws are in place. For us, like, you know, as an enterprise company, you know, that, you know, we don’t actually think a whole lot about that. But it is important to sort of have, you know, these rules and regulations in place because otherwise AI can actually do significant damage, you know, in the industry.

Great. The other dynamic I now want to move on to is, you know, the tech industry, as I think I’m sure all of us have seen, is in many ways, tech and entrepreneurship is defined by this idea of creative destruction. Large companies come as startups. They become big. By the time they get big, there’s a whole new wave of tech coming in and then a whole new set of startups come in and disrupt the incumbents. We’ve seen that again if you go into history, time after time, wave after wave, that’s happening. So my question to all of you. is that principle of creative destruction going to continue with AI? Or are we going to see that the big companies of today, the big tech firms of today, with the amount of capital they have, the amount of talent that they can hire with the kind of balance sheets that they have, the global scope of these companies, et cetera, their ability to shape policy, right?

Is this wave of big tech firms different? Or can we expect that the principle of creative destruction of them getting disrupted sooner than later is likely to continue? I’ll start off maybe, Arvind, with you, and then I’ll come to Naveen and Mahal.

Yeah, well, I mean, I think this creative destruction or disruption, rather, you know, it happens, and like always, you will see that, you know, over the last 20 years, companies like Google, you know, Microsoft, you know, these are big… giants and they have all the resources in the world and all the policy making power but yet when you think about innovation that happens in the tech industry often it actually happens outside of those companies and that’s because I think the spirit of entrepreneurism is actually alive, it’s an innate human thing and most bold ideas actually come from a single person who wants to actually who’s passionate about solving a problem and so I don’t think AI is going to actually change that in fact if there’s any indications AI is actually going to make it even more, it’s going to make it easier for people to actually create really interesting products and to serve large players because now there’s more power in their hands you don’t even need to be an engineer, you don’t need to be an AI scientist to actually use these amazing technologies and build and sort of turn your ideas into real products with very few reasons.

resources. So what I expect to see happen is that more and more innovation that is going to happen again in startup land. But ultimately, of course, I think the larger companies are well -established, they have large customer bases, so the model in the industry tends to be that new products are always, innovation comes from startups, but then innovation scales at larger companies.

Malhar, I’m going to come to Navrina in a second, but Malhar, I want to ask you a slightly different question. Navina, did you want to add to that?

You should not be worried about another person or even like AI taking your job. You should really be worried about a person who’s so good with AI actually replacing you. So I think so I have started to think about disruption rather than like in context of big tech or startups like individuals. Right. What what are creators and entrepreneurs going to create just when they can unlearn very fast rather than, you know, we don’t have a playbook right now for how you should be succeeding in the age of AI. So can, you know, new set of entrepreneurs use these tools, unlearn very fast old habits and be open and willing to try new ways of building faster?

I think that’s the construct that’s more healthier than thinking in the context of a company.

Great. Thanks, Navina. Malhar, I want to come to you now and ask you, we’ve spoken about how companies or startups are changing both internally. They might look different, might be leaner. more research focused in the age of AI. You’ve spoken about the importance of policy and regulation and especially in the world of AI, but I want to ask you now about the entrepreneur themselves. Given we’re sitting in India, I’m going to ask you the question from the perspective of India. You’re an Indian entrepreneur, grew up in Bombay, working out in San Francisco, part of the Y Combinator batch, dropped out of UIUC. Tell me from your perspective, Malhar, what does the Indian entrepreneur building a startup in the US today look like?

Is it any different from earlier generations of Indian entrepreneurs in the US? One. And do you find some difference that you can maybe point to between an Indian entrepreneur who’s grown up in India and then is working there, starting up there in the US, versus someone who’s grown up in the US?

Yeah, I think something that has been quite fruitful for me moving to America is that there’s an entire process of actually leaving where you’ve grown up and going somewhere and setting up things entirely new from there. And I think that sort of sets some sort of tone and precedence in even the work you do at your startup in terms of just taking risks, the people you hire, the things you do. I think in some sense that has perhaps stayed the same over multiple years because that procedure has not really gotten easier. It might be easy to get information, to book flights, to stay in contact with people, but the act itself has still been incredibly hard.

I think that is one big difference, and I think something that also probably contributes for more specifics is someone who’s grown up, let’s say, in America, is more aware of systems in America, how do you sell to people in America, what are talent distributions like in America, and how do you sell to people in America? And I think that’s something that has been quite fruitful for me moving to America. Thank you. someone like me who’s grown up in India. I think if we believe that India has a large role to play in things like drug discovery in the coming decade, I know a lot about how drug discovery works here, how hospitals work here, how data is collected, how many patients are treated, how diverse the patient body here is.

So I think there are those very specific advantages to it as well.

If I go to Arvind to ask the same question, can I just see a quick show of hands? Anyone has questions or quick comments? I want to make the last few minutes interactive if you’d like. Any burning questions or comments in the audience? Okay. So while Arvind’s answering, just raise your hand so I have a sense of the room, and then we’ll try and get to you. Arvind, this is your second startup, so I think you might have some perspective on this.

Yeah, well, I think, first of all, in technology, a lot of startups actually are started by Indians, folks in Silicon Valley or, of course, here. One thing which I… I think is interesting in the U .S. and Silicon Valley is the… you know, there is availability, you know, of capital. There’s belief, you know, and specifically in the Indian diaspora in terms of, like, you know, their ability to go and build great companies. You know, today, look at tech, you know, in the tech industry, you know, even in the large enterprises, you know, there are a lot of Indian folks who are CEOs. And I think what has actually made that happen is fundamentally, I think, you know, we are more hungry.

You know, we are, like, you know, I think there’s something about, like, in our culture, you know, and where we are as a nation, there is, you know, that drive, you know, that, you know, Indian people have, you know, and which is what is actually creating, you know, this incredible success, you know, for success stories, you know, for all of us. So I think that that’s one thing that I would say. I routinely, like, you know, of course, you know, I had the same thing, you know, I had the desire to make something. You know, big and, you know, that. continues to drive me, but what I see from, I work with a lot of young folks, a lot of people have actually joined our companies and then went on this entrepreneurship journey and I continue to see that same pattern that it is the folks who actually grew up here and then relocated to the US they are the ones who are most likely to start companies and become entrepreneurs.

I want to quickly open up to the audience, I know we don’t have probably mics there so I’m going to can I see a quick show of hands again? 1, 2 and 3. So we have less than 4 minutes, so what I’m going to ask you is in 15 seconds give us a question or comment. 3 hands I see. We’ll start off here and come to you and then come to you. Hello,

Yep, I have a question for Malhar. So you have a multi -discipline startup right now, so and you also told that you’re not from biology field like you’re not affiliated from biology field so the question is how did you like find this problem to solve great we’ll take these two also you can just shout out while the mic comes Yeah. So my question is so I mean we had this technology and it became a boon and bane and then what started evolving with technology was cyber security the field of cyber security right so now we have this AI and also we have the fear of how AI is being used for the boon and the bane and also you have the additional fear of hallucinations and of course so all these equivalent to cyber security are you going to have something like AI security or is there a new field that will come up and also how can you handle this hallucination I mean you can give a relevancy score to the output?

Hi, my question is for Navina, actually. I also work in an AI governance company called Protego. I had attended sessions today with Amazon and Zoom, especially these big leaders are saying that if we do governance at this stage, we will not see the ROI from AI, and it’s going to stop innovation in some manner. What’s your take on that? How do you advocate AI governance, especially with your hands -on with G42?

Great. So I’m sorry, but I mean, I’m sure we can speak. I literally have a timer that’s in two and a half minutes. Navina, I’m going to give you less than a minute, and then we’ll go across the room.

Yeah, it’s funny. If you were in the Amazon room and they made this comment because they were our first customers, so I’m surprised to hear that. But having said that, you know, it’s actually very clear. We are seeing very clear ROI on AI governance. If you have a very clear visibility, risk management practice, you can actually adopt third -party AI much more faster. And you’re seeing… much more, obviously, productivity gains with that. Secondly, when you have governance, your AI deployment increases, so you can actually deploy more products faster to customer, but also products that can be more trusted by the customers, and as a result of which, you are just adding more to top line.

So happy to share more details from our customers.

I think you can take maybe the cyber question, and then Malhar will come to you for this. Are we going to see a new field of AI and cybersecurity?

Oh, that’s right, yeah. So absolutely, I think AI is a very new technology, and it’s actually very gameable. So there’s a new form of attacks, like prompt injection are coming into place. It’s actually a rapidly evolving new field with a lot of entrepreneurship opportunities. It’s about how you actually… So I’m going to turn it over to Malar. control like what data, what information actually goes to AI models so that they actually get to work on good safe data but then also like whatever output comes back from AI the responses that comes back from AI how do you sort of make sure that those are not attack vectors and similarly I think the other thing you mentioned the related point of hallucinations.

The hallucination is actually a core sort of feature of the current AI technology unfortunately like this is how it’s built and so again from a discipline perspective I think companies that actually detect hallucinations that can monitor it, provide observability on it is also again like a good area and a field of discipline.

Good entrepreneur. Anytime there’s a problem there’s an opportunity. Malhar you have something? 16, 15?

I think for my co -founder and I both it started off as this deep intellectual interest more than anything, being college students that was really what we had to go off with. We were always interested in DNA and how your body regulates different cells, how it sort of maintains healthy functioning and what can really be learned by mining the genome and understanding things from that. So it started off with that and then I think after that we treated it very empirically, talking to customers, talking to scientists, talking to doctors who know a lot more in this field. I think that was sort of the start and how it continued.

Great. I think we are out of time, but I do hope that all of you have taken something away from the session. I hope that this summit has been a two -way conversation. I think it’s more important that, and I want to end with this remark, it’s very important that people sitting on the stage, whether it’s us or other panels, listen to all that you have to say and ask and show. because I think the summit must be a two -way conversation. I think that’s a very important piece, especially since so many students and so many entrepreneurs and would -be entrepreneurs have come here. So please do take the time to find the panelists if you want subsequently.

And now let me end with one best of wishes to all of you in your entrepreneurship journeys and to you. And we hope to see all of you back again here soon. And thank you all for staying here.