World of AI-Startups

Hi, good evening, everyone. warm welcome to all of you very nice that we're all connecting on a weekday, middle of the week, are trying to understand something very, very important for us, which is the world of AI startups. Let me take a couple of minutes to quickly introduce, you know, who we are. And our speaker for course for the day uncial is here. And I will then hand it over to uncial to take it forward. So very briefly, we are at talentsprint, National Stock Exchange group company. And we are a deep tech scaling company offering different different programs and all the leading deep technologies like AI and machine learning, cybersecurity, blockchain IoT, the list goes on. And all these programs we offer in partnership with all the top academic institutions of the country, like IIT, Hyderabad, IIT, Madras, IIT, Kanpur, iisc, Bangalore, iron, Calcutta, or even we also partnership partner with top global corporations like Google pega, systems, automation anywhere blue prism, VMware. So, it's a long list that we have. And, you know, we all have different sort of skilling programs that people can get into these sorts of really, really exciting technologies and career paths. So, as part of our initiatives of promoting awareness on these technologies, we have these webinars, and today is one such kind of a webinar. And the topic is very, very interesting. It's the world of AI startups, to different themes put together, right AI, as streaming itself is a very, very exciting and curious domain for a lot of us. And then the world of startups itself is another separate thing in itself. And what did what does it take to be an entrepreneur and that journey of starting your own company, that tuner technology company in the most new technology, I think it's, it's really fascinating to be in that space. And in that context, we have a very special guest uncial Hi, unshelled. He Hi. Hi, Rita. Yeah, so uncial is an IIT Kanpur alumni, and he's a young entrepreneur, as you can see from the image also. So he is here with us to share his journey and talk about a little bit about himself, if I may ask you, and, and also share his experience of this entrepreneurship, the company that he has co founded, which is hi short, is leveraging a lot of deep technologies. And he can throw some light on that as well. And, of course, he can take us through more to know what sort of opportunities young professionals can also explore in these domains. So until that's all from my end, I think I'd like to request you to talk take some time and introduce yourself a little more, and then I can take take us through your presentation.

Sure. So I'm audible raise it right. My voice. Yeah. Okay. All right. So Hello, everyone, I hope that you guys are doing well, in these testing times. Obviously, this has been a very tough journey for most of us, last one, one and a half years, but I'm sure you must have been doing well, in some ways, getting better every day, in terms of upscaling or whatever, whatever new things that you might be learning. So I'm sure that you must be doing that. So I just give you a brief introduction about myself. So I'm a 2015, graduate from IIT, Kanpur, I did my B tech, and I am a civil engineer. Like if you look at my academics, but although I haven't pursued anything in that domain. So my my core interest was more towards the technologies that I can probably learn, I have a lot of interest in web development, I have a lot of interest in whatever new is coming our way. So I like I would say, I have pretty much self learn myself into AI. And and that has been something that has helped me, you know, start my own company as well. So this is my second venture. I think I was lucky enough to, you know, start something at this young age and that to do it twice. And I would love to share my experience over the course of discussion that we'll have right now. And yeah, so that is it about front myself. And what would love to take any questions throughout the discussion that is happening? I'll try to address the question as much as possible during the discussion or towards the end of the discussion. I'll try to you know, take take everything that has been coming from your site, because I have just prepared a small deck so that I don't you know, fall out of line when we are having a discussion so I stay in that zone. So I'll just start with that. So I hope my screen is visible to everyone of you. There we can see. Great. So I mean to start with I mean I think you can you can see this catching heading which is the world Va startup, I would rather break it down into two parts, which is, you know more about talking a little bit about AI, and then talking about startups and what actually, ai startups are required to do and how people perceive in the industry, what kind of requirements that they do have. So that is what I'll try to cover over here. So, I mean, this is one of the poor by, I would say, one of the visionary of our time, stating that AI is likely to be the best or the worst thing to happen to humanity. And I think this is a very extreme statement by Steven Leight, Stephen Hawking. And I, to an extent I disagree with with this point, not not entirely, but to an extent, I mean, I feel that this is slightly scary. I'm not sure if I entirely agree, but certainly such kind of statements are good. For for one reason for us as well, because it, you know, generates a lot of interest among people, if you release this kind of thing. You feel the Okay, yeah, okay, is something which is, which is, I don't know what it is like, how can I get something can have this kind of definition, which is like, it is either the best or the worst thing to happen to humanity. So, that is, to an extent, that adds a lot of value and weight behind, I mean, coming from such kind of visionary that these kinds of statements add a lot of value, I am more, you know, familiar with this kind of idea. This is a statement by VPN chief AI scientist in Facebook, that our intelligence is what makes us human, and AI is an extension of that quality. So this is something which I feel which which, you know, tells us that, okay, AI is not something which is, you know, just going to happen tomorrow, that everyone will start using it, and there's something that is going to happen all of us, I think it will be more of a gradual and it is happening, I think I think we are in that process. And there will be a gradual growth, gradual increment in, you know, our capabilities that how we are going to solve problems through AI. So that is what my, you know, perspective to an extent is, so I just wanted to, you know, make it cover, we'll start with these two ports and make it a little bit everyone take everyone's attention on the on these points. So, I think I think most of us have major AI references through different different movies, I think we would have certainly seen many of the movies where we see Oh, there's there's a AI which wants to, you know, take over the entire world or do whatsoever, maybe the end of humankind, and other stuff. I think I think that is a major theme of most of these movies. And I think that is that is most probably at least people of our generation and and slightly beyond have that as a first reference of AI coming from these kinds of movies, they would they would realize, Oh, yeah, this is also something that exists. So just to just to, you know, take everyone's interest in that I would want to just have a small poll. You know, taking that word, according to everyone is

the favorite AI movie among the following. So I would just request everyone to just answer on this. I just gave him in it. And meanwhile, if someone has a quick question on top of it, they can they can definitely add on. I don't think till now we have covered much to have questions around that.

As a host, I don't have the option to submit to you too.

I have allowed the panelists panelists as well.

That's it. I can see the poll, but I don't have an option to summarize it. But I can say I think what's what's your choice in this? I think I'm on Jarvis. Like I would love to have that personal assistance. Yeah. Definitely love to

audit, I think I think we have a winner over here. And I see that. Roughly, I think Jarvis to an extent is leading and I think we have a lot of Avengers fans. So now now I think Avengers Age of Ultron. And Jarvis is competing side by side. So we are roughly around 70% of people voted.

I just feel a little old. I'm doubtful whether people have seen Terminator or not.

I think I think we are good to go. I think we have a winner. With the Age of Ultron, which is Avengers, so

we can share the polling to the viewers. So you can just end it and share it so they can also see who is it. Okay. So, yeah, so now viewers can see.

Yeah, roughly, I think I think a Avengers in total would have got roughly around 90% of the votes. If I were to say, Well, yeah, that's great. Okay, so let's, let's get back to the discussion over here. And so, yeah, so, this is a question. So, my personal favorite over here, which, which unfortunately came second is, you know, Jarvis obviously, the reason behind this is because there is a slightly sad part with all those movies, waiting, I mean, most of the movies, not every, every movies, in the, for that matter, that mostly the AI is, is somewhat a villain to an extent. And obviously, in some of the cases, they it would have turned their way around as well. But that is how we have perceived and that is how we have looked at things. And so that's why I have a very sweet spot for Jarvis having a personal assistant and more of a as something which is useful in my day to day life and I can, you know, have that that thing that comfort with with that AI so that's why I'm I feel more affectionate with with Jarvis. And of course, I am a huge fan of Iron Man. So that's my personal favorite in this. But yeah, that's the reason. So, there is a very simple and basic opinion behind it, you know, when to use AI and like why why we are implementing AI in into any kind of software solution obviously, there are like things like automation, we can do automation, then I believe there are many problems which humans can solve, which obviously AI can't. So, my thought process with this is when you don't have a solution, which is not fitting for you when you when you when you're looking for a solution which is not fitting for everyone like you can't satisfy all your customer with a with a standard solution there are like in finite you know, type of solution that someone is looking for more of a personalized or kind of a different So, when the problem doesn't have you know, one size fits all kind of solution or Blitz for that matter, multiple size fits all finite size fit all that is the point when I believe is something that we should think about AI there are not necessarily every time that that is a requirement, but yeah, this is something when we there should be an alarm in our mind, oh yeah, this problem should be solved with with this kind of approach with implementing AI over here. So, let me just take you brief like take you through a journey of how it has actually evolved and and what has been the past, I think the most interesting one has been i would i would say post my birthday itself like more from after after 99 days. So, that is something that has been more exciting, but yeah, like, I think the initiation just to you know, prove my point, which I mentioned in the last slide as well. So, it was started at in a workshop at Dartmouth College in 1956. And the reason behind coining this term of you know, artificial intelligence was to distinguish itself from cybernetics to distinguish itself from process automation. So, that is something that people wanted till that time people never even looked at AI as a separate thing than automation. And right now, you understand like, these are like poles apart these are these are entirely two different things, something which can be automated and something which can be solved by AI. So yeah, this this was a reason for, you know, having that term, obviously, in the concept at all. It existed even before that, but but the reason for this term being coined was because of this. Then moving further, there was some, some doubts on that there's people who are skeptical, so there's a phase that they call as AI winter, which is, which was a time when I would say specifically the US government reduced funding from their side. Then in 1980s, there was some sort of new supercomputer launched from Japan side. So that kind of, you know, a raise that interest from everyone to start doing something around that. Then again, came on tip from their side which which is called as AI winter. And then our After 1993 and and beyond, there have been a lot of, you know, interest around it. And the reason behind that has been, I would say a few PR stunts from from some of the companies. And obviously, if you actually use cases that has come forward, so the there's a very big event that that actually happened It Like It, it happened in

around I believe, 97, which was Grandmaster Castro, who was a, who was a reigning Grandmaster, I believe, at that point in time, he was challenged by an AI, I think it was an IBM VIP Bluetooth, and it was actually defeated. So that was a time when when people and see act till that time and and for centuries, chess was something which was considered as a barometer for intelligence, and any AI coming and defeating. And obviously, there are a lot of controversies as well around it, but it attracted a lot of attention. So that was something that, you know, initiated that thing, then again, there's a game which is famous in China, Japan, South Korea, game of Go. And that is, again, considered a game for intellectuals. Even in that there's a Google bot, which which kind of defeated the reigning champion. So these are the few events where, you know, people realize that, okay, there is something that is that is happening around it. So yeah, I mean, this is just a brief history of how the AI has, you know, evolved it. I think I see few hands over here. Let me try to address a few questions around that. If I may, let me repeat if you can help me with, with where exactly, I can take this thing?

Yeah, I can read the question that will be really helpful. So I think there are a couple of questions. One question started off the beginning itself. Demo saying Hussein, is a first year student? And what should you do now, so that by the time we graduate setting, up in the right place,

okay, so I think I think for now, you should start reading, you should start reading a lot of articles, you should start following some of the leaders who are doing some good work in the field, just just try reading their blogs, get that level of interest, I think that is very important. Before jumping onto something, I still feel that you are at a very, very early stage of your career to even decide that, hey, I'm going to pursue this thing. And it's it's definitely a great thing. But decision is more formed from your side, if you have, you know, taken all those kind of things that you have convinced yourself into that decision that is much better, instead of, you know, hearing from everyone Oh, wow, that's a great technology, I should definitely learn it, it has a great future. Instead of that, you should rather prepare yourself, you have a lot of time, fortunately, on your side. So you try reading out things, get to know, some of the leaders, what their views are, what how to blog on these kinds of things that will really be helpful for you to, you know, generate more interest, get to know new things around it. So yeah, that that should be the approach that I would say yes.

Yeah. So I think that was one question. A lot of other questions were about response to the favorite movie. Okay. So I think the resume considerable was missed.

So I'm really sorry for that. I apologize. But again, that's, I think that that's again, a good good one. So definitely, that as an investor.

Yeah. So and then I think there's one question I'm not, I don't fully understand what Shiva asked by Shiva asking me Has anyone heard about bicylist paradox? So I'm not sure if the question is addressed to somebody but maybe someone in the group will they can respond. Okay. Okay. So, balancing balancing has asked another question, saying he's retired from computer science specialization in artificial intelligence. And it's been two years and I haven't done anything and I'm serious now. But I want to do something productive.

Yeah. Yeah. I, so I totally understand where he's coming from. And I mean, he definitely has an edge over everyone. And still, it's like the technology in itself it as at a very earliest day, specifically, if you look at the Indian market, it is at a very early stage. So I would, I would, what I would suggest is that whatever organization he is part of, or like anyone as part of, they should and if they have, they can have some influence at you know, have a discussion with with some of their seniors with In the organization, a manager or someone, they can propose some solution which which, right now, they might not even understand, right? See, even if right now with our product, if, when I go and approach a client, most of the thing they don't even understand and my product is focused more on the HR side, I don't expect them to have that technical knowledge. And most of the companies might not even understand that aspect of it. So there are two ways of looking at it, you can definitely look out for some opportunities within the organization, or else you can just find out what are the organizations that are actually working on the stuff which which which might interest you more, but trust me, you have an edge over most of us that you already have an academy qualification, which resonates with your interests that you are you are wanting to follow?

I think there's one question which asks How about the scope of influence of AI in the coming future of technology?

So it as I mentioned, I think I think it will grow more gradually, there will be few fields, which see, for example, customer service, I think, that is something which is very well being adopted by chatbots. And and people are trying to build their own AI engine as well. I mean, some of the companies are, you know, selling as a solution for for other companies that they can use their AI boards. Some of those could be just a decision tree, but but at least few of the companies are doing a good job in that domain as well. So I think it will grow, it will grow from segment to segment within our within an organization itself. And it will, it will reach a point where like, you can't actually ignore it because other companies will have a job where you see, just take an example. If you look at what websites were like, like 20 years back, I don't think every company would have thought of having their own website, most of them would have that opinion that only the companies which are into e commerce domain should have a website. I'm not saying that it is equivalent. But to an extent, the I think the use can be very generic and can be utilized by many companies and in certain sector or segment of their operations. So I believe that it has it has a lot of scope. It might take time, especially in the Indian context. It might take some more time. But yeah, I think we are almost there like now is the time to have these kinds of skills and to learn more about it.

Yeah, so until I think we keep getting questions. We'll take one question now. And then you can continue with the presentation. And we can take more questions again, to show Sure. Yeah. So Nikhil Kumar has asked, right now, whatever resources I have just begun to go for the AI thing, but I found totally theory based stuff. And I'm more into coding and one my hands on experience with real time projects on AI, in please suggest some basic projects where more of the coding thing is required.

So obviously, there are a lot of theory stuff that that is over there. But But I think the actual learning would start if you are, you know, going for an actual solution and at a business level. And that would be the best thing like if you are in your college try for an intern with a with a company, which is actually doing some some kind of stuff, there is not yet set template for what exactly you are going to you know, do so. So that's the reason it requires to have see there are a lot of companies, if you are talking in the Indian context, there are a lot of companies in the medical field, there are a lot of companies in speech recognition field as well. So I think you can certainly explore and you can also explore for an opportunity where you can have an intern, if you are in your in your college, you can have an intern or something like that, that will you know, give you an understanding of what exactly a real world problem would look like.

So until I think a lot of questions are around, where do I start? available? And that's, that's what I'm able to sense from most of the questions coming in. Maybe you can cover it in the present. Yeah.

So towards the end, I'll try to cover some add some few points for there as well. Yeah. Thank you, john. So I just continue with the discussion and would love to spend more time on the question. So we'll try to take it slightly faster as well. So yeah. So I mean, this is the basic AI spectrum that, you know, look like there isn't. There's a term called industrial AI, which is more about doing something based on whatever business record Mendes coming up to you, then application AI is more about the problem that maybe you can recognize. And Korea is more about, you know, building a solution which is more generic and can be utilized by multiple industries, I would say it is it is somewhat academic to an extent. And obviously, if, let's say, let's say if someone has built a very scalable chatbot, which which, which does a lot of NLP, which which does a lot of things are at their end, and it can be utilized by by a company actuaries for a very specific problem, maybe they want to solve only their customer support kind of problems. So, it is more of a short term and long, long term over here. And that solution being generate a general or or a specific to the, to that particular property. So, I mean, these are the few common fields that I realized and and some good work has actually happened, like, I would say, is sensing and cognition, and I can see that these are few major fields in which some good work has happened, like when is medical field, I see a lot of startup nowadays coming up, and even some of the companies are opting into it. And there is an actual value add around those. So I was speaking Few days back with one of the co founders of a company called synapses calm. So what they do is they take the radiology reports and give the assessment on that report, within seconds, what usually would have taken at least two to three hours. So and it's, it's a very good help for radiologists. And currently the customers are radiologists only were using to you know make their processes more efficient. Then talking about analyzing text, I would say like most of us would have come across this. One very common example is in G mail, when you when you are typing a text it It also tells you what next should come and it's very adaptive, it's it's based on what you would have written in the past it did understand that aspect of it then facial recognition, I think everyone is looking at their phone to you know, unlock the phone. So, that is the most important aspect of it, then I also seen some of the, you know, companies like even in some of the automobile companies, they have implemented AI solutions to identify defects in within their process if there is if there is some failure as well. So, this has been a very, you know, I came across this very recently and I felt very interesting. So, this is also one feature that is there, then the speech recognition is obviously one thing that that has gained a lot of interest, then, of course chatbots that have, you know, mentioned that many, many companies are using. So one good metric that I realized when I was reading about chatbots, that companies in general who have implemented chatbot for their customer service have improved the customer satisfaction by more than 15% on an average. So that was a very interesting thing for me. And there have been some study, which which tells that people are usually, you know, like it better when there's speaking to a board for that matter, they are happy to share most of as well, which which might resolve their problem in a better manner. So yeah, that is one thing. And I think we see most of most of the companies having implemented or using some other services for the chatbot. So yeah, that is that is what it is for you.

Then talking about what do actually iced hunters need. So I think they have a lot of emphasis on data. And I think that's the most important part of it. You can't have an AI model with a good quality as well as quantity of data. So yeah, so that is believe is is the most important aspect of it. The other thing is there should be a use case. I mean, you can't just, you know, try to solve a problem, which might not even be a use case like that might not even be someone's problem. So there has to be a use case, or else it might look lucrative it might look cool, but if it is not solving someone's problem, day to day problem, that's not going to be you know a business I mean, it definitely you can have a good model developed over here. Then the next step is a PLC which is proof of concept. So I think the iteration and announcement of whatever you have developed is very, very important. So again, PLC is I think one of the very important aspects on the business side of it and I'm coming from the product background. So for me like proof of concept is something that I always look for I try to identify Whether it is going to actually, you know, satisfy whatever basic question that I made, whether it is actually going to satisfy, and the and the fourth important thing is talent, I think I totally understand that there is a lack of, you know, good opportunities, at least at this point in time that some of you might feel there are a lot of companies that are, you know, now trying to incorporate things. And the best part is, you know, this is something that no one has a head start on you. This is this is a field where even I did learn, probably three years back or maximum four years back. So, that's the maximum Head Start that anyone could have, obviously, there are a few champions who might have, you know, taken interest much before that, but that's the biggest yet start. So, I mean, we need, we really need a lot of sharp talents. And I think those talents are going to drive, you know, that feel within an organization as well, that we need to actually adapt something on that press me AI won't be limited to just a few technology companies who are just doing few stuff, the names like Google Amazon, I don't think that is going to happen in future, it will be more or less a need of everyone. So yeah, that's, that's what I feel, what AI startups to me, then moving on to next assessment of AI startups. So, these are the two major things that usually is considered for accessing an AI startup. So when is product development and when is customer development. So obviously, if you are having a data, and you know, coming up with some solution, using that data, it has to have some some meaning in that, I mean, you should have an understanding of the potential market, you should have an understanding of the pain points. So this is very much important. If there's a startup that is there, I mean, you can have some assumption in your mind that, okay, this is something that they are looking for, but but that might not necessarily be true. So that is very important. And on top of it, there's a customer development, which is very important. So the what I mean by customer development is like you have to go through that cycle, in which the customer is, you know, improving your engine and it is, the customer is providing that information. So that customer development in in the part of AI is AI startups is very, very important. And obviously, there are a lot of questions around, you know, data that how a company would get data and other stuff. And there are obviously ways around it. But if you are not even doing a proper customer development, that is something you will miss out on a lot of these kinds of data. So just to, you know, showcase you one of very interesting started that I actually came across, and it might be of interest for everyone. So I will I will just want you to watch this one and a half minute video, I'll just share sound as well so that you have good experience.

Second spectrum lies at the intersection of sports and data and technology. And right now, there's basically a one size fits all solution. But as we know, we don't all like the same thing.

It's becoming an on demand world. And that's a fundamental, almost inalienable right today that was non existence 20 years ago, let alone 50 years ago.

With the information age, big data has hit sports. The problem is the data itself is not valuable to people, it's the ability to to use data, to turn the content into things people care about what we're bringing it second spectrum is the ability to transform data into capabilities that can really change people's experiences. The good news is you can get very specific, and you can get target exactly what you want when you want it and where you want. That bridge is essentially a computer that understands the game because a computer that understands the game and understands you can give you what you want. And that to me is ultimate choice. It's going to be a big part of the scoring experience. We combine machine learning computer vision, design user experience to create a platform that is able to understand both sports and people and transform content into ways that people actually want to experience.

That's where I see companies like second spectrum play a role that they're going to continue to be that next growth area in making the experience richer and much more personal tomorrow than it is today.

Yeah, so I mean, this is this offer very great interest to me because I mean, I I'm a big follower of sports. And this was something which was very exciting. And most of the points that they are mentioning as a as a company, that makes a lot of sense for, you know, if you are looking for what actually a company should look for, and those points are very, very meaningful. So yeah, just moving on over here. So I'll just give you a brief about actually what we do. And like, again, again, we are trying to achieve and try to solve a problem, which doesn't have a one size fits all kind of solution. So what we are helping, I mean, customers are companies, so we are helping companies with with three different kinds of triggers and giving them a predictability. So we are we are allowing companies to roll out an offer, they can they can roll out an offer to our platform, it's more of a customized to what our candidate should see, then there's a FAQ interaction more of a chatbot kind of facility. Now, on top of it, there is a there is an engagement with the candidate that they can, you know, do some messaging and other stuff. And based on these kind of interaction, there is a predictability that comes to the company, that how likely this candidate is actually going to join your organization, or what changes probably you should make in your offer, how you should, you know, try to have this talent in your organization. So, yeah, that is what our current solution is, we are trying to, you know, incorporate a lot of things and just to answer at point towards the data. So, we started with almost zero data. And we started with few assumptions. And then we started collecting data. Like, whatever was available in the public domain, and we realize that Oh, yeah, whatever hypothesis that we are trying to make is somewhat correct. And then we proceeded ahead, building our own engine. So it's not necessary that you have to have, you know, the plethora of data from the start itself. You can, you know, do some minor tweaks and other, I'm sure that your solution will not be, you know, what you would want it to be, but yeah, it's a way towards that it's a it's a part to itself. So moving on, I think I think there's one another important topic, since we are talking on a lot of things, which is, which is responsibility, I just want to discuss two minutes on on this point, and then probably I'll, I'll jump on to some questions as long as we can take. So there's, there was a big discussion on face recognition bias specifically in us, I think that's a country which, where we have a lot of technology advancements that are going on. So that's the reason it came from there. So what what people realize was the face recognition system that they had built, was more accurate towards white men. And it's not at the thought of building such kind of, you know, partial system. Since most of the, you know, subjects on with whom they actually tested it, they were white men, and that is the bias, which was a kid represented in the, in the system that they made. So this was criticized to an extent. So as someone who might be working on on such kind of thing, you always have to look at your solution in future that it is not, you know, being biased or other stuff. Then there is another example of a tweet, which was, which was something by Microsoft, I think it was launched a few years back, it was just a board, a Twitter automate, but Twitter bot more or less, and it started from humans are super cool in in one of the initial tweets and it ended with Hitler was right, I hate the Jews. So, I mean, that has to be some element that you have to understand that I mean, you can't just let it loose right, you have to understand what what actually you are building. So, there has to be few responsible elements as well in whatever solution that you are building. So, I just wanted this to be covered from from my aspect as well, because even in our organization, we have failed, when we are when we are trying to build our stuff, we have failed and we have ensured that there are no biases by any kind of parties involved. So I always feel that this is something which is which is very important. So as everyone says that with no, I think

they say that with great power comes great responsibility. So you have to like if you are using a tool like AI you have to be responsible. So these are few you know, practices of responsibility I N thanks Many big organization are leading way to, you know, have this kind of thing implemented. So yeah, that's that's very, very important. If I am sure that once you once you are doing that hands on stuff, you should keep this in mind that whatever you're building is it doesn't have any, any is not following any of these things. So yeah, that is my my view on top of it. So, then moving further, I think I pretty much covered some point of it, that what I do feel is the future. So I believe that, again, it's, I'm not very sure that I am always writing my predictions. But I still believe that it will be something like a website for for the companies that you can't live without it. I mean, it will be mandatory for everyone to use it in some form or kind of other form, there will be some templates, there will be some services, which will, you know, enable a company to have that solution. And this is not very far, I think I believe that this is something that is going to be built in a very, very near future. So yeah, that is what my thought process on this is. And I would love to have questions on top of it. So yeah.

Thank you so much central for taking us through your entire presentation. Very beautiful. And I think you've emphasized one very, very important point that no one should be aware of when you're talking about AI startup or anything to do with this kind of very powerful technology. These are all dual purpose in nature. It can go either ways.

Yeah. Yeah, I think one thought that occurred to me when you were speaking is

one, as a young professional at this age, we don't really have enough exposure to the outside world. I think it's really, I'm not sure we know how much we can start thinking about implementing an AI technology for something, then then you're first trying to explore understanding how the technology works in itself. And I think as you go, and you as you see real world problems, business cases, or any social problems, or something that you find that connect, and then then you can start thinking how you can apply it in AI powered solution for it. So I think, I think that's really important that you start on the responsibility, a part that that's where people will start really thinking, Well, where is this going forward to?

And I, I feel that at least some of the corporates, and at least the bigger ones now have realized, obviously, there have been some pressure from different side, but but to an extent, they have like said a few things. Right on their part. And I would suggest that others do follow as well. So yeah. Okay, good. So I think we'll start taking some questions. The latest question I saw is from my Mecca Anamika, who was asking is if bias is a higher? Sorry, if bias is a high error? Is bias a high error?

Yeah, so I think it's, I think the context to what you talked about the aka.

So I think I don't actually recall the number, but there were like, difference in terms of I would say 15 to 20%, if you talk about the different communities, how this particular like face recognition, bias was, you know, doing it, so, like, what what it suggested what the data suggested was at face recognition was like, as high as 95 96% for white males and as low as 70% or lesser as well, for for black, black community people. So yeah, I mean, that is something which was, you know, noticed and is a huge thing like I, I am I would not want to devise a system which which doesn't have which, which does have such such level of biases. So yeah, it is for me, like it was a significant amount.

Thanks, actually. So I was just going back to the questions where we left off last time, and one of the questions that came that time was if automation is also part of AI.

So not, not necessarily, I mean, it is obviously confused with the iPad automation and certainly not to to answer that. Automation is something as is more about, you know, your solution. You don't have a solution right now. And your, your system will learn that thing and then probably come up with that level of solution. So you don't know for automation, you have like, fixed up like you, you know, yeah, if this doesn't happen, you have We could do this, if this isn't happening, we're going to do that. So with AI system, it has to be more of an iterative kind of thing. automation, obviously is a subset. And it can be done with AI, but like AI has like further scope much, much further support. So like, these are two different thing.

Essential. So the, like, we noticed, like the a lot of questions about where to get started, what type of courses? And because one question from when he wrote, The question is, he says, I'm trying to pursue my career in robotics, my specialization in engineering is electronics, I'm confused as to what I should start with AI, or IoT, or anything else.

So I really believe that, you know, reading a lot of blogs, leading a lot of articles, definitely helps you take this, this decision from your side. So that's what I have at times decided, you know, what, what exactly I have to do, and that has helped me a lot. I mean, if you if you start following someone who rides on these kind of stuff, and you start getting that level of interest, nowadays, there like a lot of YouTube channels as well, which are kind of promoting different different kinds of stuff, if you want to consume the information in that format. So I think the first step for everyone who are in doubt, is to, you know, go and read, go and know about these kind of stuff, try to understand what it actually is. So, most of us, we just we just jump on things, and later go on to realize that, Oh, this is something which is not of my interest. Like, I'm also guilty of the same thing I did my beat again, civil engineering, obviously, I was very naive at that, that particular age, I never researched that what exactly civil engineering would look like, whether it is something that will be of my interest. So I just opted for it, because I just wanted, I might have, you know, opted for something else, which might have been of more interest to me, I never researched it. So again, I think I think it's more about you know, going and understanding and convincing yourself, you will always only have one chance to, I mean, some people do change their field. But given a life, if you have like two options, right now, you can only do practical with one, right, you have to leave the other one aside. And the best thing is to convince yourself for that option, so that you also are bought into that thing, you are never in doubt why you are now pursuing it. So again, it's more of a career advice than anything specific to AI. But that's what my thought process on this and that will really have just tried to follow people who are into this field who are doing things, try to read about the companies, there are some very, very good companies that have actually come up. So try to read about them what exactly they are trying to do. If you are in college, try to get an intern with those companies. So that will that will really make a difference for you to make a decision.

Thanks, I'm sure like, I just like to add a little bit we already discussed the program that we had started, you know, with offering with IIT Hyderabad. Yeah, so that's one program, where we, like you said, we also expect people to consume a lot of content, which is already available on YouTube or any other blogs, following people, leaders, technology leaders, and seeing what sort of trends are coming up, that will give a big picture for sure. And bite somebody if they really want to get their hands on into it and start doing something. And between these AI IoT blockchain or something, you know, they're all if you individually located, they're all big in itself, but if you want to really figure out you know, where is your niche and how you want to put them together or something, then then that how do you go about it? So that's the thought behind this particular program, where we thought you know, six months course about 200 hours and delivered by it faculty, they are like the leading research experts in the country. Yeah. Just to also say it Hyderabad is the first institution in the country which have launched which has launched a full fledged B tech enabled program.

So just to add two points over here. So the first thing I think, is it is like people who might be opting, I would say they should feel lucky, because at least four years back, I didn't see any kind of like, when I when I actually started to learn, I was more on my own and it is always better to have a structured approach there will be a lot of cues that you will be getting, even you can, you know, have some mentors and all during that discussion and and and they will be the much better people to guide you in that direction. Talking about the second part of it in terms of the academy caliber I'm very sure that the institution that you have been enrolled with is certainly one of the best, at least in that domain. Definitely it is. On top of it, I think the level at which academic is being covered is more than sufficient to have solve any kind of business problem. So if you actually follow the academy properly, I mean, the level at advisor research is actually going on talking about over AI, I would say, I don't think the solution, like there isn't any solution that we can't actually device with that. So at least at least allow whatever has been expected in the industry. So the in that way, I believe. I mean, it's the program can certainly add.

I mean, definitely, I think their level of expertise that they have been bringing into the program, and and it's also fascinating to see the context that we're currently in, right, like the COVID situation and healthcare crisis. That is definitely people are looking at it in fresh ways, saying, Can I do something about it? Can I pick a crisis there? And can I implement these technological solutions? One of the one of the previous cohort participants actually built the AI solution like that, on COVID prediction using chest X ray data. And I think this is very, this is where the notion started coming up. And and that gave us some promise that, you know, we can also add the elements of entrepreneurship. Yeah, the same program and saying, if there are people who have these ideas who want to take it forward, then it is also willing forward to support them through mentorship and incubation. Any promising idea like that? Yeah. So I think that's, that's something that we have been doing from our end. Like you said, I think the first step is to just really read a lot. Yeah. Okay. That's great. Yeah. So I think some more questions have been coming judge. This thing, I'm sure has posted twice the question, is there any scope and opportunities for AI in the field of agriculture?

Ah, yes, definitely. And I would say that you should go ahead and read some of the Chinese startup which are, which are doing well, in that particular field. Haven't been too much of my interest yet. But I think there's a lot of scope. And this is an area, I believe, government is currently investing as well. So you might have some government associated incubation centers as well, who might help you, you know, have this idea as well. But again, it's not that you just you can just go and read about an idea and just be can deliver it in, in your geography. I mean, it has it, it has to be geography specific, and, and a lot of things that you have to do. But But yeah, there are many interesting things that you can, you know, take an interest from from some of the companies, you can you can just search search those companies, I think China specifically is leading in that particular domain. And us also does a few startups in that.

Yeah. So another question I noticed is, what AI is currently doing with the current technologies, and how this is going to touch the various aspects of all technologies going forward.

Yeah, so I think as I mentioned that, it will start getting into one of the fields and other fields in the within the operation of a particular company. So let's say as I mentioned, that customer engagement or customer service is something that like most of us have figured out that there is a solution using AI. And similarly in even in other kind of stuff, there will be some, some some or others thing that will that will keep on kicking in. So it's not just about the technology. It's more about the adoption in a field and a breakthrough in a particular field, within within the organization. I mean, there are many ideas for AI in marketing, then, even in end of UI and other stuff. There are some ideas around AI as well. So yeah, there's a lot of things that can be done. And for every new solution to come in, there has to be some bigger mass to start adopting it. As I mentioned, that customer service is one thing that people have started so other field also, they might start adopting it or maybe they could be a big company who would, you know, come up with this idea. So yeah, so that is what currently I feel that how it is going to grow. That's again, my thought process. It might, it might be something different. I hope it happens much sooner than what I actually think like going in stages. I would love that. Tomorrow morning, I wake up and everyone is like, I have to implement the ISO, that that would be an ideal scenario. But yeah, again, the in the realistic view, it will go in terms of phases as well. So that's what my thought process.

Yeah, I think definitely actually, like everybody wants to, but they're not yet ready for some somewhere. But I'm sure definitely will be there faster than we all predict. Right. So I think it's seven o'clock between Mr. Since we've been discussing, I am sure a lot of questions will keep on coming. And I'm afraid will not be able to answer all of those. But what we can do is we will definitely collect these questions. And we can note it separately, and we can give it back to them. That will be Yeah. And for a lot of people are asking to share some information about this course that I was just talking about that bit of the my list, take a minute to share my screen and show these programs so that we can quickly see. So this is the website of talentsprint and go to programs and for graduate programs. This is for college students, AI and emerging technologies. Why it has about this is this is the program. So yeah, so you can see, you know, a lot of startup companies from which are using AI technologies are having hiring from this pool as well. And the next cohort, I think only 10 seats are left and it's closing soon as well. So you can just if anybody's eligible, you can definitely apply. So this is all the details can be found on this program. It's a curriculum, what sort of roles are there in the industry, specifically with these sort of expertise, what the previous code participants had to say, and from which colleges have been which cities, they have been part of this cohort. So you may already know somebody from your colleges, they've already been part of this cohort. And here's a list of faculty, you can see how each another very focused specialization in this vast domain. And all of them are coming together and trying to build this course for you. And here's the curriculum as well. So it's pure, I can see a lot of people, you know, asking if I don't have the programming skills? If I don't have, if I'm not from computer science background, can I still sign up for this? The answer is yes, we do start from foundations, of course, you have to clear the selection test, that's not very easy, but you can give a fair give you a best determine if you are through them. And we will train again on the foundation so that you can really pick up. And, and we are covering a lot of content here that you get a decent exposure, Internet of Things somebody said from electronics, background Internet of Things is again, one of the topics which will be covered blockchain and quantum computing as well, is one of the topics here. And applications. I actually did mention about some of the most prominent applications we experience on a day to day basis. So you can try and understand how this works. Image Processing, speech processing, text processing, and look at the projects that already people have done. So this is what I was talking about here. COVID-19 prediction from chest X ray images. And this is something in real time you find a problem and you try and come up with a solution. So this is something very exciting. We'd like to see more and more such kind of people who are wanting to solve these kind of problems to join this cohort, that really add value to the cohort itself. Of course, additionally, a lot of other support is how you can showcase your entire learning to the outside world and make the best of you know what you have done so far. And like I already mentioned, if there are people who have these ideas, innovative ideas that you want to convert into a startup project, then it is willing to also support in the form of incubation. And, you know, fine tune your idea and create an MVP during the project phase. I think that's, I think another fascinating part of the program. So anybody from stem background can apply. There's no restriction in terms of computer background or anything. And, and like I said, we what we are looking for is people with this sort of passion who want to learn fast work who have ideally already did some amount of research, which is there in the public domain and who really want to go deeper than that. And application null is no cost. It's very simple. Just take apply on this page and give a selection tests 30 minute test. And after that you will have to write a statement of purpose as well as to why you think you should be in part of this cohort why they should select you and what you can bring in how this program can help you in the long term, things like that. And then after that, let's hope for the results. Once you get the result and a lot of support that we can give in terms of the fluffy as well, a lot of installment options, EMI options, loan support, all those things are there, so you don't really have to worry about it. So that's about it, I think this is we can share the link to all the participants as well, and so that you can check it out later.

So other questions, any other questions people have have to answer, please do feel free to write to us, we will connect essentially, and

I see one of the question in the chat, and I just wanted to actually address it. Like, I think someone was asking about how to get an internship in any of such such kind of companies. So I would what I would suggest is try mailing, you know, sending a mail to those people. I mean, also ever had a CEO, many times organization might not have a requirement of an internship. But I think if you have that kind of willingness and all you also can add value to the organization and organization as well can add a lot of value. So I think it's in both of the interest, new as well as organization to get that thing sorted. So if even if you are taking that first step so that that's a great thing. I just looked at this question and it fails that it's important for someone who is in college. So feel free to you know, write to someone connect one thing then or even writing an email. Like we do keep on getting such kind of stuff. So we are totally okay with that.

Thanks a lot. I'm sure Lynn, I do hope that you can do that. Yes. Well,

I did three. Hi, good evening. I'm so Hi, Linda. Hi, Linda. I just quickly added to what just what you just said that, you know, guys, when you when you you know directly, you asked that you know how you can get an internship with one of the one of the companies like headshots, I'll tell you about my experience and how I got in touch with them. So it wasn't in my previous organization, wherein, you know, I was I was patient enough to want to get into LinkedIn or to get hold of us, you know, until the email id and I just wrote an email. That's what I did. That's that was the starting point for me as well. So what he said, You know, I'm just gonna reiterate that, you know, if you want something to happen, or you're the one wants to make sure you take the first step and do it, you know, yeah, so that's exactly how you do it. This is how it worked for me, I got in touch with them. And of course, you know, now there's a long standing, you know, partnership between us, but then that's how you do it. That's the starting point for everyone. So just, you know, don't, you know, don't wait for, you know, things to change, you have a phone, you have all the technology in the world to reach out to people, you know, we are now technology nature that you know, there are not even you know, those were days when you just have to pick up the phone, look for phone numbers, look at directories, etc. Now reaching somebody reaching out to somebody is not very difficult. But if you're not able to get hold of unspools phone number from from anywhere, you can you can ping him on LinkedIn if you want to do that.

They say fail again. And like I would respond to anyone. I think in general, that is everyone see, I am not very sure that what is the opportunity that is there. On the other side, when someone approached me for an internship, I actually realized that oh, this can actually add value. To that time, I never even thought of having an internship is something having an intern with me is something that can actually add value at that point in time I realized and then, like it was a fruitful. So yeah, I think at times, even we don't realize in our position, and you have to initiate that thing on our end as well. So that that will definitely, you know, help you open those kinds of doors as well. Now, absolutely. Thanks

a ton. And thank you so much for your time. Thank you. Sure. Thank you.

Oh, thank you. Thank you. Thank you, uncial. We are on the table they are now and thank you for taking that one more question. What other questions I am trying to make sure that you know, we can collate it and send it to you. And give it back to them. So once again, thank you all for joining. There is this World Cup, world test temperature going on. And you can see a lot of the sports analytics there also, I'm fasting it's so fascinating to see how over the period now I've been following one sport for a long time but in the same spot I can see so much of analytics content being fed in that's really exciting to watch. I'm sure all of you also will watch and let's let's let's do some support for the country there. And on that note, we can end this and let me quickly share the link of the program before we log off here so that you can just not miss out on that as well. Okay, thank you somebody. I just saw that you posted the score. Yeah. Yeah, so I posted the the program page link here so you can just check it out quickly apply. Hardly there are 10 seats left and I think only two days left. For the application is also to be closed. So this how this program is offered only once a year. Take a shot at getting selected First, if you have the selection then nothing like it right so it can be a turning point in your life. So wish you all the best for that time, wish you all the best for all your future endeavors. And thank you so much for joining us once again. Man. I really look forward to doing more of these sessions with you once again.

We'd love to thanks everyone for for your time as well as having an interest in this. And especially thanks generous they can read it for me again.

Thank you so much I truly appreciate Thanks. Bye bye click and thanks

Watch the entire interview here https://www.youtube.com/watch?v=saJZONywiPA