Uncategorized

out a long, lengthy form of information for that to be processed much later by another human in the loop, per se, to really looking at how do we get an experiential learning and an experiential engagement where the intent is to keep everybody safe and our workplaces safe as well, and then obviously have AI be an enabler in how we get this into the system as well as processed, and that giving us the right signals for predictive intelligence. So that’s a paradigm shift that we are looking at, obviously, in today’s times, and the evolution has taken us to this stage right now. So we as Benchmark Gen Street have been around the business of digitizing environment health, safety, and transforming workplaces for the last 30 years, and we work across the world with close to 450 global…

Subscribers. and about 8 million user base using the system day in and day out for various aspects of compliance, assurance, environment, health and safety to sustainability and ESG management to obviously looking at supplier engagement and quality and security as well. So it’s a time -tested active product and the challenge for us over the last three years has been really to transform a SaaS -based system that we have today into making it AI -first. So that’s been our motto over the last three years in how we convert all of our intelligence, learning experiences into giving our customers AI -first philosophy and methodology of engaging with the platform. I think I covered some of this aspect. And in the pipe, I think we have.

I think we have already 75 different use cases in AI that we have available. but I think our next gen is about agentifying a lot of that to deliver the right value for engagement. So with that, I think I’ll invite my colleague Chandan to take a shot at helping us walk through the use cases and really talking through the value proposition of how AI is here to change the way we do stuff. So, Chandan.

Thanks, Naveen. So now we’ll walk you through, I would say, a story of someone who is working at a work site and how they really look at the different risks and hazards at the work site. So let’s say I am just walking into my work site, and this is something that I see the moment I kind of walk into a construction site. I look at this scene. and I know something is wrong here. I am not entirely sure what is wrong here. I am not sure what kind of safety rules that they are violating. But I know, I get a sense that something is wrong here. Traditionally, in a very traditional sense, what Naveen spoke about, you know, earlier what used to happen is that I am supposed to kind of, you know, go find a form, fill it either, you know, manually on a paper or, you know, find a portal, look at a form and fill it, understand what is the type of risk, the type of hazard that I want to report on.

But now let’s look at what the transformative way of looking into these hazards and risks. So I will go online. What you are looking at is one of the programs that we have. We call it observation reporting. And this is something that is used for engaging people in reporting. Reporting any kind of health and safety concerns that they have at their workplace. What a worker can or anybody for that matter they can really do here is look at let me just I think I am not connected to internet so just give me a second to connect it back but essentially what I can do here as somebody who is using this kind of platform and AI technology I can very easily scan a QR code on my phone or scan a direct photo of something that I am seeing and then look at sharing it with the agent that we have we call it Jenny AI and the moment we kind of share it with the Jenny AI the agent can really process and look at all the different health and safety related hazards that we have and kind of fill that form on my behalf.

So let me let us take an example we will look at the same photo that I was showing you earlier and let us see what that overall process will look like. So assuming I have already captured the photo here. I will locate that photo which is in my phone or my computer. And let’s see what really happens here. What you will see here is the Genie AI, which is the agent, AI agent. It will pass through the photo which is uploaded. And that’s what is happening right now. It is analyzing the image input. It is reading through the intent of the input which has been provided. And it has filled the entire form on my behalf.

I did not have to go and tell it or describe the hazard. It says that there were a couple of workers or two workers who are working at site. And they do not seem to have any fall protection equipment which is there. Now, of course, we do understand that the AI is just looking at the photo. It does not have broader context at this point in time, which is where it will also ask you, do certain things that it does not care about. So right now it is not very certain that while the people are working at height, it’s not certain of what is the height that they are working at. And it will ask you some follow -up question that you can kind of really provide.

But this is where it will help you, you know, update most part of your form, if not everything. Now let’s, you know, assume that I don’t have a photo. I am there in the site and I just want to kind of go and report something that I saw. And I do not, I am not very fluent in, let’s say, English or the corporate language that we use. So I want to do it in my own, let’s say, language. So I am going to use an example. I am going to speak or describe what I saw in Hindi. And let’s see how the agent will respond to that. So I am going to say, I am going to speak in Hindi.

And I am going to say, I am going to speak in Hindi. And I am going to say, I am going to speak in Hindi. And I am going to say, I am going to speak in Hindi. So what I did just now, I spoke in Hindi and I described that I saw, you know, a bunch of people working it. And now let’s see what’s happening here. So the AI assistant, it is analyzing the voice, what I spoke in Hindi, and it is kind of, you know, trying to put that into the form, into an structured data for me to again go back, validate, and then submit it. So what, you know, how it really helps is, let’s say I do not have the safety inspector’s lens or competences, but I still want to contribute and I want to report things.

This AI can really help you, you know, put things in. So you can get the perspective in the right structure and get the data into the system. now let’s say you know I have reported this I saw two people they were doing something which was not really safe and it was reported into the system what’s next? The next step is for us to really understand why they were doing it and that’s where the incident investigation comes into picture it is a process for the industry to look into what really happened and then understand the root cause behind it and that’s something that we do here using the other AI that I want to talk about which we call as 5Y AI analysis and 5Y is nothing but a way of looking into what exactly happened and why it really happened and we keep asking question you know as to why it happened so in this example you know two people were working at height they were not using any safety equipment then the question would be why they were doing that you know were they not trained about it or were they not really, you know, given that safety equipment, right?

So, this is how you look at all the different reasons which really contributed to that particular incident. Now, in this case, typically when we do it in a very traditional manner, what it needs is, you know, multiple people who have years of experience, they collaborate. These are the, you know, team of cross -collaboration, you know, experience. And then they look at all these reasons. But in the absence of that kind of experience, this is where, again, AI can be used as a digital co -worker. So, in this case, the AI is helping me kind of articulate what really happened here, and then it will support the entire process of conducting a YY analysis. So, the moment I click on suggest, it kind of opens up a separate form, takes into account everything that has been reported here from a context standpoint, and the moment I click on…

generate Y statement, it will give me different branches, different options, which I, as a practitioner, I as a supervisor, I can really pick at and then conduct this analysis. And this is the process that I will kind of, you know, go and repeat until I reach to that final Y as well. So this is again, like I mentioned, the idea here is that even if someone does not have that kind of experience, it can use the LLM, the large language model, which are, you know, trained on the latest datasets. And that’s something that can, you can really use to, I would say, substitute the experience part of it. Now, let’s say we have investigated this.

And now we need to also figure out what do we do to really, I would say, repeat the recurrence of similar incident, right? Two people were standing on a drum, they were doing something they were not supposed to do. We investigated it, we understood that, you know, maybe they were not trained, maybe they were not given the right kind of equipment. So, now we need to look at what should be done to really, I would say, correct that. Typically, when we talk about corrective preventive actions, there are different controls that we talk about, right? Not all controls are same. There are certain controls which are more structured, more powerful. We call them, you know, we identify them as hierarchy of controls.

So, in this example, when someone is working at height, the first type of control that someone would look at is the elimination. Is there a way we can eliminate this risk altogether? If not, can we substitute it with a less hazardous risk, right? Instead of having two people climb the height, can we do it through, you know, maybe something else? Maybe we bring in a forklift or maybe we bring in a Caesar lift and we do that activity accordingly. And then we talk about the engineering. Engineering control and then the other administrative control that we have. So many times what happens is, you know, when people are thinking about these controls, they don’t really have a very structured thinking in identifying these controls.

That’s where we have this option or this AI agent which looks into the details and then across the hierarchy of controls which should be applied, we can look at generating those different type of controls. And that’s what you are seeing here. It is giving me a very good first draft on what are the things that I should be doing for preventing the recurrence of similar observations, similar incidents here. So just to kind of recap, this is how AI can really help people in not just understanding the context of what they are seeing at the site from a risk perspective, but also look at understanding the root causes behind it and also come up with the corrective preventive.

actions without, I would say. you know, of course, it’s not again, a replacement of human, but it is a digital co worker that you can have in your pocket and which can really guide you through the entire process that we have. Now, let’s look at the other example here. I think we spoke about fall from height and the risk that you saw there is very, very evident, right? You saw two people who are standing at, you know, maybe three meter height, and there is a risk of them falling and you know, sustaining a fracture. But there are other risks when you work in industry, which are not so visible. And one of those risks is ergonomics risk, risk, right?

It depends on, you know, what kind of activity that you’re performing, right? What type of movement, the body movement, the manual material handling that you’re doing, and it creates a strain on your shoulder on your backbone, and so on, so forth. Typically when industry you know run these programs they need people who are actually trained on these guidelines some of these are called Reba Neosh guidelines and that’s where you need someone who is certified ergonomist to really look and identify those hazards. If you are a remote site if you do not have a certified or trained ergonomist this is where the AI can be really helpful and powerful. All you need to do is take a video clip of that particular activity which is being done and then you run it through this AI agent and it can really help you identify all those risk points that you have.

So in this case what you will notice here in this video is a person who is standing next to this conveyor and his job here is to pick these boxes manually and place it back on on this conveyor. So it might look you know a very very simple activity but if you keep doing this for one hour, two hours, six hours, eight hours a day there are a lot of risks that you are exposed to from your ergonomic standpoint. So if I just kind of run this video, you will notice that the Ergo AI agent is looking at all those pressure points and trying to kind of identify those risks which you are not able to identify unless you have gone through that rigorous training of being an ergonomist.

Once it is done, you can also look at converting it out and generate a quick report here. So the moment I click on summarize, it takes all those learnings, those analysis, and it is creating a ready -made output for me to kind of go and share with the relevant people. So this was an example of, I would say, ergonomics. Now, let’s also look at another example. And I think Naveen spoke about how we are kind of transitioning from having AI as a standalone functionality or feature to now looking at the AI. So if I go to my software, I’m going to go to my software, concept where the AI functionality works in the entire ecosystem and focus on autonomous action as well.

So it’s not just about the inside, but it is also about taking action on behalf of human, of course, within the certain defined guardrails that we have. The example that I’m showing you here is of a legal compliance. Typically, when you are in an industry, you need to go through multiple type of regulatory compliances that you need to report on. I’m taking one such example of a regulatory requirement from one of the steel industry and feeding this information to this particular AI. What it will do is look at consuming this entire information and it will then deconstruct it into different requirements that we have. And this is where you will see that the agent here has deconstructed it into almost 35.

Individual requirements that the industry is supposed to comply with. At a click of button, we can also take all of these requirements into a tool called compliance calendar, which is where these requirements can really be operationalized. Right. You can, of course, interact with this agent and, you know, ask specific questions or give specific, I would say, directions. Also, in this case, I’m asking you to do a quick synopsis also, as well as taking a quick way of auditing this entire activity. So this is where the single agent is kind of, you know, connected and working with multiple of the programs that you have within that defined ecosystem that we have. Now, the last piece and, you know, one of the most important piece that we wanted to share with you is all of these individuals.

Individual AI components that we saw, they tell you, they process a single record and they tell you a story about that particular record. but what if we want to understand the overall trend and the story that all of these data points together they are telling us that is where the RISC -AI comes into picture it looks at processing all of the records that you have each and every record which is logged into the system across different programs whether it is observation whether it is incident, it is kind of processed and that is where it helps you identify the patterns the trends of precursors things which can go wrong so I think again going back to the example that Naveen used of Bhopal there were of course many many precursors before that incident happened in terms of maintenance in terms of safety culture but all of them probably went unnoticed so this is where a system like RISC -AI is extremely powerful extremely helpful which really helps you see kind of trend and help you take a preventive action also The other aspect that it can also do is help you visualize the different kind of risk that you have in your organization.

So using this chart, and let me just refresh this for a second. But what you will be able to do here is use a mathematical model to assign a severity of different type of risk that you have in your organization and visualize those on a heat map. In this case, what you will see here on the x -axis, I have the volume of those different risk categories which are captured. And on the y -axis, I have the overall weightage risk score. If I just talk about some of the examples here, for example, slip and trip risk, you will see that the count, record count is on a higher end. There are almost 75 records which are tagged to this category.

But the weightage risk score is comparatively low when we look at some of the other components here. Such as fall from height, because it is taking also into account the inherent risk that you have in that particular activity. So this is how it can really generate a very powerful picture of helping you understand what are the areas that you need to kind of focus on from a prevention standpoint and also provide you a bit of predictive intelligence about what and where you should focus next, both in terms of the different part of your workplace, organizations, as well as the different kind of activities that you’re having in the system. So with that, I will now invite Naveen back on the stage to kind of, you know, Naveen, anything else that you want to add from a closing standpoint?

Thank you, Sundar. I think this is great. I think I had a few friends come up to kind of comment on the demo, which I think they could relate to a lot more, I would say, from an industry standpoint. But overall, I think as benchmark Gen Street, I think our journey this year is going to be focusing around some of the stuff that Sundar showed. which is autonomous agents being able to do a lot of the stuff, a lot of the heavy lifting that is required by individuals who were earlier wanting to engage with a platform and type in all of those details which are required. So I think with that, I think hopefully we’ve been able to do some good justice in helping you understand how AI can transform a function like safety and look out for us over the next year or so in making it a completely agentic platform.

So with that, ladies and gentlemen, thanks a lot for your time. We do have some time for questions if you do, but yeah, otherwise we have a booth back in the room when we can have a lot more personalized conversation if you’re specifically interested. So thank you. Any questions, please let us know. All right. Thank you again. Bye.

A bumblebee cannot fly but it still does. The thing is that when this statement was made in 1930, we understood very little about aeronomical designs. And by 1980s and 1990s, more research came up and we realized that okay, a bumblebee can truly fly because its wingspan and body weight support a variable flying measure. That is what design does. And AI only understands what we know of design today. not what we can create with it tomorrow. Creativity is today’s human advantage. AI can generate, AI cannot originate lived experiences. The context, the culture, the emotion, the meaning and the human intuition matter more than ever. Good design is not about a good drawing. Good design is about good solutioning.

Good design is not about beauty. Beauty, good design is about good solutions. And good solutioning needs good understanding of design. And hence, I make a very provocative, bold statement today that resumes are going to die by 2030. Because the skills that you may have learned today, I may have learned so far today, may become irrelevant. AI probably will be able to do everything faster, better and at a much lesser cost than us. So then which is that? Not one skill. that remains extremely, extremely important. Design and creativity. The workforce that we need 5 years from now, I’m not even making a bold statement by saying 10 years from now or 20 years from now, which can think across disciplines, which can collaborate with machines and not compete with machines, which can communicate visually, which can learn continuously, which can adapt to context, to cultures, which can build and shift fast and which can adapt without fear.

And hence, being human becomes your advantage, even in the age of AI. And how do you become more human towards solutions is by the essence of imagination, that is creativity and design. Good afternoon, I welcome you all to this session hosted by Code. And now I welcome my colleague Garima, who will invite all the panelists and we’ll continue the discussion. Thank you so much. My name was Magma Sree. Thank you.

And we are proud to have Dr. Shweta Chaudhary, founder and director of CodeEDU and host of this session, a leader working at the intersection of creativity, learning design and future ready education ecosystem. Thank you all for being here. And I would like to thank Dr. Shweta Chaudhary for his time .

Hello friends and thank you for being here with CODE, the Centre for Originality, Design and Expression. Why we need it? I am thankful to Umang for setting the stage that yes, the bumblebee can still fly. So what is it that in the age of AI will keep all of us the way we are, the humans? I am privileged to have with me an August panel which has been through various walks of life as a student from esteemed institutions, as workers, colleagues and administrators into institutions of high repute and public administration, as founders who have struggled and evolved built systems which have handled talent at a larger scale. So let us hear from them what it means to them that why and how the human intelligence will stay, should stay, has to stay in the age of artificial intelligence.

I would prefer to begin with Sir from Sunstone, Puneet here, Piyush here, sorry. Piyush sir, what does this word creativity, cognition and culture mean to you as a person? That’s the best way to introduce ourselves. Rest of the chat, GPT tells about us. So today he asked. He can’t tell.

I think these are all the pillars which define any human being. Because whenever we talk about Vixit Bharat, whatever we may think of, we might have things like GDP coming our way, but at the core of it, it is the human capital. So, whether it is personally us or we talk as a nation, creativity, cognition, culture would always be the key pillars. As a founder of a tech school, I can tell you that today coding is no longer a skill. It’s table stakes now. Because how you apply that, how you solution to that, that creativity works. So, I hope this will help you lead the way forward. You can ask any question, write me an essay, create me, you know.

Give me these points. But if you are not prompting the system again, you are not challenging your cognition. You are not challenging your thinking process. And thirdly, culture. I think we have a big 5 ,000 -year -old heritage to live with. There are more than 22 languages, innumerable dialects. To be able to take that along, to be able to understand those nuances is also very important and not to be ignored in this AI -led world. Therefore, no matter where this, and it is quite evident that AI is shaking up a lot of things and will shake up a lot of things. But the power of creativity, cognition and culture is here to distinguish. what is human led and what is mission led.

Perfect. So it’s not about the countries or the continents that are fighting to fight about who owns it but it’s about the human beings of those countries and continents who will be owning it. So let’s keep us intact and keep our humanness. Thank you sir for that take. Let’s have sir who comes with a background of public administration. Sir, how do you think that creativity, cognition and culture in this setup really keeps you intact or how does this value into your ecosystem?

Thank you very much. First of all, I thank CODE for organizing this beautiful session and the kind of passion they displayed in insisting upon me to come here is laudable and that’s why I am here and I would also like to tell everyone that I liked what Umang said in the beginning very much. Beautifully he presented in a very brief thing. I told Umang personally that I liked what you said. so you know i’ll tell you how i mean creativity cognition and culture why it matters i was going around this stall i also came day for yesterday for something else so i was trying to meet this this floor has a lot of government ministries so i was trying to meet trying to find out if there is some officer from any ministry i didn’t find except in ministry of skill development stall i met a lot of youngsters consultants other people so i said are you worried about ai or are you happy about ai more often than not i said we are worried sir i also across you know across the spectrum i try to meet a lot of people and talk to them engage them it’s great fun and great learning actually so i found that you know there is a lot of fear and i found that you know there is a lot of fear and i found that you know there is a lot of fear about ai and people are actually not very clear about what kind of changes ai will bring And in this kind of fear and anxiety, we should not forget that our originality, our USPs as a human being, they will matter much more than today in the world of AI.

Because AI is what the data tells the tool or the bot to give us. If the quality of data is not correct, for example, today if the data is not reliable, the results will not be reliable. So one of my friends said that, sir, AI is not like you ask a vendor to give an AI solution, he gives you and he goes. Like an IT solution used to give a software, a computer laga diya, ho gaya. It’s a continuous engagement to improve the results. Because the AI bot will improve its own results, different habits, colors of skin and languages. I think that will matter much more in the future. Thank

A very beautiful take as put up by sir. One thing that’s most resilient is us. amongst all the crowd or amongst all the stages that are set up. Something that differentiates is our originality. Yes, and that is to be kept intact. Coming to some very beautiful solution, I would say, or innovation to education comes from a university which itself is formed on a very innovative format of education. I would request, sir, to define his definition of creativity and cognition.

Yeah, thank you for this opportunity. So, as an educator, when we jump into this new term called orange economy, so the new orange, how the orange would be. So we have seen oranges, but we have not seen orange economy. So the new terminology came which defines what creative, how cognitive, and the culture immersed together to define the human being. I represent South Asian University, which is the first university in the world set up by Sark Nation. where students come from all eight countries. So people come from Nepal to my university, people come from Afghanistan to my university, people come from different destinations. We represent Asia. So within Asia, are we same by cognitive thinking? Within Asia, we are same and we are sharing same culture.

So culture to what extent? The same culture. Are we different in culture? When we say creative, Indians are more creative than the neighborhood. Neighborhoods are more creative than Indians. So when I look at this international perspective to my institution, I engage with more students and I evaluate critically what you do better. So as an educator, when I say I am in the age of AI, we are already in the immersion of the AI. People have already started AI. Students are already using AI for different tasks. So when a student comes to me, sir, I have done this work, I ask, show me the problem. I first thing I ask show me the prompt so it is not the skill that you have done assignment you have done reports it is done by GPT your skill like that you said that your skill is how you define redefine your code how you build the skill to understand the code coding is not a new thing now lot of training usually happen but what remains us creative human being how you apply your creative brain that always you can’t beat technology always assist you I believe with my personal opinion technology always assist you technology bring efficiency in you technology support you but the decision -making is always lies in the human brain are we are using the technology responsibly we are using technology ethically there are so much concern as a educator I have to train to my new human resource And I believe this new orange economy will give lot of opportunity in the time to come to the people who feel if my job is displaced, I’m sure some new job will come that you have to learn, you have to survive and you have to adapt with the change with AI time.

So that’s my perspective as an educator.

Yes, sir. Beautiful perspective where he tries to say that culture and cognition and creativity bind us as Asia. That’s a very beautiful definition and separates us from the Western world and they tell us that this is what keeps us together. And at the same time, this is what will keep us going will be the cognition. Thank you, sir. Coming to Satya, sir. Coming from an IIT as a student, getting into a technical field of learning, engineering, and then coming to administration. I mean, all these numbers and domains, or I would say background, sound very redundant and sound very boring. So how still creativity stands with you, creativity, cognition and culture keeps you going.

Thank you so much, Swetha. Thank you very much, panelists. And I would like to thank that this question is being asked. And I just want to describe the way we are sitting here in this hall, right? After every one hour, this hall is changing with the audience, speaker and everyone. And this is the standard setup. I would like to give the answer for all the three things. This is the standard setup is being provided for all the type of stakeholders, be it global, different types. The type of creativity we are putting or hosts are putting into this, you will see after every hour, this is being changed. And the kind of cognitive inputs or… discussions are being done must be different and it will creating level of the discussion and reception of all the stakeholders and in the similar manner the kind of culture both the sides be it speaker side or audience side or host side it will be literally different so my main just to answer this question this is a very subjective and with respect to AI AI is artificial intelligent it will always be artificial and human intervention human inputs humans with inputs of human creativity cognition and this culture will always surpass the best thing I would like to agree with professor Ashish that the kind of input prompt and expertise of that particular field which always surpass and that’s why I was discussing with Upade sir that everyone is scared, children are scared I say that there is no need to be scared with them, on these things in fact, their level of artificial intelligence will be very good they will be able to give their input through their input so there is nothing to worry about

so nothing to worry about friends the walls are going to remain the same we are the emotions into those walls and that is what is going to make the difference so let’s keep the emotions and the humanness intact, I am happy to say that all my panelists here strongly say that human intelligence will supersede the artificial intelligence let’s talk about the audience, anyone who feels that the artificial intelligence is going to top us and the humans are going to stay behind or all of us are on the same page let’s start with you audience, any take on this? human intelligence or artificial? what comes first? all agree to the panel yes sir please

you mean to say there will be a timeline where this human intelligence will cease to supersede it’s a time bound super time bound position basically as AI improves is there a timeline like after certain years that AI will be better than human intelligence

please say your good name please so Saurav says there is timeline to it

I think certainly there is merit to the line of argument which you are making so as AI becomes more and more intelligent our education system is continuously under stress. It is being tested. There is a stress test happening all the time. What’s happening is that the shelf life of hard skills is really diminishing. Like if I could hold on to a skill and take my whole life career with it then it came to 20 years and now it’s a matter of couple of years, three years, four years and so that the shelf life of hard skills is really shrinking. But where we need to focus is that not only making. Earlier we used to say that don’t learn but make things.

Now it’s not only about making things. You have to understand the meaning of it. You have to apply it. Rather if you can say that not only artificial intelligence but applied intelligence is where humans are going to really be there. Because I can tell my student to code. They can make a chatbot, right? But can that chatbot tell, let’s say, a farmer in MP that whether he will be able to sell it at a good price or not? So the application of it, the solutioning of it will matter. And again, the timeline, I think it’s right now not an easy answer. But that’s the direction where we can at least all go and we know that we can expand it further.

Okay, thank you. Yes, maybe that’s one of the reason why we all talk about the fear. Is that a timeline or it will be the resilience that will go forward and the humans will become smarter or the artificial intelligence will become smarter, yes? So it’s a generation that all of us are going to see and go through. So let’s keep ourselves crossed for it that we will remain the smarter ones as the panel says or the generation sitting on that side, many of the young faces don’t even want to answer. Because they are waiting and trying to tell us. that every next is smarter one.

Yeah, so actually, as I was mentioning you that I was interacting with a lot of youngsters and in the overwhelming feeling that I got from all of them, apart from fear, is that, you know, everybody is very unclear and unsure about how the AI will shape the world in the future. I mean, he said about timeline, which could be 10 years, 20 years, I don’t know how many years, even I don’t know. Nobody, none of us are sure about how things will actually unfold in the future with more and AI systems being more and more smart, data becoming more and more strong. And so there is a lingering fear among everybody in terms of what will be the impact as it unfolds because we actually don’t know.

And there are no mathematical models or something which can predict how things will unfold. But as I said, as an administrator, as a public policy person, for me today if somebody asks me a simple question that tell me what should be the purpose of having ai i would say that you know when i go to a village i find that you know there are a lot of people sitting without any work they don’t have any money in their pockets they all look for some kind of employment and they are not very well educated so they are very poorly educated in the village school you know a lot of absentism happens in government schools in the rural areas people don’t go or whatever you know i mean all of you know this so for me i mean the for example if i talk about ai in education so i should be able to use the ai bot or ai tool to examine a person’s background very quickly and find out what best i could skill i can give to him so that he or she can fend for himself or herself have a decent job And I don’t think of anything bigger than this because there is an army and army and army of people who have no job.

And that scares me more than the AI because in the future, if in such a big country, so many people will not have work, then this may lead to social imbalances and problems. So, for me, AI should be able to, and AI does it actually, because in a class of 50, 100 students, 40 students, AI, with the help of AI, we can find out about each and every boy and girl’s learning abilities, how much quickly they can learn, and then we can design programs for them, which a human being, a single teacher cannot do. So, anything which we do with hand, for example, plumbing or repairing a vehicle or doing any hardware kind of. Everything AI cannot do.

It has to be done by hands. Robots can do one day, maybe, but then. when will that time come again I don’t know so these are my takes as far as our country is concerned or South Asia is concerned because today you know we are having neighbours Nepal, Bangladesh, Sri Lanka, Pakistan in this neighbourhood we are sitting if any one of the neighbours as we have seen in the past is disturbed the country gets disturbed so in our own interest and there is too many people all around in South Asia so if people can get some kind of job as per their abilities with the help of AI that would be the best

application so friends yes that’s an important take to understand that where the human capital will go and what will be called the human capital how does you keep it sustained yes ma

so I want to know in a developed India we youngsters from 18 to 25 years for us it is very difficult to understand it is very easy to search a lot of things on YouTube search on chat GPT but what about our parents what about our kids what about the people who are like right now in the age of 2 to 3 years and they are learning now they are depending on chat GPT or my parents are afraid of chat GPT what can happen in AI how can AI be a fraud when are we going to teach them how to use it 140 crore people when will all of them be trained how to use AI

I mean I would just say how did you teach them how to use Instagram they haven’t learned yet people are still afraid so the easier it is the easier it is it’s all about intensity education has something I will talk to everyone about it education requires an intent for sure if you have an intent then maybe yesterday a teacher first your mother and then the technology is training you to become there to reach there we will take this question again with our panelists also and also discuss about human capital per se which is the human capital human capital is scaring us and when will we be able to train it and going forward how will we be able to make this human capital so sir as a professor how do you look at professors to become better with AI?

Or what’s your take on human capital of educators?

Yeah, so this is an educator’s dilemma. To what extent we support the use of AI and the more important ethical and responsible use of AI, right? So the question came, when do we have to teach people to use AI? So as an educator, when we see, do we have to start from school? Or do we have to start from college? Or when we go to higher education? So the most important foundation comes from the school. If you look at the kids now, they are more gadget friendly. They have tablets at home. They have IPTV at home. They have mobile at home. The kid has WhatsApp too. The kid operates WhatsApp on his own. The kid has his own group of school.

Teachers put topics in it. The kid asks the meta, that I want this meta, I want an article on this topic, of 100 words, and the meta scripts it and gives it. and he copied it from there, put it in a notebook and gave it to the school. This is not a challenge, actually. People will learn. People will learn by default. People will learn by training and people will learn through pressure. High work performance environment, where you will have to learn that technology. The problem in school is, how much ability we are able to use. That is cognitive thinking. Has that student used as much brain as the teacher said, this assignment has to be done.

He copied that much and put it in the meta, or put it in the GPT. He did not make the effort that we used to make at our time, when we used to search by ourselves, open the book by ourselves, make the notes by ourselves, and he is doing all the work in GPT. So the question came, to what extent cognitive skill remains strong into the market, learning is not a challenge, learning is not a challenge, learning is not a challenge, learning is not a challenge, learning is not a challenge, government of India is also taking lot of initiative through digital skilling. Kahi saare portal create kare kiye gaye hai jahaan par government khud ye chaat ye koi bhi citizen of India un portal par jaa kar apna registration in fact I did registration yesterday only to AI readiness.

Ki main AI ready kaise ho sakta hoon. Right. I know something of AI but I may not be perfect of using the AI. So that is my ability to learn fast. Government is has launched such programs through digital skilling portal jahaan par wo free mein apne citizens ko wo training dena chaati hai. Second perspective new education policy. Government is constantly trying to make over, re -look into the perspective of policy but again the challenge comes kya hamare school AI training ke liye tayyar hai. Infrastructure AI ke liye chahiye. AI lab humko chahiye. So learning, people are willing to learn. There is no resistance to learn, but how to support. And more importantly, I always emphasize ethical and responsible use of AI.

One more example. A few days ago, people started creating their image from Ghibli. Who taught them? Ghibli images were… Millions of images were created by family, housewife, homemaker, cooking, restaurant. Everyone put their DP on their WhatsApp. Everyone put their DP. At that time, we didn’t think about privacy. Where will that photo go? We didn’t think. Instead, we thought of creative images which has been created. Now people think about GPT. A carrier creature should be created. Chat GPT will create everything which you do. Who taught? We have learned it by learning through enemies. A friend told us. YouTube told us. Chat GPT taught us. Be clear. How to create? How to create? caricature. Yes. So indeed the human human capability to adapt is an important aspect.

Hi, thank you so much for this valuable inputs like government is there, universities is there. So my question is like how we are thinking about this ruler areas. Like they say already there are many universities, there are many colleges. But still after 12 candidates, first year, second year, final year candidates is not getting that much knowledge like what is going on in AI. Now people don’t even know what is to be studied in AI. It is not clear yet. How does AI work? How AI engineering, feature engineering, this data science, data analytics fields actually work? So how does this field how does this ruler and how does this ruler and urban is fine. How will it go to ruler areas?

Like I belong to a city. Murtujapur, whose name is also unknown. So there are such children who want to learn but they don’t have money. So what is the government is planning for them? Universities which are fine, everything is best. How they can shape these underprivileged candidates economically backward class.

So, yes please. That’s a very beautiful thought that comes and in a country like ours where diversity is huge we need to understand that not everyone has that take. We would also want to listen it from both our panelists sitting on both sides of me. One coming from the government and one who has developed education in a decade. Seen India growing with it. So sir, what is the systematic approach and what it has what is the process to make all of us understand that this is new but it will not stay new. When the efforts keep going continuously, we reach somewhere. So, sir, a portal like GEM, a government -y marketplace where you have been in the part of the system right from day one of inception till today, how do you really think that the people have to trust on something of a government initiative that it will reach and become everyone’s kitty?

Any person who is having a GST number, they can onboard, register on this thing. And they can participate in various products and services of the government. And in that, as madam is asking, to validate and recognize it, all the vendors, if they have any services and products, they can be onboarded and as a reliable product and source services, we properly do vendor verification and after that, we onboard its catalog. And if all those products are to be purchased by the government, services are to be purchased by the government, then tender process can be done there and can be purchased through direct market place. So I can just say that, if I am correctly pointing out taking your question ki jo ye services aur products banenge agar AI entrepreneurs jo bhi hai jo unke product aur services banenge toh wo sarkar unko sahi madhyam se leh sakti if I am able to take yes there is a system that has to start a day 2016 jain shahid JEM shuru hua hoga humne nahi socha hoga ki that we will be able to reach to this level where every smallest of the manufacturer or vendor from the rural area, the urban areas and every part of the country can become a part of a sales or a buy, sale and buy purchase platform of that scale so it takes time for sure, technology integration and adoption and also making it a part of mainstream is a process and journey let’s listen it from Piyush Piyush how do you say for such a diversified scale the question here

sso I think AI apne aap mein ek bahaat bada democratising tool hai learning ke liye hume kya chahiye hota hai? Ek self motivation chahiye hota hai aur ek koi madhyam koi medium jo hume koi padha de jo samjha de Now this part of the problem is solved by AI Right? If you have motivation and the assumption being we all know internet is everywhere now Specifically for tier 3 towns for rural areas Now anything and everything can be learned as well as anything and everything can be built Now you will see that as a trend we will see lot of solopreneurs single person small setups kyunki aap website khud buna sakte ho creatives khud buna sakte ho marketing content khud likh sakte ho everything you it is now more empowering rather so I think it is only more democratizing and more empowering for the rural India you can build things of your own you can have aspirations which earlier needed lot more things which are now possible.

I would like to give, as a parent I would like to give your answer. I have two daughters. My elder daughter is in NID Ahmedabad. And in creativity, NID Ahmedabad is quite good. And my younger daughter is in 11th class. She is a player and plays in 11th class. My elder daughter, because she didn’t have much, I asked her how you are going to deal with AI. She said, I don’t have to deal. The answer she gave me I want to tell you how the children are thinking. Our curiosity will be reduced. Professor will also be finished. She said, I don’t need to be afraid. I am studying. I will learn that first. As long as this tool is made, it will be for all of us.

I have to understand how to use that tool. And for that, until I don’t read the subject well, until I don’t understand the subject well, there is no benefit. So I don’t have to fear about what is happening. And the younger daughter, because in her college, as you said, sir, because in addition to the responsive and ethical use of AI. So once I said, how do you do notes these days? So she said, in our college, a lot of my school children use chat GPT. So I said, you don’t use it? So she said, if I use it, I won’t be able to use myself. So this was the answer from her. So in addition to what sir, professor sir has mentioned, we have to educate them for ethical and responsive use of such kind of tool, not limiting to AI.

So perfect, sir. I would like to add one answer to his question. That. Rural urban divide has always been a challenge in India, right? I remember the time of internet 2k internet launch hua it has the perceived that internet kaha tak jayega pehle shehron tak tier 1 metro then now you see the penetration of internet to aaj gaon tak internet pohucha wo infrastructure create hua government ne utna scale up kia telecom companies ko utna strong banaya ki wo us market tak pohuchka aapko aaj ek affordable rate me data de paye right aaj rural humari population hai that plays significant role in terms of economy in terms of business in terms of small business also and I am agree that education is also a fundamental right for the student who live very far areas of India AI ko bhi wo infrastructure chahiye AI ko bhi scale up karne me utna time chahiye the way internet penetrated slowly AI also in its studies in school, in course in its curriculum, in its lab it will assimilate slowly things moving we always look at where technology comes from, where technology is made and how technology diffuses technology sometimes don’t go immediately to every places, sometimes there is systematic movement of technology from one place to another place one more thing should we fear?

it is better to learn the things we should not afraid of whatever challenges us we should adapt to it better the version is the things which challenge you, it is better to look at it, adapt it and find out the new solution that how we can bypass how we can surpass and how we can head to head head to head competition with the technology right Maybe there is one question by Saurabh That with time technology will become so strong That it will surprise human beings Maybe it could be When you as a human being Feed the LLM When you as a human being You feed the LLM What could be the possible situation of a cricket shot Then the Chetji PT will tell you You have to play this shot Which is unique Because you have to feed the LLM first How LLM will know The large language model Has to understand the human What human think first Then the LLM work in the background For the answer to be the correct one The question has to be the correct one And the question has to come from the audience And the people How do we take it forward

Yes sir Namaste Thank you Thank you for a wonderful session I joined in late It was a little far from the other one So for India to become the India of the world we are talking of a 4 trillion economy 7 .3 trillion in 2030 it could easily be 10 trillion if we start trading our people we are not trading our people so if anyone of you are connected with policy makers Indians who travel outside India should suppose I travel to the UK and I work in the UK and I pay 40 % tax in the UK then 33 % of that 40 % should come back to India if I want to maintain my citizenship of India we will become 10 trillion economy just by this if Donald Trump can play everything we can also play so that’s question number 1 if anyone has any comment on that question number 2 is someone mentioned about motivation for education and the medium for motivation motivation comes and goes I think I would like to hear all of you all all of you all of you The power of confidence and does stereotyping in the education format that we have today, does it enhance confidence or does it kill confidence?

Because I meet so many students across the country. Last week I was in Hubli, I was in Belgaon, you know, I traveled to the depths of the country. And you’ll meet students who are fantabulous. People say we have Gen Z right now. I think we have Gen X, Gen Y, Gen Z, all 25 year old, depending upon the geography they are in right now. So fabulous students, but low on confidence. They are not from the city. So what does the education system do to multiply and enhance this confidence? If confidence increases, then it will do everything.

So I’ll take the second question. I think as an education system, we have to move towards a more inclusive education system. from learning to creating to applying. And when we create, when we make things, there is a different kind of a dopamine release which is there and it also gives you confidence. If I have built a working prototype, which right now, currently the education system by and large is not really supportive of creating things. It is about learning things. And today’s discussion where we were, you joined in late, is that even this is not sufficient now. Now we not only need to create, but we also need to apply it. That is it useful? Okay, this thing exists and it works.

But is it useful for someone? This is the next level because with the AI coming in, this is where we need to be. But by and large, to answer your question, I think the confidence really comes by creating and not just by learning. I think the confidence is the key. I think the confidence is the key. I think the confidence is the key. So if we have more and more creating opportunities, building opportunities for our students across the board in education, across programs, across the board, I think the confidence level, and this is right from K -12, I am not even talking only of higher education, this is right from K -12, I think more and more creating is what we need to really instill.

Thank you, Piyush. We would say that, yes, there was a time when knowledge was the reason of confidence. I know it, that’s why I am confident. But today it is that because I can build it, I can have the confidence. So friends, we are moving from the age of knowledge to the age of cognition, from the age of knowing something to the age of creating something. That is where we are here to discuss that it’s not just the artificial intelligence that is going to take us forward, but it’s all our collective cognitive ability that’s going to keep the Vixit Bharat or the India or all of us to come back to India. because yes, we were this what we are today but to get you all back to all of us we have to stay the way we are and that is something that is going to get us in that let us keep this intact the layer intact, the context the culture, the creativity of ours with that friends, I would thank my panelists for being here with us because we have to take this stage forward and the floor will be open for all of us to discuss we also have a team to have a product demo and a few of our friends to join hands together in taking creativity and cognition way forward in education so I would thank all of you for being such great listeners and be here till the time we have the next part of this session coming forward with the product demo I would thank my panelists to be here and would request for a group picture with all of us can we have a group picture so friends this is an inaugural or unveiling of one of the products that we say may I request the team also to come forward the team here may we have Ajay Rivalia sir, Viplav sir Nandaji, Garima ma ‘am Mansi the moment Vijay sir may we please have you here yes we have discussed about creativity and cognition this is going to be the tomorrow and this is something that is going to keep all of us intact so we are the torch bearers to it and we present to you a product which is going to make it better and educate all of us for creativity and cognition may I request our mentor Unkar sir to please join us Thank you, friends.

And now put your hands together for a product demo, which the AI -led education platform brings to all of us.

becomes unique, adaptive and future ready. Powered by machine learning, LLMs and agentic AI, the platform intelligently maps growth, interests and creative potential. The platform fosters mentorship, discovery and meaningful skill development. So, from recommended courses to resource hubs and spotlight mentors, ENCODE the creative learning network. Create, connect, collaborate. Shaping personalized journeys for the creators of tomorrow. In a rapidly evolving world, SHAPED by ai creativity cognition and collaboration are the new foundations of learning where the creative learning network meets the future of intelligent education so this is not a static learning it is dynamic responsive and continuously evolving with the learner at the ai impact summit bharat 2026 learners educators and innovators engage with encode’s live ecosystem they can explore domains interact with creative pathways and experience how technology and creativity converge so Design the world you want to grow in.

A philosophy that places creativity, exploration and individuality at the core of education. With an intuitive interface and curated experiences, ENCODE enables learners to discover, engage and progress. At their own pace.

Thank you. Thank you. May I please request your statement for how do you take it forward along with your current work that you are doing how will you add it up as a creativity layer to the systems

No, I think this is what would separate a graduate from a real world professional because we really need this layer beyond this, everything wrote, everything monotonous is going to be taken up you know one gentleman asked about the timeline, that question is pretty real and I think partnerships like these will really help us future proof our students, so really looking forward

Thank you sir, we also have our team from MEC Connect from across the borders with us to join hands The Next Gen Academy Thank you

So, we are proud to contribute to this academic industry partnership by bringing the design -oriented courses to our coding students. Our focus is that our students should not only learn the coding. They should have idea about the design thinking, digital thinking. They should apply all these stuffs in the product development. We want to make them entrepreneur. So, definitely this product going to help us a lot. Thank you.

Thank you, sir. We have a strong, strong education partner with us called Nimbus. Yes. Learning is already there with the academic institution. So, I saw this entire presentation was really great. One of the thing which, you know, I saw here was with learning, the accessibility should be there. So, we have solved the problem of accessibility. But with CodeEDU, I guess collaboration, providing the next -gen courses, exploring or connecting or creating network with developers. Definitely help the students to be industry ready. And, you know, really do wonders into this area.

Thank you sir, the make connect We are going to I am happy to see that the product, to be frank we are too excited as well and I as she said that we will be taking it abroad and see that we have a platform of students so we will be definitely taking it and joining hands with them on this Thank you. So thanking our partners may I request our partners Ajay Rivalia sir, Vipulov sir to please come forward for this for marking this milestone time that we have we have good education partners with us who plan to take us forward not just across the country but across the continent and make our intent stronger make our intent stronger within MOU that yes together we stand to make the education more meaningful for the Vixit Bharat to come so may we have a picture to document this All of us are overwhelmed to stand on a stage which the government has provided us with, so we want to be a part of this milestone.

Thank you. Thank you. Piyush sir, Gyan Prakash sir, please come on stage. Thank you. so with this I will conclude this session I hope everyone enjoyed this insightful and wonderful session and everyone agreed with this AI may automate ecosystem and system but creativity determines direction thank you so much everyone

So congratulations to all of you. You should be proud. And I just want to say that on behalf of the 30 ,000 AMDers worldwide, and particularly 10 ,000 in India, I just want to congratulate you and thank you for this opportunity to have this discussion. Since we are a small group, I think we’ll keep it informal. And I want to make sure that somebody please keep track of time so that I do justice to my colleagues here and the dais. The topic that I’ve been asked to talk about is sort of building AI readiness from compute to capability. In AI, in the field of AI these days, there seems to be an over -indexing of AI and GPUs. When in reality, AI is much broader.

GPU is obviously a significant part. It’s a part of the core infrastructure. But what we do at AMD is to really provide a full suite of AI capability from AI on AI PCs to core infrastructure to all the way out to the edge. And I have my colleague Tim from AMD, so we decided that we’re going to tag team. And so I’m going to focus perhaps a little bit on the sovereign side, and then Tim can focus on the enterprise side. That’s okay with you. So let’s just talk about sovereign AI in practice and exploring the motivators. So this particular slide is something that is created by the Department of Energy in the United States as part of a new initiative that was kicked off by the Trump administration called the Genesis Initiative.

and I had a role to play in terms of trying to support and address in crafting this initiative and the framing is very simple. If you look at the top line, I don’t know whether this has a pointer, it’s okay. Okay, so the top line, the white line is funding in the United States for R &D. Today, the United States spends about a trillion dollars a year in R &D. That’s just my involvement. Not all of that is government spending. It’s roughly about, say, 20 to 30 % U .S. government and the rest industry. The bottom line is what we consider research. Output efficiencies. So the problems are getting harder. it is getting more challenging and even though we are trying to tackle really important problems the sense is that throwing money is not having the same rate of return and this slide basically asks the question how do we reduce the gap and at least the thesis for the Genesis mission is that you can use AI as a way to accelerate scientific discovery the Genesis mission has three areas of importance for people who don’t know about the US Department of Energy the US Department of Energy is the nation’s largest physical science agency so it has it operates through 17 national labs and some of the earliest ones, like the one Oak Ridge National Laboratory, which I used to lead before joining AMD, came to being during the Manhattan Project.

And Manhattan Project, about 65 % of the entire funding of Manhattan Project was at Oak Ridge National Laboratory. And in addition to, you know, in fact, I think the Prime Minister mentioned that, about nuclear energy, both the destructive aspect as well as the significant outcomes that came out of that from nuclear medicine to nuclear navy to nuclear energy. These all came, you can trace back to Manhattan Project. So U .S. Department of Energy is not only responsible for energy, but it’s really a science organization. It’s got three priorities. One is just discovery science. The second is energy. And the third is national security. and national security. America has a really interesting thing, a way of keeping the nuclear arsenal away from the military in the sense that it is the U .S.

Department of Energy and not U .S. Department of Defense or Department of War that is responsible for the nuclear arsenal. And the three lab directors, Los Alamos, Livermore, and Sandia, has to certify each year that the arsenal is ready for the President of the United States. So this is a piece of the hypothesis. If you think about research, you can look at the left side. It starts with hypothesis, then you conduct experiments, get the data. And today, you take the data, use AI, machine learning, et cetera, you get analysis. What you’re trying to do is to make this much faster so that you can have science outcomes coming out. That’s it. do it in a reduced cost because you cannot throw more and more money at this problem and enhance global collaboration.

I think there is a genuine interest on the part of the U .S. that this whole premise is not just a U .S. issue. And so I think that it’s likely announcements that suggest that countries like Japan and Europe and UK and others may be part of this overall approach to drive sovereign AI for those aspects of AI deployment and scaling that is uniquely a government or state function. So as I mentioned broadly, scientific discovery, energy and national security. But if you look at the scientific discovery further to the next step, then you will see healthcare, education, skilling, all these things. Fundamentally, a government function. And this is not an easy task because if you think about how these institutions’ research is done, I mentioned large fraction of it in the private sector, a lot of it is done in academia funded by government, and then of course in national labs in the United States, India has its own set of national labs, academia, etc.

So what you need to do is take a look to see how do you integrate all this data? At least the U .S. Department of Energy operates these large, multi -billion dollar light sources, neutron sources, specialized scientific experiments. You need to be able to incorporate all these things, so you have to federate the compute and data, you have to have cloud -enabled lab operations, which is not how things are done today. Security and governance by design, especially when you’re thinking about public -private partnerships, even in the enterprise commercial scale, you want to make sure that you have secure computing, you have confidential computing, you can maintain integrity, but also if you think about national security, you have additional layer, and then you want composable standards versus infrastructure.

So this particular program was kicked out by Secretary Wright, well the President of the United States, then Secretary Wright, and the last fourth quarter of last year, and the first announcement was done with Lisa Su, our CEO, because one of the things that they wanted to do was a unique public -private partnership, and so the core infrastructure, which is currently called American Science Cloud, this program is just being stood up, is going to be run on an MI355 cluster, which is what this entire program that is aimed at driving innovation is going to be run on. And so we are really excited to be a part of this. initially US and soon an international effort to drive innovation in those areas that are uniquely government function.

I’ve had a ringside seat in computing for the last 30 years and been responsible for a lot of supercomputing deployment, a dozen or so. The last four or five of them were number one systems in the top 500, each first of a kind. This is another important thing. Innovation, if you think about AI, AI didn’t happen magically with NVIDIA or AMD. It happened because US government took the risk to invest in first of a kind systems. So we were the first to deploy 30 ,000 NVIDIA GPUs when people thought that CUDA was a four -letter word. Now everybody thinks that this is this amazing software, but change comes hard to people. And so I just want… I want you to know that…

particularly all of you who are youngsters things are going to evolve. If you think that AI is just like the Prime Minister said, it’s just the early stages. So you have to be open and you have to be part of this drive for effective, scalable and impactful AI. Then deep learning came where this mixed precision computation then generative AI and last year was really authentic AI and some of us think that this year we’re going to focus increasingly on governance. Governance does not mean regulation there is a role for regulation by governments but governance is that how do you want if you want to have agentic systems driving, accelerating innovation you want to make sure that the output has a person in the loop.

The one way to simply think about it is that if you are researchers here, if you have a professor who’s got a dozen students who are doing research you don’t let the students just go publish things. There is the professor’s responsibility, there is the peer review committee, etc. So you want that human in the loop before you can update and let this thing to drive innovation while it also allows it to do things that AI does best. So this is how we think about compute to capability, a model of national AI readiness. We want its rest on talent, talent and readiness of talent, giving people access to compute and models. Research enablement is key because you want people to operate AI in an environment where you’re questioning things and innovating all the time as opposed to assuming that what we in the industry is providing you is the only solution.

So I think… If you look at countries that are leading in AI, there is a very strong R &D and innovation foundation that is allowing you to lead because there are people who are questioning every time somebody says something. to make sure that it is validated, it’s continuing to innovate. Start up an innovation lab because you want to take these ideas and start new companies because many of these new innovation and new technologies may be led by people with new ideas and opportunities and of course ultimately enterprise and public sector adoption. We strongly believe, and again I heard Prime Minister Modi say, open ecosystem and open source, open platforms. These things, if you think about iOS and Android, India I find has a lot of penetration of Android systems because inherently open systems allows you to innovate without getting locked into vendors.

And so we at AMD have a commitment to make both our hardware infrastructure and our software infrastructure to be based on open standards so that you can innovate. Around this, any part of this infrastructure. can be part of a new startup or new company adding to that. That is also an important way for India to become part of the supply chain and the semiconductor ecosystem, because you don’t have to start with an attempt to go in for two or three nanometers. You can actually do amazing work and be part of leading -edge technology at different form factors. So I mentioned a little bit about how we think about agendic flows and AI scan work. This is simply the way you think about it.

The inner loop is an autonomous loop where AI and agendic AI does things, what it can do fast, it can operate. If you have 100 ,000 GPUs, you have 100 ,000 agents tackling this problem and it can actually go through the hypothesis -driven experiments and systems. So you can do simulation, campaign scale coordination, machine speed execution, etc. But we do not allow it to update. the outcome until a human in the loop has had the opportunity to validate to make sure that we don’t have unintended consequences. Now, how do you build this thing? So this is, if you haven’t gone to the AMD booth, I would encourage you to do. This is my only plug in this presentation. We spent a ton of money to bring this Helios rack here just so that you can have a sense of what is, not what this particular rack can do, but giving a glimpse of what is possible the next year and the year after.

So we, in 2007, myself and two of my colleagues started what is called the Exascale program. And the challenge was to deliver an Exascale system for under 20 megawatts. Because if you had just scaled the capability in 2007, it would have taken three to four gigawatts. And we knew that the government was not going to… sign, $4 billion for power, just electricity alone to run the computer. So we were motivated to drive that. And we delivered that first exascale system, Valfrontier at Utrich, for less than 20 megawatts. Everybody thought it was crazy, it cannot be done, but there are some things, when you put audacious goals, people rally around and then deliver. This particular rack, in one rack, there are 72 GPUs that will deliver 2 .9 exaflops of AI compute, which is FP4, not FP64, just to be very clear.

But for AI capability, you get 2 .9 exaflops of compute capability for 220 kilowatts. Right? That, even for somebody who’s been in this field for a long time, it’s just mind -blowing. this is where we are headed AI is the fastest adoption of any technology that humanity has introduced we’ve gone from 1 million active users to 1 billion in a matter of just a couple of years and we are headed to 5 billion users so there is a lot of opportunity to innovate in this field and all of us are going to continue to create these opportunities as Lisa said, we are entering the Yara scale so already people are thinking about the next 1000 so let me just say you can get to Zeta scale by just taking 300 of those racks and putting together and then it’s another 3x so I would say in the next 10 years maybe we would be at this 10 ,000 factor so the kind of problems that you are thinking about should not be constrained by what you can do today by the time you figure out the solution for an important problem compute will be there.

That is what we in the industry like to promise you. And I think advancing national economies, these are one of the things that people might you would be forgiven if you thought that does AMD do these things and how prevalent are our compute capabilities. I think Tim is going to tell you that our GPUs and our systems are in every hyperscaler globally and when it comes to HPC and national priority missions, AMD is the leader. If you listen to President Macron, he referenced Alice Recop, which is the first AI factory that the French government announced, the CEA announced, which is based on AMD MI430X, which is a variant of the MI450 on the right that you see outside.

I will close by saying that a shared path forward is really what we are looking for. I know India is in the early stages and we are really delighted to actually have this conversation. Thank you very much.

I’d like to invite our next speaker, Paneerselvam M, CEO of the METI Startup Hub at Ministry of Electronics and IT, Government of India. Dr. Paneerselvam M is a distinguished leader with over two decades of expertise in innovation, management, strategic growth and market development. He’s been instrumental in advancing India’s startup ecosystem and fostering impactful partnerships between the government, industry and entrepreneurs. In his

drawing insights out of this data and then comes the interface layer where most of it is going to be really driven by agents, by agentic AI and of course as Thomas mentioned there is always going to be a human in the loop perspective but as we progress this is going to change as well. So you know the two fundamental things that I want to share, one is the entire transformation in the readiness space for AI is an opportunity for you know certain change and intent needs to be very very clear and then comes the curiosity to learn about this little bit more for each business owner and then comes the implementation part of it and then start -ups have a very very critical role to facilitate this because you are coming in almost as AI natives, working with an understanding of this and you can really go out and demonstrate value.

and help implement the entire readiness, improve the readiness quotient or improve the readiness quotient for small and medium enterprises and ensure that, you know, this is a broad -based growth opportunity for businesses across the country and not limited to just a few of them, right? So there is huge potential and I think enough has been spoken. The summit itself is a proof of the kind of curiosity. We have had 267 ,000, you know, registrations, people who have registered in the last five days. Unexpected, overwhelming response to some extent that we couldn’t really handle it, right? At the same time, it gives us immense pride and excitement for the amount of curiosity and excitement for the amount of curiosity and excitement for the amount of curiosity and the youngsters in India, across India.

travel here from the length and breadth of country to understand what is AI going to be and how this is going to impact and what the opportunities are and that is itself is a fantastic starting point and and as I said you you know there’s a lot of happens this is in Indian sovereign models coming the tech the five layers the infrastructure the design you know all the layers are being worked upon in the Indian context and we are ready as a nation we are ready as a government to facilitate this this real disruptive transformative technology but the truth is it’s you know it’s also important for it has to populate into all the layers of the society beat just not just limit itself to large and large corporates but also to to small and medium enterprises and of course it is already populated with the large and medium enterprises and of course it is already populated well into the d2c to the individual users and it’s much much beyond the beyond the chat, GBTs of the world.

So with that, I think I once again take the opportunity to thank the entire team from AMD and we have had some interesting conversation and I look forward for the continued partnership with AMD and METI Startup Hub because in our perspective, corporates have a huge role to play in the success of the startups. Thank you.

Thank you. There’s a couple of things that I want you guys to think about as I go through my talk. 30th of November, 2022. The world changed. ChatGPT was launched. And I’m willing to bet that everyone in this room, myself included, what we thought we knew about AI changed. Two years ago, what we thought even after ChatGPT changed. A year ago, what we thought changed. And what I’m hoping is as you leave here, other things would have changed in the last 45 minutes of listening to these talks. Okay, so I’m going to skip through the reason why we need to go through and need compute. But I think one thing that is very, very, very important is things are moving so fast.

And things are moving in a way that we cannot predict that the only way that anybody is going to be successful is an open ecosystem. And, you know, both of these themes. And I think the other gentleman before me have alluded to this as well. and I’m going to take you through specifically around software. I mean, everything to do with AI really, I’m a hardware guy, I used to design chips, but everything today is software, right? And I was talking to one of my colleagues and I said, okay, so I’m going to India, I’m going to do all this, we’re going to go through. And I said, is it really going to be the, you know, are they going to understand it?

And he said, Tim, India is software. This is what we do. He said, you’re going to be in front of the best people in the world that are going to understand what you want to talk about. So I’m really going to focus on the software side of that. And one of the things that I wanted to do, understanding that we had our esteemed colleague from MITEI here, is we do have lots and lots of experience in this space. And one of the things that I want to highlight is some work that we did with Lumi in Finland. Now, why is this important? So within Europe, almost all the languages are Indo -European, right? If you know a little bit of Greek, if you know a little bit of Latin, if you know a little bit of one of the languages, there’s 27 countries in Europe.

so let’s call it 27 languages and then you have Finland Finland is a Uralic language nothing to do with any other language in Europe absolutely different construct, different base different absolutely everything and so what we found working with the guys in Finland is they were coming to us because they put in this Lumi supercomputer and they said okay so we have a small country in Europe, 5 million native speakers and we have to take all of this work that’s been done English, big codex Spanish, big codex, Hindi, English big codex of all of that to do your training, suddenly you have a language of 5 million people how do you get that language into your LLM model so that it becomes useful now I’m probably going to get the pronunciation really really wrong here okay but I did actually use chatGPT to look at the 22 Indian languages right so if we look at Bodo, Konkani, Dogri, Sindhi, Nepali there’s less than 5 million people that speak those languages so how do you get an Indian LLM that caters for everybody as we’ve seen from President Modi AI for all of that kind of thing and this is the kind of area that with Mighty this is where we would like to work with you guys and be able to bring some benefit of the work that we’ve been able to do now remember the first day 30th of November 2022 this machine was inaugurated so it was put together all of the systems were put together it was all brought up the chips were made years before this machine was inaugurated my birthday 13th of June 2022 6 months before ChatGPT came out so this machine with 12 ,000 GPUs that had the foresight from the Finnish government was using AMD technology to run AI before ChatGPT came out.

So a lot of people that think that a lot of the stuff from AI has come from a specific area. This again, think of our way of thinking. We were there and we have the ability. We actually did the Bloom 176 billion parameter model. It was an open model made for European languages. So again, we would love to bring this knowledge and use with the Indian ecosystem to make this successful for everybody. I’m not going to spend a lot of time on hyperscalers. They’re obviously an important part of the market. It’s where a lot of the capabilities go into. We’re there. We have tens of thousands of GPUs. We actually have, as Thomas mentioned, we have the Helios system coming here.

Please go and take a look at it. If you like Harvard, it’s an interesting piece of kit. But really the idea here is whether you’re in a hyperscaler… or whether you’re in any other area, there is an ability to have a wider ecosystem. And again, inference, so AMD specifically, it’s not really an AMD pitch, but there was an idea in the market that AMD was inference only. That dates from Q1 2024. That’s two years old. So again, we have to kind of change that thinking, right? That’s older thinking. We actually now, again, completely open source. There’s a Primus ecosystem or a Primus tool for the open source, which enables you to be able to do all of the training that you need to do for all of your Indic languages or for your use cases, which again is completely open.

Enterprise AI. This one I think is an interesting one. I know when I started going out to customers and going out to enterprise customers, the difference in customer knowledge on what AI was, was amazing. You go into one customer and they say, okay, so this is our use case and we’re seeing these kinds of sizes of matrices, so we’re doing these optimizations. And then you go into another customer and you say, what are you doing around AI? And the guy goes, oh yeah, we’re doing Gen AI. Okay, great, yeah, what are you doing with Gen AI? We’re using LLMs. Okay, great, so using LLMs, what do you think? LLMs. And they had no idea, right?

It’s just, we have to do something with AI. And that has changed over the last 18 months and chatbot was something that most people said, okay, that makes sense, I understand chatbot, we can fine tune the model, we can do an internal AI system within the company. And now we’re starting to see with the agentic workflows this entire plethora of different use cases coming through. And so how then do you take it from a research institute or people that actually get onto your accelerator, whether that’s a GPU or a TPU or an FPGA or whatever else? and get it to a stage where actually people within a corporation can use it. And so this is something that has been understood.

And again, no lock -in, open, everything here is something that can be used without having to tie you into one particular area. And actually, I’ll come on to it a little bit later as well. It’s also something that I’ve been very impressed with, with the infrastructure that MITEI have put into place. In this case, with the public -private partnership, you have GPUs, you have TPUs, you have Inferentia, you have all of the different types of accelerators available to you within the Indian ecosystem that MITEI have made available to you. I’ll come on to that a little bit later more. But again, the idea here is that whatever the ecosystem is, or whatever the compute that you’re using, you’re able to go from an area where, whether it’s in the cloud or whether it’s non -prem, you have an ability to be able to give your employees within your enterprise an ability to be able to use that AI assistant or tool.

Neo clouds so these are the kind of what we call the smaller clouds, you know, they’re not the hyperscalers they’re a little bit more nimble they are a little bit more available to doing things a little bit different a lot of these guys are doing sort of bare metal and managed Kubernetes services, but it is coming to areas where they’re becoming like APIs, token factories there’s an ability for these guys to be able to provide you with compute quickly easily and at reasonable pricing to enable you in whatever it is you’re trying to do we find these are the first movers in the market and again in the same way that we’re integrated and working with the hyperscalers, we have these relationships with the Neo clouds and actually we’re working with quite a few of the guys here in India as well to make that available for you as well, so the whole idea again here is there is that compute that’s available please go out and understand the benefits or the trade -offs between the different types of Kubernetes services that you have out there and get the right solution for you guys.

Now, I’m assuming that most people here are going to be startups. And again, startup is an interesting area, right? So you have a startup, you know what you want to do, you absolutely are laser focused on getting your MVP out there, getting in front of customers, how do you generate some value, how do you generate some revenue? Although that these days is less and less important, it seems, as people get funding even sometimes before a product. But one of the things that you guys have to be sure of is that the compute that you have and the capabilities that you have are capable for the products that you actually have to then go and put into position.

And so this is an area where we understand that proof of concept, it’s very important. And again, I was chatting with the CEO of Mighty here before, it’s something he was saying, you know, POC to PO. You know, you have to be able to make sure that you understand the technology and how you can take that to market before you can actually go and invest. So we have a couple of different ways that we can help here within the ecosystem. You could actually go on there right now, there’s the AMD Developer Cloud. You can get, I think it’s 50 or 100 hours of free compute. You want to go on, how does AMD work, you know. It’s always going to be dependent on use case and what you’re trying to do.

But there is a huge TCO advantage, which of course is important for startups. Get onto the Dev Cloud, get it working. We actually provide Docker containers, so that’s everything put into a single Docker. So you can download a Docker and run it, so you don’t have to spend your time and your energy installing all of the software, putting everything together, get everything working. We’ve done all of that for you. Take the Docker down, get your model off of Hugging Face, get your weights off of Hugging Face. Use your own model and do something else. Whatever there is that’s in there, in the open source ecosystem is there and it’s going to work. Give it a go.

Give it a play. And then of course from that we can… can take you into our accelerator cloud a little bit more sort of hands -on, making sure we understand what you’re doing, helping, guiding, and assisting you in moving yourself forward there. And then, of course, we have the relationships in with the industry, you know, try and buys, being able to get you access to the computer, being able to get you the right solution at the right kind of price. So this is something also that I really want to highlight. So day zero support of models. Now, we announced this. So Quen3 Codex came out last week, day zero support on AMD. Baidu came out with one of their paddle models this week, day zero support on AMD.

What does day zero support mean? Well, it means that it’s not the first time we’ve seen this code. It runs on AMD. It’s guaranteed. It’s optimized. you know a lot of people think that to run something in AI you need a specific GPU the whole point is with day zero support absolutely false right again with Lumi pre -chat GPT in 2022 we were building LLMs for effectively an Indic type language languages right and so the ability is there if there’s a new model coming out you want to run it you want to test that you want to see how it works for you guys then that is there and runs out of the box and you know again if we look at this line in the middle you know PyTorch if you look at the history of PyTorch you know there were lots of signatories on PyTorch to make sure that was available for everybody AMD was one of them this mainly comes out of Microsoft and Meta who did not want to be closed in to a single supplier so actually what you’re doing with PyTorch is you’re writing Python code right you’re not writing vendor specific code it’s an open ecosystem that’s the whole point right you don’t want to be tied in you know it’s gonna slice for innovation it’s going to increase So PyTorch came out and that is the basis of 99 % of all of the customers I talk to, right?

They’re all writing Python under PyTorch. JAX is then coming forward. Triton, this is a Python -like language which is specific for gem optimization. Again, if you’re getting to that area where you’re actually seeing the gem sizes that are coming through from your operations and want to do gem -level operations, then Triton enables you to do that at the compiler level. So then you can be completely agnostic of what the underlying hardware is. The ecosystem and the underlying compute becomes kind of abstracted away because Triton enables you to run on anybody. It’s just a compiler for the new architecture. If we look at these models on the bottom here, President Modi this week has announced the first 12 Indian languages.

I can’t wait to get you guys here. right, fully supported day zero support, you know just to give you an example here, DeepSeek of course when DeepSeek came out, they did some things a little bit special multi -head latent attention was new we had day zero support with DeepSeek why? Because we’re one of the main contributors to SG9 there’s not a tie -in to an inference engine here, it’s an open ecosystem so we were able to come out of the door with better TCO, better performance, better cost and full support through SG9 on that DeepSeek model which was you know, the leader of its time because of our complete commitment to the open ecosystem just to give you an idea, again you’re walking out of here in 45 minutes with changed ideas, this is what we’re going for here I did have two minutes I now have five, I don’t know who bought me extra time but I owe you a beer Okay, so really actually that’s kind of the end of the pitch here.

One thing I would say is we do have a booth here at 5 .10. I’m sorry, I’m going to do a little bit of an AMD plug at the end here. But do come by and see us. You know, we actually have some of the neoclads there. We have some model creators, vendors, some ecosystem partners there. You know, come see, come change your mind. Come see what’s available within an ecosystem with the compute that’s available for you guys. Okay, thank you.

So first of all I’m Gilles Garcia I’m French so we can talk about LLMs for French language if you want so I’m French, I’m based in France but I’m covering worldwide and I’m focusing on physical AI for the communications and robotics and industrial so we have been talking a lot about AI and most of the people are thinking AI means GPUs, big cloud and what we are seeing is a big shift, that’s another change that we are seeing, change management, so I’m the change management first but changing is we are seeing the AI moving into the edge and moving into the far edge which is industrial, robotics vehicles as well as the networks and so for that you need to have different type of beast, GPUs is one aspect of it but you need to have very profound different technology that AMD has as part of the bread portfolio that we have, these technologies need to be able to send to the market and we need to have a lot of that are able to send the data to the market and we need to have a lot of and we need to have a lot of that are able to send the data to the market and we need to have a lot of that are able to send the data to the market that are able to send the data to the market act, react in a so quick manner that there is no time to go back to the cloud for that.

And so these technologies need to be, of course, that will be inference, but need to be able to take decisions and act very safely, reliability, reliable, without having to rely on the cloud. And so that’s a new change that we’re seeing at AMD on the physical AI, which will become very, very important for us, is how do we take what we have learned in the cloud, and how do we make it available in the physical AI? Software is a big thing. Full stack, meaning hardware and software being able to deliver to the customer solutions, is what AMD is aiming for. And so our CEO, Lisa Su, was saying, it’s AI anywhere. And one size does not fit all.

Meaning that if you want to address a robot you can put a GPU into it, it will burn to hell. So you need to have a very dedicated accelerator with a high software stack, open source, that will be able to have this robot perceiving, visualize, act, touch and be able to act accordingly to what his purpose will be. At CES early January, Lisa Su brings on stage Gene01, which was the first humanoid built on AMD technology. That’s just impressive. Everything has been done by a startup in Italy to make this humanoid being able to sense, visualize, touch when somebody is touching it and when it’s touching something to act and react very rapidly without having to rely on the centralized source.

So I will not be longer than that. Physical AI is probably something that India, by the way, will have a lot of things to act into. Because GPUs are there already where physical AI is something that you will have to create. A lot of things related to medical, related to autonomous networks, autonomous cars, autonomous plants, industrial, and that’s where I think India will start, with all the startups and capability to use accelerators that are much smaller than what GPUs are, and this is all available today in the EMD portfolio. So I will stop here, encourage you to come to the EMD booth, and we can continue the discussion. Thank you.

Well, so we gave you a lot of information on AI, gave you four different accents, I think the French guy probably carries today. But my one message is that stay curious, as all of us have said, things are going to change and continue to change at a rapid pace. And, you know, people talk about so many thousands of GPUs, that will not be the main thing. and I think that’s something that we need to because you will find that we there’s a whole lot of interest in trying to provide you with even more powerful GPUs for their infrastructure while at the same time provides you very lightweight low power at the edge and so I think stay curious look from the from a start -up community point of view for a research point of view but academic point of view look for really interesting problems challenges to deliver the infrastructure that you need because ultimately this applications with where it is going to change society and life that’s all thank you very much Thank you.

Thank you. Thank you.

Thank you very much for having me here. at this very, very prestigious event. I just came in from Mumbai in the morning, and what I see over here is, I mean, I think it seems to be the microcosm of the globe, in fact. So thank you very much. Yes, I think, you know, I take all these compliments on behalf of Max, and I think it starts and ends with the trust which is sort of reposed by patients at our hospital system. Today, our occupancy is at least 10 % to 15 % better than the next best player in the hospital system. And, you know, one of the things that I want to point out is, you know, AI seems to be sort of the buzzword, of course, today.

But five or six years ago, when we started our journey, we started bringing digital technology at that point in time to the core. And what you see today, what you experience, and, you know, you mentioned better outcomes, and perhaps… patient services. But that is what you experience. What you don’t see is the technology behind it. And I think that is the true test of technology, and that will be the true test of AI as well. When you don’t interface with technology, but the experiences are improved. Having said that, I think, you know, like I said, we started this journey a few years ago. We started by creating a common -size data lake for all the patients which have been through our doors over the last 15 years, and which are doing so on a real -time basis today.

Having said that, you know, these were our attempts. We tried to sort of create a closed -loop system, like Google, so to say, for our doctors and our patients. But, you know, we, like many people, faced very early, very big setbacks because we didn’t have the technology. Because when we used to do search results, we used to get zero results. in the search engine because it wasn’t sort of native to the language, and that’s stuff that we’ve been playing with. But having said that, I think the early days of AI are going to impact tasks rather than, although one is moving towards institutional, adopting it from an ecosystem standpoint, from inculcating it within the institution, so it becomes an intrinsic part of the institution.

But I think today it’s affecting our tasks. It’s affecting tasks of efficiency. You know, we’ve already started doing predictive analysis of beds which are vacant and available and so on. It’s working on safety measures. I think though the early sort of wins that we have, especially with respect to patient satisfaction of the risks and so on, I think clinical support, you know, it’s data collection, a lot of… time by clinicians was being spent in the past to collect data. now a lot of that data is being collected through forms which are in our apps today. And you can speak to them. It kind of collates in a particular manner. So the clinician actually spends less time in perhaps gathering history than in providing a little more value of the value chain.

Great. And I think, Max, I mean, as you mentioned, there is this data lake that you have created is quite ahead in terms of digital adoption. And I’m sure when you would be starting, and this is a term that we use and see quite a lot, that adoption of digital in a hospital. So is that what is also happening on top of this large data lake and the EMR solutions that you have created on, for Max, is there like a AI adoption wave that is happening? And do you think, like, when the digital adoption happened, things such as NABH, ABDM, many of these things started coming up, talking about policy, talking about regulation. In AI adoption, are there any challenges, any things that you see that can help in this adoption to be much more faster?

Or you see that people are just going all crazy on getting AI adopted in the hospital settings?

I think, you know, there is a desire all across, you know. But having said that, desire does meet reality. I would say more than occasionally. And that comes in the form of failures, which are welcome, sort of. I mean, we quite welcome it, actually, because the more you try, the more you will fail, and the more you will sort of have better outcomes coming into the future as well. So we’ve had a lot of failures, I can tell you. You know, whether it is the longitudinal data of. Patient or. looking at, you know, ICD -11 norms, you know, tagging our data with respect to the WHO. I mean, we’ve been failing left, right, and center.

We’ve been reasonably successful as far as ICD -10 is concerned, but I think 11, you know, most sort of layers that are available in the market don’t work. The ones which work are very, very expensive. You know, so we’ve started, you know, we’ve been in -housing a lot of this. So we’re toying around with it. I have no doubt that the speed at which we are failing and the amount of failures that we have, shortly we will run out of all excuses and failures, and it will be like Edison, right? You would have found out every way to fail, and I think perhaps the only way to succeed will be in front of us. So, yes, there is a lot of enthusiasm, you know, towards adopting it.

We see this as a future. I think everybody does. There is, we, of course, have to be very, very careful. Because unlike, you know, let’s say something like education, where if you’re imparting. perhaps incorrect information, you know, it can be resolved. But this is healthcare. I think patient safety, data privacy, these things are right up there. We have very, very little, you know, standard deviation possible in what we do. And so it requires a large extent of supervision, I would say. And perhaps it will continue to for years to come. Although it makes life easy for most, but, you know, at least from a clinical prescription outcome, it will require a lot more supervision to come as well.

Sorry. So is it now the priority for hospitals? For example, when the digitization adoption happened, it used to be a priority for CEOs that, okay, you have to make sure that all the billings are online. You have to have all the JCIA. You have to have all the discussions and UHS. ID created and so on and so forth. Is this a priority today, adopting AI at hospitals and as a KRAs for your CEOs or operators? Is that what, has AI reached that level today at hospitals?

No, I think clearly, clearly it has. And it’s really out of, I think, two sort of drivers that I find at least, and you know, this is at a very, very, at the outset level. I think one is the way the world, the consumer behavior itself is changing. I mean, a lot of the searches used to happen on Google, a lot of the searches now are happening through different platforms altogether. And the way they sort of seek, whether it’s their thought about your website or, you know, when they’re looking at, if you simply ask which is the best cardiologist in Delhi, you know, there’s a different way of people reading into that early and there’s a different way of people.

So you have to, whether it’s your collateral, whether it’s your digital. assets and so on and so forth. You have to make those changes. Information, I mean, if I look at ESG, if I look at investor ESG, how do I improve my ESG score? I mean, it’s like an encyclopedia out there, right? You just ask it any question, it tells you to do so. How should I present my annual report? How should I present myself? I think, you know, pretty much, you know, it is intrinsic to now everything that we do from that standpoint. Second is how can I use it as a tool to improve efficiency? And these are low -hanging fruits. I’m talking about the low -hanging fruits before we even, I mean, kind of, you know, absorb the entire ecosystem or create that ecosystem or participate in that ecosystem.

Make it a part of institutional habits, right? I think even prior to that, when we’re looking at it as a task stage, you know, how is it that I can improve? Now, you know, if I have a particular waiting for my patients, okay, how can I do predictive analysis of room availability? When I’m looking at discharge, how can I sort of this thing? When it comes to patient summary, how do I get, how do I unlock the time that my doctor spent on patient sort of history and so on and so forth. That all improves efficiency all improves outcomes see eventually the lens we are looking at it from is efficiency is accessibility is safety, is clinical support and finally to the experience I mean it’s quite a bit of breadth that you’re looking at AI

but a little bit more on generic terms everybody says that technology is moving very fast or things are changing so fast AI is also changing so fast and we also keep doing that like we want our businesses our operations, our sales also run very fast is more your internal feeling how are you feeling? how are you feeling? how are you feeling? health institutions moving as fast as the technology is moving even people in the organization be it doctors be it nurse staff all of them are looking at it and a lot of this is about India AI Summit as well because government is looking for educating people on how fast things are changing and we should all be ready for it so what are your views on your institutional readiness people in your institute and in general on this whole AI moving fast

so I think first and foremost also depends on you know the institutional culture we are very clear about one thing that we have to be more sort of circumspect about it than anything else we must go up the learning curve as far as AI is concerned things are changing very very fast we have close to 43 3000 healthcare workers which provide healthcare. You know, that means there are thousands, if not hundreds and thousands of work processes. For us to adopt AI in any task means, you know, you have to change huge amount of attendant work processes, even if this layer sits on top. And having said that, okay, is there something else which is better out there?

Is there something which will disrupt this further and so on? Should we wait for something to be adopted by and large to see, sorry, to see what the efficacy of that is and see what the, you know, see once it’s sort of established before adopting it. To me, look, having the first mover advantage in this is not going to do anything. But getting it right is. I think because we can’t afford to get it wrong. These are human lives, these are people. So I think there’s a huge amount of learning within the organization which is happening and I meet you know phenomenal people people across the board, okay, for various aspects. I think since the morning of today, if I look at my sort of schedule, 30 % of my meetings would be people, you know, from a technology background, pitching various sort of applications where our lives can be improved and outcomes can be improved and efficiency can be improved and so on and so forth.

But, you know, at the very least, you have to be very, very circumspect about what you’re going to adopt and what you’re going to roll out.

No, and I think you touched a very important point that we learned at Eka. We were earlier did a travel startup, me and Deepak. What we realized that in health, there is obviously innovation that people are looking for, but trust is the most important thing. I can bring a cool idea or there could be a cool way of doing a diagnosis at a clinic, but I as a person would trust only the doctor that I have spoken to or I have spoken to. been talked about. So there is this and that’s the reality that we learned when we started doing health that yes, innovation is definitely important, but trust is key. And I think Max has been trusted over the years.

And to be very honest, we also don’t know how to balance that out. The trust that has been created for institutions, for doctors, and now these technologies that are coming in, where it asks questions to the patients and gives relevant next suggestions. This trust factor is kind of getting a little sort of changed. Any views that you have, especially when it comes to patients, people trusting doctors to AI to institutes, any change that you see, and even doctors looking for AI solution and whether they feel that this is right now not as good?

So, you know, I’ll give you one example. At most hospitals, at least once every couple of months, you will have a patient who will come in, okay, with a pain in the chest. You do the ECG, and the ECG to the doctor seems sort of normal. He speaks to the cardiologist, okay, and the cardiologist says, okay, I don’t see anything wrong with it. And the patient is sent home, and he has a heart attack, right? Because ECGs, although they’re extremely, extremely common, okay, can be very, very nuanced. So, an expert cardiologist, okay, may be able to catch a particular movement there, okay, while somebody else may not. But even the expert cardiologist on a good day may be able to catch a particular movement.

able to catch it on a bad day not right now I’m not saying AI in its sort of this thing is complete but when a patient comes to ER okay I think it’s absolutely necessary to use that tool okay because that tool says requires admission okay whether the patient doctor sees it on admit him okay look by the end of the day you may admit 150 instead of 100 actual patients but don’t let that one go I think that’s the important thing you’re able to if you’re able to use this as assistive tool to augment your capabilities okay and I think that is what is emerging today you know I think it’s little too far out to say whether it will replace the clinician or not okay but I think right now clearly that is a very very essential tool that you can use and let’s start with safety before we go to efficiency or anything else you know so I think a very simple example like this okay and it depends it starts with leadership moves to institutional sort of habits okay to be able to adopt something like that change your work processes because the umpteen amount of work processes which have to change okay doctor when a patient comes where do you move when this sort of ecg report you move him to the cath lab okay and which is a 13 minute sort of this thing but that’s also preparatory time right you’re doing it within the golden hours you sort of move him into uh you know the icu how do you sort of interact with the doctor you have to call the doctor let’s say it happens at three o ‘clock at night okay the doctor the cardiologist has to come from his home and so on and so forth so the entire dance starts right okay but you have to make sure that you know you you can use this tool to err on the side of caution but i think at the very least that’s what you need to

and i think you touched upon um like these this complex healthcare process and uh when we look at it from a technology perspective this is what ai can solve for these extremely complex process that today there’s a multiple human touch point very simple such as doing an emergency call to a specific doctor with giving all the respective which today can be optimized, which can save lives. So that’s the sort of things that we keep discussing about during our board meetings and discussions. But a lot of these, and maybe health and non -health as well, what’s your view how the next five years, next six years, yesterday there was this conversation with Sam where AGI will be there by 2028.

What is your view on how next three years to five years? Now we can’t even say a decade, right? It seems like we don’t know what all will happen in a decade. But how do you see next three to five years changing in your hospitals or in general health care?

I think dramatically. Adoption of, and it’s not because hospitals or health care providers desire it, I think it’s becoming… absolute necessity for the country. One of the things, and perhaps one of the major things that propels our country forward is the demographic dividend. You know, the average age is 29, 28, 29, whatever. But make no mistake, 15 years down the line, it will be very, very close to the European age. And that’s the time people will require medical intervention. There just isn’t enough infrastructure and doctors available in the country. Okay, barely, barely sort of, it’s actually not even enough for the population today. I can certainly tell you 15 years down the line, there isn’t enough infrastructure which can possibly be built.

There isn’t enough money over here. Or, I mean, we’re just behind the curve a little too much, right? And if we have to solve this equation as far as healthcare is concerned, you know, you have no choice. But you have to, it has to be about predictive health. It has to be about, you know, sort of, before even patient comes to the hospital, falls sick, to be able to predict that he’s going to fall sick. and make amends there. Reaching out to people, unclog the hospital infrastructure, home care and so on and so forth. Okay, be able to replicate capabilities, skill sets of doctors to be able to take them to patients and so on.

I think all of that is a necessity. Without that, we will fail the future generation. So there’s no question of us. I think, you know, this is here. I mean, the future is here today.

And especially the whole vision of making India a developed country, we have to leapfrog. And many of these technologies can help us in leapfrogging the way you were explaining. But thank you so very much, Abhay, for your deep insights. I think we all love Max and the kind of work that you are doing. And we see more and more AI coming together at Max to solve for doctors, patients, and all of us. Thank you very much.

That is entirely mine. Thank you. Thank you so much. Thank you. Thank you.

as Director IT at the National Health Authority where he leads the technical architecture and implementation of flagship national initiatives including the Ayushman Bharat Digital Machine and Ayushman Bharat PMG. We welcome you sir. We have with us Ms. Padmini Vishwanath, Researcher at the WHO SEARO, Southeast Asian Regional Office, bringing a regional lens to health equity, digital health policy and evidence -based transformation in low and middle income countries. We welcome you Ms. Padmini. And last but not the least, we have Mr. Jigarth Halani, Director, Enterprise Solutions Architecture and Engineering at NVIDIA South Asia, a 20 -year technology veteran driving innovation in supercomputing, big data and AI infrastructure and a trusted advisor to government and industry on AI strategy.

I now hand over to Duy. Deepak to lead the panel discussion. I think we are short of space, so I’ll manage to standing high.

Thank you very much. It was a great session, Vikalp and Abhay just left. We have a short of time, so I will try to leave maybe 5 -10 minutes at the end for everyone to have questions. I would like to start this session with Dr. Gupta. Dr. Gupta, we were talking last night. You were instrumental in defining the whole first white paper around ABDM, how did it all started. There is obviously a lot of progress from when you conceptualized way back in 2019 -2020 to today. What do you really think has really worked towards seeing the reality and what are the challenges? How do you see going forward? How do this whole documentation moving from? Between patient and interoperability will start impacting the clinical decision making for the physician.

going forward.

Thank you Deepak and thank you Vikal for this wonderful session and giving me the opportunity. So it started actually in 2014. It was in BJP’s manifesto where I wrote and then in National Health Policy in 2016 and eventually when I was advisor to Health Minister. So you know, firstly we should compliment the ABDM team. There is no precedent. There is no precedent to create records for a billion population. How do you go about doing it? But I think people like Vikal and you every time you know you take a bold step, there are nurses who will say Bijli nahi aati, aap kese karoge. Today we have 860 million ABHA IDs. So I think if I look at the reality today and I know I am sitting on the right of the Director IT.

We have created the digital infrastructure. Now we have to leverage that to empower the people who are going to use it. I see a future where we will not have people using multiple schemes. That was our biggest problem internally. I can tell you why this got you know created and there are more reasons to but eventually technology will allow us to optimally use resources to clinically be precise in treating people remove redundancies and also my boss who is still the unit health minister we agreed fundamentally it will be tough to send doctors to relay they study for 12 years to make their life better not to go of course we want them it will take time to have that infrastructure where they can stay in rural areas but we believe that digital health digital solutions will be able to leverage this backbone that we have created to serve people in the areas where they need them the most I think that golden hour to platinum minutes to I think finally what I believe will be the digital health standards that in a minute you could get to what you need at least for primary care so I am very optimistic and we call was right the decade is not we used to talk decade at 2013 -14 now we talk three years max few months is better to talk So I think it’s a time where we should be really optimistic of the vision that we were able to build thanks to people like who had implemented.

You know, we had COVID at our hand, you know, when we looked at 2 .2 billion people, you know, getting vaccinated, not calling up people, just going to the app and getting it done. So I think the creators are in the room. The implementers are in the room. So ideators don’t need to worry much. Thank you.

Thank you very much. That’s very nice. So moving to your left, Nikhil. Nikhil, you guys have done a phenomenal job in, you know, deploying adoption of ABDM in public sector today. But we see a lack in the private sector, definitely. What have you been learning? How do you think this whole learning from ABDM deploying at a large scale PSU where obviously there is obviously massive, massive load of patients walking in and very limited physician and staff to support. Digitizing appointment has done a great way. do you see it going forward moving into private sector how do you see it going forward getting into the workflows even deeper which will really help better outcomes

which can be developed by IKAK and other health startups. Where ABDM created the federated architecture, where the model can go there and they can be tried. Because the simple making algorithm doesn’t make a solution in the health sector. Just now as the max safety is very much important. So what is missing in the foreign models, which is not tried in the Indian data, especially we can’t neglect the population, the rural population, small hospitals where most of the people go there. Where ABDM created HMI solutions, where we have access to the longitude records of the patients, where our Indian models can be tried, and where we can get the success actually. The ground is fertile enough right now to pitch in for the Indian startups to come in and try.

in your models especially because of federal drugs you don’t need LLMs you just need SLMs and some random models to come and do it so that the model cannot be biased because the biasness I can’t see only from the technical angle here you have to keep both clinicians and technologies so that the context data is available from across the India and across the population where the subject is the billion clinical realities and where and the AI model should be not only transactional they should be conversational where the literacy rate is very low so now is a fertile ground for the Indian startups to come in and show the brand value of the Indian startups so where I can see it.

Thank you.

Thank you very much Nikhil insightful you touched upon cloud infrastructure and we have Jigar here. So Jigar cloud infrastructure has made AI scale. We all are using, everyone is using chat GPT today. Infrastructure, sovereignty and trust are hot things. We’ve been hearing about these words for last five days like I don’t know n number of times. It becomes super, super relevant for health as we heard in the last session, the trust. How do you think the models or the companies building in India bring that trust factor so that physicians and the operator like Abhay would trust the solutions and then start implementing which will really help, you know, people like Nikhil in building those models for the country.

So I think it’s a deep question. Trust has many aspects if you ask me honestly, right. Trust in my language could be the most accurate results and I’m happy because I’m a fast moving guy, IT professional, right. So we are known for it. The event gets over today and Monday we are going to do it. We are back to work and we know we are going to hog again for next five days to make sure that we are something better and bigger right trust for my mom could be a very different storyline right because for her everything on priority line is health nothing else essentially right for me plus or minus 1 % 3 % 5 % 10 % is also okay for her nothing is right and trust for a mother who has just a newborn in her hand it’s gonna be completely different right so it I personally feel it has many years but a fundamental layer if you ask me honestly model builders what they’re trying to do is trying to still accumulate the knowledge which is still available on the web right what we haven’t gone back and that’s where I would borrow if India is achieving these numbers which I was not aware I knew about pretty well I have it from myself as well although I have not used it yet but a but I am a registered user I won’t myself get enrolled into everything but I am a registered user I won’t myself get enrolled into everything scheme that government is coming of it just to make sure that to understand where all connectivities possible essentially right but I’m not even a willing one yeah but but but I’m saying that once we have this data how do we make use of this data better so that I bring not just the context of India which is so important and what a couple is trying to do just on the language side of the story which we all understand that language is so important to us but imagine the you know the the the the environmental changes that I have from you know place to place and basis which the changes that I have in my body structure and basis which what medicine helps me better and so on and so forth right it has its own subsequent you know chain of things that that is it how do I bring that data more into the ecosystem thereby I make those model more and more efficient better and in the lingo of what India understand not just in language but also in the lingo of health which is important acting that particular like for example I come from Gujarat but I stay in back Bangalore, I know for sure that environment is not suitable to me, right?

And I keep sneezing for the poll reason, of course, many of the moment I go back to Gujarat, I’m absolutely normal, right? Whether it is extreme cold, whether it is extreme hot, it’s raining, doesn’t matter at all. I never sneeze. I think things work in Gujarat. I go, I come daily, I don’t get sneezing at all. I’m just another example, right? So how do I bring that data more into the ecosystem, number one? And then number two, how do I train those models more efficiently and serve them back to the users? So that’s one aspect of it, right? The second aspect of it is I think unlike language, in the healthcare, we need a very large momentum of citizens to participate and help us to have a lot of feedback ecosystem in what they are pursuing from these models which they are inferring it.

Right? Thank you. like, for example, in your solution, which I’ve seen the demo because now it’s been a number of times in the demo booth I’ve seen this. If a patient is talking, right, and, you know, going through your recordings, let’s say, which he or she has just done, for him or her, it’s the most important thing. For the doctor, it’s like the next patient, right? How do I go to the next? But the patient will definitely go back and check the recording. Patient will definitely go back, as we all do, and for the rightful reasons. We check the second opinion with the doctor, right? But that information is only with me. What did the second doctor told me, right?

I check with you as a doctor, and then I say, all right, it’s a big operation. I should take a second opinion. And I go to her. I take another opinion, and then both they say the same thing. And I then still Google, right, and I take the opinion there. And I say, you know what? Looks to be that I need to get operated. But we’ll wait. And then five days. It’s free consulting. Four days later. will come to the doctor. There are four questions. So I think the user also need to put the feedback back in the ecosystem by using these models and then getting democratized. I think that’s how the trust layer is growing.

This is at a very high level. Policy level, things are going to be very, very different and I’m sure it’s a topic by itself. Some other day we’ll work on it and I’m

Thank you very much. This Google doctor has been very, very popular in clinics. When we meet a doctor, they hate it. I have seen a board many, many times outside the physician’s cabin. No Google doctor, please. Okay. So we discussed, so next question to tell me, we’ve been talking about private hospital infrastructure. There’s a mass of high quality infrastructure available in the country with really great physicians. On the other side, we have PSC, massive pressure, less number of physicians. How do you think, you know, builders, when they think of building solutions for both of these perspectives? Should they think of a single solution? So I think the answer is yes. So I think the answer is yes.

So I think the answer is yes. What do you think of two different solutions? What do you think how it’s going forward?

Yeah, so at PeoplePlus, which is an initiative of Aikstep, we do a lot of analysis on what are the adoption trends and for high need populations. So basically for people who are building in healthcare, education, agriculture, right? What’s the uptake? Who’s building what? Who’s not taking third -party solutions and trying to build internally? And there are a couple of points that have emerged in that thesis. I think the first is because AI is meant to be personalized and context -specific. It can deal with multilinguality and voice. There’s firstly a lot of opportunity to bridge some of these inequity gaps that exist. So the first thing is that today you can imagine as a builder solutions that are in some very, very regional, low -resource languages for the different beneficiaries.

And you can design them to be voice first, which in a way is inducing trust because now they are speaking to someone and they’re just not reading or… an answer and they don’t know who’s behind that solution. So the first aspect is that AI is meant to be personalized. So when you’re building solutions or, you know, I’m going to go a step further. I’m going to say it’s beyond a solution. It’s a transformation. You can create very customized transformations. That’s number one. I think the second thing over here is that when, you know, because it’s a very fragmented value chain, right? In the case of healthcare, like someone is paying, someone is using the technology, someone’s ultimately benefiting from it.

What we’ve realized is when you’re designing these transformations, a big part of a builder’s journey is not just making the tech stack, but spending time with people who will be adopting it, educating them at different levels to explain how this tech could get consumed or improve their life, right? So many times, and I mean, there are 700 plus healthcare startups in India who are doing all kinds of pilots and demos right now. And what we’ve realized… is that the demo phase goes really well. Like three months, six months. Because there is adopters who could be hospitals or other institutions sometimes play from a place of either fear or hype. Like I want to be aware of what’s going on and I’ll do the demo.

But after three months, this is just going to be a side window on my browser which I never go back to because it was never thought of as a solution that I would embed into my workflow. So you have to think from the start of this as a journey and not just a one -time switch. That I get that one -time contract or that one -time demo and imagine that that will convert into some kind of impact. Now to build that trust, it’s very different in a private hospital which is maybe much more urban, much more aware of what’s going on versus a PHC, right? And the people in the PHC. So I think a tech stack and the solution is one piece of it.

But when you’re designing the transformation which comes with education, awareness, trust -building activities, creating safety and maybe feedback and evals that may be a little bit more make sense for a PHC versus a hospital which might be very different. So when you’re thinking of the… Transformation stack, it has to be very different. And transformation is about much more than tech. And I think that’s where people should be spending a lot more time as builders. It’s just not about cracking that first pilot or that first deployment, but saying what will it take to go from pilot to population scale, right? What will that take? Because that is a very different journey. That’s a systems journey. That’s not a tech journey always.

No, that’s super helpful. Continuing the same discussion, Dr. Gupta, when you look at policymaking, do you look at these two segments very differently or you think when you look at policy like private sector, PSC, you think health is one single sector or do you start defining, saying, okay, how will it work in public, how will it work in private sectors?

So if you look at the national health policy, this is the first time where I actually wrote the line both for private and public sector. In 2002, it was mostly written and even implied that it was only meant for public sector. I think if you really want to deliver care, you have to break that. barrier between private and public that’s how you will deliver care when patients has a problem it doesn’t see whether is the private or public should I get it the first hospital they get it so I think that was the thinking behind it and that’s what the policy is like

oh that’s great learn something I move on to Padmini from your regional vantage point how should AI system be designed differently to reflect the diversity of context capabilities and care relative across countries

yeah thank you first of all thank you so much for having us today WH was very glad to be representing the work that we do and you know listening to my co -panelists it’s interesting to hear about you know the the importance of tailoring because interesting and a little how do I say anxiety in using for me because the you know the work that we do is on the other end of the spectrum which is how do we create norms right how do we create norms and normative guidance to ensure that AI is equitable and moving in the right direction. And so I’ll talk from the regional perspective. And, you know, of course, we work with eight countries across CRO, and all of these countries and systems are at very, very varying levels of digital maturity, right?

But what we often find is the AI tools are developed for the most advanced, most connected tertiary institutions. And then adapted later for the most more remote settings, right? But we are finding that some of the countries, you know, pilots are looking at reversing this logic, which means that we start developing readiness frameworks for the most remote settings, understanding the frontline capabilities, device availabilities, all the factors that matter in AI readiness. You know, developing a framework, a framework for that level of remoteness. and then scaling it. And we do see that in contexts where we do that, there is higher provider trust, there is more equity. So I think that is, from our experience, we feel that maybe we need to slow down a little bit and look at how we can modernize existing legacy systems rather than kind of building on and adding new systems.

Yeah, I’ll stop there for now.

Please, Annie. So maybe starting from here.

I’ll go first. I think voice. It’s a common factor. I think it is horizontal, not vertical, but it’s very, very important for the country, right? If I understand what Tamil doctor is speaking with the patient and convert it into Hindi and have that deployed in Delhi and Gujarat, I think I’m home essentially, right? I’m solving many problems for years together that has been prolonging in the country essentially. I think it’s by itself is a reward to the country and we should be fully liberating it. One thing that I’m very happy about is the mindset change. You know, that’s going to be the biggest thing. It’s not a technology problem. It’s a mindset problem. And that’s what I’ve seen every single person, you know, talking to, they started more believing in the fact that, you know, the time has arrived.

I will tell two things. One thing is product. So I am very happy that a lot of discussion is going on about AI. So for any technology, anything to encourage the public, the thought process is very much important. That impact submitted created that impact to discuss things on AI basically. Now everyone will discuss on AI, like you beat a very rickshaw puller to the CEO, that discussion is happening. That is very much important to build systems, that thought process. Second thing, I visited few of the special start -ups. So very happy to see some start -ups are doing really great, like Eka scribe. So where the TVDM can use basically small clinics to reduce the burden of the clinicians from the non -clinical worker work.

So and there is one company and they are doing very great work on data anonymization. Because for many people, they have models to train after the advent of the technology. DPDP act so the data privacy and patient consent is very much important so they are working very really good in India so I’m very happy to such companies are there and they’re doing really wonderful so I’m very fed

I think for me it would be the emphasis on AI ready data systems because this is across sectors everyone is realizing that AI is only as good as the data for the model and application layer that it has access to and I really want to give you guys credit for that because you are pioneers in terms of putting out data and making it available to that MCP server that came out in fact we cite that as an example we are working very closely with Mosby right now and they want to make their statistical data sets available to the world they have put out their first MCP about a week ago but just the fact that you are you know institutions are just not extractive when it comes to data but they want to give it back so that others can build on top of it is very important so in health it’s crucial that happens because otherwise there is no personalization happening.

So I would say I think so far we have looked at a lot of quantitative measures of adopting AI in health, diagnosis, accuracy, number of patient visits, et cetera. But I think this time around we are seeing more discussions around the qualitative dimensions, right, empathy, dignity, care. And, you know, it’s interesting because in one of the pilots we are conducting on palliative care, we, you know, we didn’t even think about it, but a caregiver and a patient, palliative care patient visiting a nurse, you know, that’s their only source of human connection during that week. And so how does AI kind of change that dynamic of caregiving, right, in those little moments they spend together in the clinic?

So I think. The increased conversation around this. and just acknowledgement of not just the quantitative but also the qualitative dimensions is something that I’m personally really looking forward to.

Thank you. The objective of this question was not to get the promotion for Eka, just a disclaimer. I will… No, but thank you. This was super insightful. Audience, any question?

Sir, I just had a question. You said a voice language is not as new. So that mostly 90 % of them are on the cloud. So that needs to be on the edge only or on the cloud or hybrid?

No, no, of course. I think… Do you use ChatGPT? Yes. One of the servers I hosted over in India. No, I’m just saying there’s cost factor is also there and they have data privacy also there, so… The moment you add cost, as long as it is in India, I think we are home. I don’t think so we could be… Ever cheaper.

So I was just… I’m asking a suggestion from you, so like what model should, like someone who’s creating such solution for voice and translation, multilingual, let’s just target 22 languages. So where should the MCV or the influencer or the activity server should be hosted? On the edge, on a gadget, like a mobile phone or something, audio recorder, or, you know, hybrid?

I would say, I would say it depends on the use case. If you have a very particular use case, very tiny one in a remote place, edge would be the solution. You don’t have a choice. You will lack behind the connectivity and few other aspects as well.

It will synchronize once a month or once a week or once a day?

No, voice is something you need to have connectivity in play.

Okay.

You can’t be having offline things. That’s my view at least. People are trying. I think Saboom had something on, on the device. 90 % we should go for.

Connecting with the cloud or the server?

Yes.

Even if it’s a local India hosted server?

That’s correct.

Hello everyone, we have seen a lot of stalls in the expo showing AI powered documentation and diagnosis. I am a dentist and I am currently pursuing MBA in analytics. So I am curious how far this AI, Indian based AI tools are relying on Indian data rather than global data sets.

Depends on what they are claiming that’s first. And the other side I also represent the Mayo Clinic strategy in India. So as Mayo Clinic platform we are opening in partnership with some of our data sets to look at but also collaborating with hospitals inside to leverage each other’s anonymized data sets. So I think important. Thank you. point to note is the culture of data is missing. I mean, we still have to get the culture of data to get to have those AI systems that are based on Indian population. I think this is still far away. I think with ABDM sitting next to we have 860 million of IDs, but if the number of records on ABDM, if you check, they are not what we want to be.

So I think we’re still not there in terms of if someone makes a claim, be careful. Thank you.

That’s great. We talked about what we really like, what we’ve seen the change fundamentally. But do you guys also think there are still few items we’re lacking behind as a country, as a health, where we should have been already seen? Or you think we are on the right path? And if we are on the right path, then what do you think would be the great outcomes in next year?

My answer is very frankly, even at the cost of obesity. See, the issue is not about the usefulness of technology or the use case. It’s about ethics and doing the right things. Most of the people are not using, not because the UX, UI, technology, outcomes, everyone knows that. How many doctors would actually want to tell what they charge for a prescription, how many prescriptions they may, and why they write three antibiotics for one case. So I think it is about regulating that unethical part, the way they were able to crack it, you’ll be seeing the mass adoption. The challenge lies in the medical practices and medical ethics, not on the solutions per se. Otherwise, we would be the most adopted nation in terms of digital technologies.

The great, last night, we were having this conversation where in China, I was surprised to hear this, that in the real time, when a physician, is writing a prescription there’s a data going back and if there are errors it’s coming back and the doctors are getting flagged if they continuously do this thing and then that’s the way one way of controlling what you really said and you know think of us we are still in metros literate but think of people in tier two tier three having three antibiotics at the same time i have seen in bombay a chemist saying as you throw my religion yeah we pop up so i think it’s an issue about practice medical practices good good pharmacy practices good prescription practices to follow i mean you could have given a cold and a cup syrup that would have made him money too

i want to give as if you had a point just want to add and she asked one question how many models are training on indian data so you said now that where we are lagging behind so we want to say like the behavioral change is very much important so we have solutions even And we gave very, with CDAC, we gave one e -shift flight, which is almost free to small hospitals. And all the government hospitals, including Ames, having the HMI solution where they can create the language records. But some of the docs are not ready to do, because they said that we are very much accustomed to writing on the paper only. So still they are doing, and we are accepting.

So where we are losing the context data from the major public hospitals. So where we need some tough stance, because I am now working in National Tadati, but before I was in Railways. Now Railways totally stopped physical prescription. Because they took a decision that no more physical prescription. They are doing only now online prescription, everything, even lab record, everything integrated. So they took one decision. They retested. So we need some tough decisions, and also we need some behavioral change, where we have to go for creating language records. then only we can give some context data to the Indian startups where our models can be deployed and trained then we can get rid of it.

Thank you very much you have been a great panel thank you very much for all your insight and I am sorry in the interest of time we will have to wrap up but before we close this session a sincere gratitude and thank you to all our panelists I request Deepak to just present a moment to from our behalf thank you Thank you. Thank you.