Surfing the AI Wave: Nisha Talagala on Empowering the Next Generation Through AI Education
Nisha Talagala, a leader in operational machine learning and the founder of AIClub.World, emphasises the importance of AI literacy for everyone, from children to professionals. She describes AI as a powerful wave that can either uplift or overwhelm those who engage with it.
Throughout the episode, Nisha shares her journey into technology and AI, sparked by a childhood fascination with robotics. She discusses the innovative educational initiatives at AI Club, which aim to teach students how to build their own AI projects, fostering creativity and critical thinking. Nisha also highlights the ethical implications of AI and encourages listeners to be aware of how AI systems operate and the motivations behind them, ultimately empowering individuals to navigate the increasingly AI-driven world.
Main Takeaways from the Episode:
- AI Literacy is Crucial for Everyone - Nisha emphasises that AI is already deeply embedded in daily life, impacting healthcare, finance, education, and more. Teaching people, especially kids, how to understand and work with AI is essential to empower them to thrive in an AI-driven future. Education helps remove fear, fosters creativity, and prepares individuals to engage with AI responsibly.
- Customisation and Relevance are Key in Learning AI - AI education should be tailored to each learner’s interests and needs, whether they’re students, professionals, or hobbyists. By letting kids merge AI with their passions (e.g., ballet, sports, or solving local problems), AIClub.World makes learning engaging and relevant while encouraging innovation and problem-solving.
- Ethics and Critical Thinking Matter in AI Development - Nisha highlights that AI itself is neither inherently good nor bad - it’s a tool shaped by the humans who create and use it. Teaching learners about bias, ethics, and privacy ensures they approach AI responsibly and understand its potential for both benefit and harm. Critical thinking and responsible usage are key to navigating AI’s vast capabilities.
Find Nisha Talagala on LinkedIn
Find AICub.World on social media: Facebook | Instagram | LinkedIn
Textbook link: Fundamentals of Artificial Intelligence Volume 1 - For Middle School and High School Students
Forbes: Five AI Trends To Expect In 2025: Beyond ChatGPT And Friends -
Links referenced in this episode:
Companies mentioned in this episode:
- AIClub.World
- Forbes
- ParallelM
- DataRobot
- Intel
- SanDisk
- Fusion IO
- Yahoo
Transcript
So I can tend to describe AI as riding the wave.
Nisha Talagala:The AI is like a wave, right?
Nisha Talagala:It's a very, very powerful, large wave.
Nisha Talagala:You can either be on top of it or drown in it.
Nisha Talagala:There really isn't that much left.
Nisha Talagala:But if you can surf the wave, you can do a lot of cool stuff.
Speaker B:You're listening to with aifm.
Speaker B:Hello and welcome to Women with AI, the podcast dedicated to amplifying the voices and perspectives of women in the field of artificial intelligence.
Speaker B:My guest today is the CEO and founder of AI Club, an initiative bringing AI literacy to school children, students and individuals worldwide.
Speaker B: AI Trends to Expect in: Speaker B:So I just had to invite her onto the show.
Speaker B:I'm really looking forward to speaking to her today.
Speaker B:But before we jump into the podcast, let me tell you a little bit about her.
Speaker B:Nisha Talagala is a recognized leader in the operational machine learning space.
Speaker B:She has over 20 years of experience in enterprise software development, technical strategy, product leadership, leading to her work with AI, machine learning and distributed systems.
Speaker B:She's experienced in introducing technologies like artificial intelligence to new learners, from students to professionals.
Speaker B:She's also a committee member overseeing an AI education initiative across 100 schools in Sri Lanka.
Speaker B:Neesha co founded Parallel M, which pioneered the MLOps practice of managing machine learning and production for enterprises and the company then went on to be acquired by DataRobot.
Speaker B:She's also led groundbreaking projects at companies like Intel, SanDisk and Fusion IO.
Speaker B:Nisha holds a a PhD from UC Berkeley where she did research on clusters and distributed systems, holds 75 patents in distributed systems and software, has over 25 peer reviewed research publications, and is a frequent speaker at industry and academic events as well as being that contributing writer to Forbes and many other publications.
Speaker B:Above all else though, Nisha is passionate about making AI accessible to everyone, helping them navigate the opportunities and challenges of this transformative technology.
Speaker B:Nisha Talagala, welcome to Women with AI.
Nisha Talagala:Thank you very much.
Nisha Talagala:Very happy to be here.
Speaker B:Oh, it's great to have you.
Speaker B:Thank you for coming.
Speaker B:And I, I do want to ask you to tell us about what inspired you about your passion for technology and your journey into AI, which ultimately led you to found AI Club.
Speaker B:But first of all, what are clusters and distributed systems?
Speaker B:Will that become clear as we speak?
Speaker B:Because I, I don't know.
Nisha Talagala:Yeah, absolutely.
Nisha Talagala:So, so what happens is that, you know, originally when computers were created, the way you got more done was that you built a bigger and bigger computer Right.
Nisha Talagala:And these were called supercomputers.
Nisha Talagala:And some of these are honestly bigger than our fridges, right.
Nisha Talagala:And they had their own like liquid cooling.
Nisha Talagala:So if you walked into one, you know, looked at one of them, you could actually see the liquid sloshing through, trying to keep it cool.
Nisha Talagala:And then what happened is that people, particularly people at Berkeley, realized that maybe we don't need to build bigger and bigger computers, we simply need to get a bunch of computer to work together.
Nisha Talagala:So that's what a cluster is.
Nisha Talagala:A cluster is basically a bunch of computers that are going to try to be like a big computer by working together.
Nisha Talagala:And so, you know, and back then, by the way, that was a pretty revolutionary idea.
Nisha Talagala:Like at Berkeley we had a cluster of 100 computers.
Nisha Talagala:And this was like unheard of, you know.
Nisha Talagala:And by the way, it's not that Easy to get 100 computers to work together.
Nisha Talagala:Like so the way I explain this to kids is imagine if you had 100 people and you are trying to get them to do something.
Nisha Talagala:First of all you need a megaphone because otherwise half of the room will not hear you.
Nisha Talagala:The second is at any point in time, some people are ahead, some people are behind, some are asleep, some are sick.
Nisha Talagala:I mean, this is the way it is, right?
Nisha Talagala:And the more people you have in the room, the more of that that's going to happen.
Nisha Talagala:Same with computers.
Nisha Talagala:It's hard to keep them organized.
Nisha Talagala:Somebody's dying, someone's overworked, someone is under worked.
Nisha Talagala:And so a lot of the things about clusters is about that.
Nisha Talagala:And it was a hard enough problem at 100 computers.
Nisha Talagala:But these days if you look at Google, Google has millions of computer and this is how it works.
Nisha Talagala:So Google doesn't do everything.
Nisha Talagala:It does because it has one enormous computer that's several buildings big.
Nisha Talagala:It has little computers, rows and rows and rows and rows of them.
Nisha Talagala:So that technology was actually pioneered by projects like Berkeley.
Nisha Talagala:And Berkeley in fact led to one of the first search engines in the world, a company that got acquired by Yahoo, that is no longer nobody knows about, but we were literally one of the big first search engines.
Nisha Talagala:So anyway, so that's what very strongly that is what distributed computing is.
Nisha Talagala:And we do it every day these days, anytime you log into Google, you're using a cluster distributed computer.
Nisha Talagala:You just don't know it.
Speaker C:Wow, that.
Speaker B:Yeah, that blows my mind.
Speaker B:I hadn't ever really thought about it.
Speaker B:And now, yeah, I'm going to be thinking about it all the time.
Speaker B:Thank you.
Speaker B:Well, brilliant.
Speaker B:So now.
Speaker B:Yeah.
Speaker B:How did you get interested in all of this because you're obviously passionate about technology and.
Speaker B:Yeah.
Speaker B:And using.
Speaker B:Well, AI.
Speaker B:I'll let you tell it in your own words.
Nisha Talagala:Sure.
Nisha Talagala:So to be honest, I mean, when I was little, like, you know, I don't know, I want to say about 7 or 8 years old, maybe a little older, there was a TV show that I used to watch.
Nisha Talagala:It was called Small Wonder.
Nisha Talagala:And the idea was that there was a.
Nisha Talagala:This was a family and there was a little girl and the little girl was a robot and only the family knew.
Nisha Talagala:And if you go look it up, it's a very old TV show, but you can see it.
Nisha Talagala:And so.
Nisha Talagala:And I was like, you know, I want to build myself one of those, you know, And I had all these dreams that I would have one and no one but me would know that it was a robot.
Nisha Talagala:And I would, you know, keep her in the closet or like fix her, and then she would come out and play with me and stuff like that.
Nisha Talagala:So that's actually how my first interest in AI came about.
Nisha Talagala:And then when I went to study computer science for a long time, I mean, I did some AI when I was about 17, 18, but I didn't do AI for a long time.
Nisha Talagala:That's how I got into the Clusters.
Nisha Talagala:I had an amazing advisor at Berkeley.
Nisha Talagala:I kind of followed his directions and did some really cool work.
Nisha Talagala:And that I'm very happy about in Clusters.
Nisha Talagala:And so I stayed away from the AI world for quite a while.
Nisha Talagala: But then around: Nisha Talagala:And that's when I co founded ParallelM and started getting.
Nisha Talagala:And I'm super happy that I did that.
Nisha Talagala:So I've been in AI now again for about 10 years.
Nisha Talagala:And it was certainly a wonderful time because it was before all the latest craziness.
Nisha Talagala:But the latest craziness is just so much fun.
Nisha Talagala:So anyway, that's a little bit about my.
Nisha Talagala:So these days, I mean, I haven't built a robot yet, much less one that can mimic a human.
Nisha Talagala:But I found that there are so many other cool things you can do with AI that don't have to do with fooling humans, thinking that your best friend is real when she's actually a robot.
Speaker B:I like that.
Speaker B:Not yet.
Speaker B:You haven't built it yet?
Speaker B:Not yet.
Speaker B:Well, AI Club is such an exciting initiative.
Speaker B:I mean, for anyone that isn't aware of it.
Speaker B:Can you just explain it in your own words, what you do?
Nisha Talagala:Absolutely.
Nisha Talagala:And I think maybe a little bit of this also help to Understand the history, because it's not just my history, it's the history of all the people who work at AI Club.
Nisha Talagala:The leaders of AI Club is we all started as AI professionals.
Nisha Talagala:Like my previous company, ParallelM, we were helping big banks, hospitals, insurance companies build AI situations where a lot of trouble happened if they went wrong.
Nisha Talagala:Legal trouble, human trouble, you know, lots of trouble.
Nisha Talagala:And so we already knew how to do that.
Nisha Talagala:We knew how to build big AI, safe AI systems.
Nisha Talagala:But then we all kind of realized that honestly, this is a technology that everybody needs to learn.
Nisha Talagala:And it I think helped a little bit that we were parents.
Nisha Talagala:So I, at the time, you know, I started teaching my daughter AI when she was nine and I realized a couple of things.
Nisha Talagala:One, she could learn and B, if I did not really put an effort in, it got boring and tedious really fast.
Nisha Talagala:And you know, nine year old has no patience for boring and tedious, right.
Nisha Talagala:I became her data intern.
Nisha Talagala:She was frustrated, I was frustrated.
Nisha Talagala:It was a mess, right?
Nisha Talagala:But I kind of realized, hey, this is possible, but you do actually have to think about how to do it well and to engage them.
Nisha Talagala:And so that's sort of.
Nisha Talagala:And so when we started teaching AI to kids, a lot of people looked at us funny and so what do you mean?
Nisha Talagala:And I even had one dad say, I don't understand this stuff.
Nisha Talagala:How do you expect my child to understand it?
Nisha Talagala:And then he comes to me a couple of months later saying, how does she understand it better than I do?
Nisha Talagala:So, so, so I think the key was first realizing that this is actually a good idea, you know, and now, by the way, you know, Asia, for example, starts in third grade.
Nisha Talagala:They start teaching kids AI in third grade.
Nisha Talagala:So.
Nisha Talagala:And we were like, heck, we were more conservative.
Nisha Talagala:We started in middle school.
Speaker B:I think people were scared of it, weren't they, to begin with?
Speaker B:Or didn't want or worried what it might do.
Speaker B:So didn't, didn't know how to explain it.
Speaker B:That's the other thing we, you're right, grown ups don't understand it.
Speaker B:People that aren't using it, how to.
Nisha Talagala:Explain it and how to help kids.
Nisha Talagala:And pretty much anybody.
Nisha Talagala:It's not just kids help people.
Nisha Talagala:So one of the things about AI is that it is sort of both extremely deep and in everyone's lives at the same time.
Nisha Talagala:Now if you go back to like the distributed systems and cluster question you asked, you know, most adults could spend their entire life benefiting from clusters without ever needing to know what they were.
Nisha Talagala:It's not like, you know, if you don't want to know what a cluster is.
Nisha Talagala:You are fine.
Nisha Talagala:You know, it's really never, ever going to become a problem for you.
Nisha Talagala:And most computer science is like that, you know, unless you care about it, you can safely ignore it.
Nisha Talagala:But AI is not like that.
Nisha Talagala:AI is in your face every single day, you know, and it's, you know, it's in the way your doctor treats you, it's in the way your bank treats you, it's in the way that you go onto the Internet.
Nisha Talagala:And every question is about more as much about you as about the question.
Speaker C:Yeah.
Nisha Talagala:So, for example, if I decide that I want to get an Uber or some kind of a ride share, the price I get isn't just about the time and the trip.
Nisha Talagala:It's also about me.
Nisha Talagala:AI has learned what I'm willing to tolerate.
Nisha Talagala:And if I'm the kind of person who will pay more for my convenience, it will charge me more so because it has learned.
Nisha Talagala:So this world, like, where the pri.
Nisha Talagala:Everything that you deal with is now not just about your question, it's also about you.
Nisha Talagala:And these systems know more about you than you realize.
Nisha Talagala:So when you have those kinds of situations, it's important that everybody at some way understands it.
Nisha Talagala:And some people need to understand different things.
Nisha Talagala:Some people understand more or less.
Nisha Talagala:So we kind of realize that.
Nisha Talagala:And I think one of the things that I feel we've done really, really well is we've adapted how people learn it to what is right for them.
Nisha Talagala:Not everybody wants to learn probability and statistics, and neither do they need to.
Nisha Talagala:Some do, some don't.
Nisha Talagala:Some people need to understand how it interacts with their daily lives.
Nisha Talagala:Some people are like, you're a doctor.
Nisha Talagala:You need to understand an entirely different set of things about privacy and health.
Nisha Talagala:And are these things actually right?
Nisha Talagala:If you're a writer, you want to understand other things.
Nisha Talagala:So we have.
Nisha Talagala:I think we've put a lot of effort into making it the right fit to everyone because it has to be the right fit for everyone.
Nisha Talagala:So that's kind of like what we do at AI Club is we call ourselves 8 to 80, practically speaking.
Nisha Talagala:We started with my daughter.
Nisha Talagala:She was maybe 11 when we started.
Nisha Talagala:So we started with her and kids like her.
Nisha Talagala:Then we went from that to high schoolers.
Nisha Talagala:Then we went from high schoolers to elementary.
Nisha Talagala:Then we went.
Nisha Talagala:We've always worked with professionals because we are professionals.
Nisha Talagala:So we've always worked with professionals.
Nisha Talagala:And most recently, we are working with college students and students just graduating from college.
Nisha Talagala:So.
Nisha Talagala:So you can see kind of like.
Nisha Talagala:And Every approach is a little different, but it's all about AI.
Speaker B:Yeah, because you're right, it's everywhere.
Speaker B:Like, even today, I was, I was emailing.
Speaker B:I was emailing you this morning and it suddenly, my Google Mail had changed on my phone and it was like, oh, can I help you?
Speaker B:And it popped up with something and then it did on my.
Speaker B:I was sending a message to my mum on, on my iPhone again.
Speaker B:I was using Messenger, Facebook messenger.
Speaker B:And it's.
Speaker B:Suddenly there's a box and I was like, what?
Speaker B:This wasn't there yesterday.
Speaker B:Like, it's moving so quickly and I'm, I'm.
Speaker B:I'm more used to it than, say my parents are or, or other people that, that kind of don't.
Speaker B:Aren't taking any notice of it.
Speaker B:But you can't hide from it anymore, you can't ignore it.
Speaker B:So you're, you're right.
Speaker B:It's.
Speaker B:It's so important that children are being taught about it.
Speaker B:I mean, they can then teach their.
Nisha Talagala:Parents and then there's that.
Nisha Talagala:Yes, absolutely.
Nisha Talagala:So, so, yeah, so that's, I think, you know, that's kind of how we got into what we did.
Nisha Talagala:And I think one of the reasons why we're so good at it is because we actually came from the professional world.
Nisha Talagala:Right.
Nisha Talagala:So we know what is actually out there.
Speaker C:Yeah.
Nisha Talagala:We also understand the need for everyone to know it.
Nisha Talagala:And we.
Nisha Talagala:The effort we have put in as to how to connect those two, two things together.
Nisha Talagala:Right.
Nisha Talagala:Is how do you take what is true, what is state of the art, what is absolutely bleeding edge, but not scare people with it, but help them understand the things about it that are important for them to thrive?
Speaker C:Yeah.
Speaker B:And why do you think it's important?
Speaker B:I mean, is it so people use it without being scared or, you know, they wouldn't use it if they don't understand it?
Speaker B:Or is it so that everyone's kind of learning at the same time?
Nisha Talagala:So I think it depends a lot on the audience, but there are a few elements.
Nisha Talagala:Right.
Nisha Talagala:So I'll talk about the kids, for example.
Nisha Talagala:So one thing we have learned from the kids is that the kids have really infinite imagination.
Nisha Talagala:Right.
Nisha Talagala:You know how women life teaches us to not imagine at the end of the day.
Nisha Talagala:Right.
Nisha Talagala:You know, we get beaten down and we're like, no, I'm pretty sure we're not supposed to do that.
Nisha Talagala:Our first question is, are we allowed to do it?
Nisha Talagala:Second question is, do I want to do it?
Nisha Talagala:Can I do it?
Nisha Talagala:We go through all these before we actually do it.
Nisha Talagala:Kids are not like that.
Nisha Talagala:Kids are like, oh, I'm going to do that.
Nisha Talagala:I didn't even realize it was not possible.
Nisha Talagala:Right.
Nisha Talagala:And so that I think is most important about teaching kids AI is that it gets them into this mindset that maybe there's a bigger problem they can solve if they have the right tools.
Nisha Talagala:And that is the key.
Nisha Talagala:So you put the tool in their hands, you give them some examples of how the tool works, you have them build a few things that you know about, and then you ask them, what do you think you should do?
Nisha Talagala:So one of the things that we do in every single class, so we do two things in every single class we teach.
Nisha Talagala:The first is the students build an AI on their first day.
Nisha Talagala:They build one literally from scratch.
Nisha Talagala:This is not about using some tool that is out there.
Nisha Talagala:They build one and they tweak it and they understand what it's good at, what it's not good at, how they can make it better.
Nisha Talagala:That goes a long way towards sort of setting their relationship.
Nisha Talagala:The fear goes away, the sense of empowerment comes in.
Nisha Talagala:Right.
Nisha Talagala:They realize that they have agency in this situation and things like that.
Nisha Talagala:And that's where we begin.
Nisha Talagala:Then every class we teach, every course, it's a multi class course.
Nisha Talagala:Every course we teach, every student has a custom project.
Nisha Talagala:Now they get a lot of guidance, of course, tons of ideas and massive library of projects from the past.
Nisha Talagala:They can pick one if they want to, but they can create their own.
Nisha Talagala:Then what happens is that by the duration of the class, they've gone from not being scared to understanding to creating.
Nisha Talagala:That creating is a very big part because now it's like, okay, I can actually do something with this stuff.
Nisha Talagala:Right.
Nisha Talagala:And one of the beauties of AI in the fact that it's literally everywhere is that all kids are different.
Nisha Talagala:So find your joy if your joy is in.
Nisha Talagala:Like, for example, we've had, we had a, you know, a young lady who, she's a ballet dancer.
Nisha Talagala:She built a tool where you can, you know, take a video of yourself doing ballet and it will tell you what is wrong with your pose.
Speaker C:Wow.
Nisha Talagala:And.
Nisha Talagala:And you know, if your pose is wrong, you could injure yourself.
Nisha Talagala:It's not.
Nisha Talagala:I mean, there are many, many things.
Nisha Talagala:So it will.
Nisha Talagala:Your movement is a little slow here, it should be smoother.
Nisha Talagala:Your position of your leg is wrong.
Nisha Talagala:You could hurt your back.
Nisha Talagala:You know, stuff like that.
Speaker C:Yeah.
Nisha Talagala:Then similar things have been done for violin, for tennis serves.
Nisha Talagala:At the same time, we have studied students who are looking at cancer genetic markers.
Nisha Talagala:You know, I think so.
Nisha Talagala:You Know, and stuff like that.
Nisha Talagala:And so the key there is that you.
Nisha Talagala:We are not.
Nisha Talagala:We will teach you the AI, but we don't mandate what you do with it as long as it's ethical.
Nisha Talagala:We let you merge your passion with it and help you sort of like.
Nisha Talagala:So I can tend to describe AI as riding the wave.
Nisha Talagala:Like, the AI is like a wave, right.
Nisha Talagala:It's a very, very powerful, large wave.
Nisha Talagala:You can either be on top of or drown in it.
Speaker C:Yeah.
Nisha Talagala:There really isn't that much left.
Nisha Talagala:But if you can surf the wave, you can do a lot of cool stuff.
Nisha Talagala:Yeah, you teach them to surf the wave.
Speaker B:I think that's such a good analogy because it's almost like the people that are burying their head in the sand or, well, they're just.
Speaker B:They're not looking at the wave.
Speaker B:They're not looking and it's just going to crash over them and just knock them over because they're not expecting it.
Speaker B:That's because I think there's so much, you know, about, oh, it's.
Speaker B:It's terrifying.
Speaker B:It's going to take your jobs, it's going to do this, that and the other.
Speaker B:And it's.
Speaker B:You're right.
Speaker B:Like, this is coming at it from a completely different angle and starting, you know, with educating people about it.
Speaker B:It just makes so much sense because then, you know, how to spot, I suppose, the scary bits and the bits that people don't trust because, I mean, it's really interesting because you're saying it's use it.
Speaker B:You know, the kids are sort of using it and they're using their imagination.
Speaker B:Start with.
Speaker B:Because a lot of the time people are like, oh, well, it's going to take away imagination.
Speaker B:You know, if art and music is just going to be written by AIs.
Speaker B:But I guess that's where you've got to have the humans that have written the AIs that are then nurturing them and using them, as you say, as a tool.
Speaker B:You're not.
Speaker B:We're not just going to sit back, I hope, as a race, and just be like, oh, AI, over to you.
Nisha Talagala:Yeah.
Nisha Talagala:So, like, for example, and this is very important because, I mean, we.
Nisha Talagala:I mean, we make, you know, we teach AI ethics in every room, but sometimes we don't teach it as a topic.
Nisha Talagala:We just make sure they appreciate the ethics through experience.
Nisha Talagala:So I'll give you a simple example.
Nisha Talagala:Like, for a.
Nisha Talagala:Like for a young child, the first thing we do is we show them how to build an AI.
Nisha Talagala:It's a very simple AI.
Nisha Talagala:It detects Whether you're happy or sad by the stuff you type.
Nisha Talagala:Okay?
Nisha Talagala:And so.
Nisha Talagala:And it was, you know, sourced by, you know, kids their age.
Nisha Talagala:So, you know, it'll think that chocolate is happy and broccoli is sad and, you know, this and that.
Nisha Talagala:And so it's very, very kid, you know, natural to contain anything that, you know, is inappropriate for kids.
Nisha Talagala:Then what we do is we let them loose and ask them to teach it whatever they want.
Nisha Talagala:So, you know, someone will teach that rabbits are good.
Nisha Talagala:Someone else will teach that their little brother is the source of all evil.
Nisha Talagala:You know, I mean, they will teach anything, and they'll have a glory of a time with it.
Nisha Talagala:And they will also see that the things they teach it change its way of thinking, you know, and what it takes to get the AI to believe whatever you want.
Nisha Talagala:And then I always ask them a question.
Nisha Talagala:Did the AI ever ask you whether what you taught it was true?
Nisha Talagala:And the answer is no.
Nisha Talagala:The AI will never ask you whether what you taught it was true, which means you can teach it anything.
Nisha Talagala:And then I ask them, okay, who's responsible for making sure the thing is behaving?
Nisha Talagala:And the answer to that is you.
Nisha Talagala:Right.
Nisha Talagala:So what is your role in all of this?
Nisha Talagala:It's my job to make sure the thing behaves.
Nisha Talagala:One of the many ways I do that is by not teaching it bad things.
Nisha Talagala:And so it's very important because it's.
Nisha Talagala:So did we teach them ethics?
Nisha Talagala:Yes, but we didn't teach it in the abstract.
Nisha Talagala:By simply realizing how easy it was to teach the AI any bad thing, they immediately understand their role in this situation.
Nisha Talagala:It empowers them, and it also shows them the right way.
Nisha Talagala:And now they're in a position where they can talk about bias, about fake news and this and that, because they can appreciate the process that leads to it and the trouble that it creates.
Speaker B:And they'll get better at spotting it than, say, their parents or people that aren't.
Speaker B:I want to come to your school now.
Speaker B:I want to join the AI Club.
Nisha Talagala:You see how it's kind of like it weaves in?
Speaker B:Yeah.
Speaker B:And so because you're doing.
Speaker B:If you're doing it at the schools in Sri Lanka, have you seen a difference?
Speaker B:Like, is sort of doing it to a different audience?
Speaker B:You know, is it different there to.
Speaker B:It is in the US or.
Nisha Talagala:I believe it is in many ways.
Nisha Talagala:But I can tell you that one of the easiest ways to talk about the difference is that we focus on problems that matter to them.
Nisha Talagala:For example, the kids that are building custom projects In Sri Lanka, some of them are building them on, detecting pests that are unique to that part of the world.
Nisha Talagala:There was one kid who did predicting used bike prices.
Nisha Talagala:It turns out the used bike industry is a very big deal in Sri Lanka, and there's a lot of people trying to figure out the right used bike price.
Nisha Talagala:So you can see that there's a lot of stuff that you can do that's very, you know.
Speaker C:Yeah.
Nisha Talagala:Very unique to that environment.
Nisha Talagala:And there may be things, but there are things that cross over.
Nisha Talagala:Everybody loves Harry Potter, so like that.
Nisha Talagala:So some things cross over, but, you know, you do see kind of a shift in.
Nisha Talagala:And that's one of the things I love about the custom projects, is that the custom projects allow these children to do something that matters in their world.
Speaker C:Yes.
Speaker C:Wow.
Speaker B:And I guess doing that.
Speaker B:Yeah, it's just putting them in good stead for the future and so.
Speaker B:And helping to understand because there's lots of.
Speaker B:There's governments using it, like over here in the uk you know, the government has just announced that they want to, like, you know, instill AI in everything.
Speaker B:I mean, how is there anything that worries you about all of that?
Speaker B:I mean, how, you know, in all your experiences, do you think we should be paying closer attention to anything before it happens?
Nisha Talagala:I mean, so if you look at any example of a massive technology wave, it has enormous good and enormous bad.
Nisha Talagala:AI is probably larger than any of them.
Nisha Talagala:So I'll take a simple other wave that, you know, and I can take two other waves and I can show you why AI is larger, both positively and negatively than both of them.
Nisha Talagala:So if you think about nuclear power, right.
Nisha Talagala:Nuclear power powers a lot of homes on the planet.
Nisha Talagala:We may not even realize it.
Nisha Talagala:You know, it's a very powerful technology.
Nisha Talagala:But we've had our share of nuclear accidents.
Nisha Talagala:You know, they've been devastating.
Nisha Talagala:And even to this day, keeping the planet from being destroyed by nuclear power is an active effort.
Nisha Talagala:There are issues, Right.
Nisha Talagala:There are rogue nations or nations, right?
Speaker C:Yeah.
Nisha Talagala:We try to control are they building centrifuge this pluton, you know, enriching that.
Nisha Talagala:It's not like a thing.
Nisha Talagala:It's not a solved problem.
Nisha Talagala:It's a problem that's actively being maintained.
Nisha Talagala:Yeah.
Nisha Talagala:On the other hand, the average person cannot build a nuclear reactor.
Nisha Talagala:And you don't build one without leaving a ton of evidence behind.
Nisha Talagala:And so that's an example of a technology that can do tremendous damage in one bad event.
Nisha Talagala:But it's really hard to build.
Nisha Talagala:Now, if I take the opposite of a car Right.
Nisha Talagala:A car is literally everywhere.
Nisha Talagala:We all have them.
Nisha Talagala:Our ability to cause trouble with cars is nearly infinite, and we have laws to prevent them.
Nisha Talagala:But if you decide to cause trouble with a car, there's only so much trouble you can do with a car.
Nisha Talagala:You can set your car on fire, you can hit someone, but you can't like eradicate a city with your car.
Nisha Talagala:So the problem with AI is that it has the ease of the second and the damage of the first.
Nisha Talagala:Like, I can sit on my computer and create trouble for a lot of people, and I can do it without anyone being able to track me.
Nisha Talagala:So it has like, almost like the nuclear level damage and the car ease.
Nisha Talagala:Yeah, that makes sense, right?
Speaker B:Yeah, that's the scary bit.
Nisha Talagala:And that's the scary bit.
Nisha Talagala:And so, but just like it has to be managed.
Nisha Talagala:It has a potential for a lot of good, it has a potential for a lot of bad, and it's not the AI.
Nisha Talagala:One of the things that I think we try very much to instill on our students is AI is not good and AI is not bad.
Nisha Talagala:AI is just a computer.
Nisha Talagala:Humans make it good or bad.
Nisha Talagala:Humans are always the cause of most of our problems, to be honest.
Nisha Talagala:You know.
Speaker B:Yeah.
Nisha Talagala:And so it really comes down to.
Nisha Talagala:And what we will do with it as a society will determine how it goes.
Speaker C:Yeah.
Speaker B:And that's where the education comes in.
Nisha Talagala:That's right.
Speaker B:And it's so important.
Speaker B:Can you've just done.
Speaker B:Because you've just started the AI club, the research program.
Speaker B:Is that right?
Speaker B:Is that a new.
Speaker B:Is that a new ARM or.
Nisha Talagala:No, it's.
Nisha Talagala:We've been doing it for a few years now.
Nisha Talagala:And it's definitely something we're very proud of.
Nisha Talagala:And it's also another.
Nisha Talagala:Like everything else was basically something that a lot of people thought was really just nuts when we started it.
Nisha Talagala:But one of the things that has happened that we realized this by having kids build their own projects, is there's a tremendous amount of public data out there and a tremendous amount of easy to access compute.
Nisha Talagala:Like, I can sit at my computer, I can get myself a free Google account, and I can do things on their massive forms of computers that you could never imagine, at least when I was the age of these kids, that allows them to solve problems that were previously the domain of graduate students.
Nisha Talagala:And they have the imagination, the energy, the, you know, the aptitude, as long as it's taught them the right way.
Nisha Talagala:So the research program is almost exclusively focused on high school students, sometimes middle, sometimes college.
Nisha Talagala:But we have asked them to really take the research to the state of the art.
Nisha Talagala:We teach them how to think, how to write.
Nisha Talagala:Right.
Nisha Talagala:How to solve a hard problem.
Nisha Talagala:So we have kids in the research program who are doing amazingly innovative things with climate science, with, you know, genetics, with bio, you know, bioinformatics, and also kids who are doing amazing, innovative things in sports, in music.
Nisha Talagala:Right.
Nisha Talagala:But the idea is we want them to start early, understanding how to tap into their own brains and into the technology to really solve hard problems.
Nisha Talagala:That positions them extremely well as they go into college to further that journey.
Nisha Talagala:Because if you think about it right now, one of the things that I, you know, I find very.
Nisha Talagala:It's something everyone should think about.
Nisha Talagala:The latest AIs.
Nisha Talagala:You know how when AIs are announced these days, they come with their test scores?
Speaker C:Yeah.
Nisha Talagala:The AI from, you know, AIs last year be it did better on the US medical licensing exam than 80% of the country's doctors.
Nisha Talagala:You know, they are, they excel at the scat stat, at the bar exam, every possible, you know, measure that we use.
Nisha Talagala:And so now I think about it, and I think about, like, kids like my daughter.
Nisha Talagala:I mean, why should.
Nisha Talagala:What is it if, if these AIs today.
Nisha Talagala:AIs today are doing better than most young people in an exam she's not even going to take for four years.
Speaker C:Yeah.
Nisha Talagala:Why is she even taking that exam?
Nisha Talagala:What does it even mean?
Speaker B:Yeah.
Nisha Talagala:Right.
Nisha Talagala:So where is she going to find her job?
Nisha Talagala:And so the research is sort of our way to show you you can do more.
Nisha Talagala:Will show you how.
Speaker B:Yeah.
Speaker B:Because if the AI has learned all that and done all that and you can just go, what is the answer to this?
Speaker B:Or how do we do that?
Speaker B:Then hopefully that frees you up your mind to look into something else or to actually go and speak to that person about this or look into something else.
Speaker B:But then what do you think then about the kind of the fact that people talk about AI hallucinating or that it's learned from all the data that's out there?
Speaker B:So now it's just going to start learning from itself.
Speaker B:And it's not always true.
Speaker B:It doesn't always give you the right answer because, you know, you can say just an example in, in the office where I was working yesterday, someone said, oh, well, I asked, you know, chatgpt to refine my Twitter message.
Speaker B:So X message.
Speaker B:So it was 280 characters.
Speaker B:And they said.
Speaker B:And it said, yes, it is.
Speaker B:And then they're like, no, it's like 350 and it's.
Speaker B:And so What?
Speaker B:How do we make sure that the AI isn't just going to start fabricating stuff and making stuff up?
Speaker B:Because if no one's learned the bar exam or done the medical, you know, seven years, then what happened?
Speaker B:Like what?
Speaker B:Yeah.
Speaker B:What do you think about that?
Nisha Talagala:No, no, this is.
Nisha Talagala:This.
Nisha Talagala:This, I think, is the crux of the thing.
Nisha Talagala:So AIs are very, very helpful to people who can read what they create, separate the good from the bad, and build on now.
Nisha Talagala:But, but.
Nisha Talagala:So you should never trust an AI blindly, ever.
Nisha Talagala:So it's really not that you don't learn these things, it's more that you learn them, but you go beyond them, right?
Speaker B:Yeah.
Nisha Talagala:You know, and there are things that you may not learn, but it's not that you don't learn the topic at all, but maybe you don't necessarily learn.
Nisha Talagala:Like, for example, like, my mental math these days is awful.
Nisha Talagala:You know, but that's okay because I, you know, I can use a calculator.
Nisha Talagala:I have calculators available in so many different forms, including on my computer if I had to.
Nisha Talagala:I can do mental math.
Nisha Talagala:I just don't.
Nisha Talagala:Can't do it as fast as I used to.
Nisha Talagala:Right.
Nisha Talagala:So it's really about that.
Nisha Talagala:It's not about black and white.
Nisha Talagala:I don't do this.
Nisha Talagala:I don't do this.
Nisha Talagala:Like, I focus my energy on other things.
Speaker C:Yeah.
Nisha Talagala:So.
Nisha Talagala:And what makes things really hard, particularly for education systems, is that gray we can do binary, we can say, you don't need to take that course anymore, you have to take this course.
Nisha Talagala:But it's not that simple.
Nisha Talagala:You have to take that course.
Nisha Talagala:Just maybe not as effective, intensely as you used to.
Nisha Talagala:And that's so hard to traverse.
Speaker C:Yeah.
Nisha Talagala:So a real and a simple example, I wrote a Forbes article about this that, you know, that I'm actually happy that I wrote very much, is that it's also about code.
Nisha Talagala:Like, AIs can write code, and their code has gotten a lot better.
Nisha Talagala:It's actually not bad at all, the code that it generates.
Nisha Talagala:But now the question becomes, I know that it can do better because I can read its code, and I do every single time.
Nisha Talagala:I never run anything that I don't read.
Nisha Talagala:And at the same time, how did I learn how to read it?
Nisha Talagala:I wrote a lot before the day of AI.
Nisha Talagala:Right.
Nisha Talagala:Now, if you look at kids, if you don't make them write it, how can they learn to read?
Nisha Talagala:So you still have to make them write it, but you also have to help them to appreciate that writing may not by itself be A skill that they can sustain.
Nisha Talagala:So it's kind of like you have to learn to write because otherwise you won't know how to read.
Nisha Talagala:And if you don't know how to read, you can't build on it.
Nisha Talagala:But you also have to understand that if you learn how to write, you can say, hey, I'm done.
Nisha Talagala:Because that skill will not get you employed anymore.
Nisha Talagala:So you see how it's tricky, right?
Nisha Talagala:And hallucinations tie into this.
Nisha Talagala:I mean, AI is.
Nisha Talagala:Hallucinations are honestly.
Nisha Talagala:I think if you talk to different AI people, they'll tell you it'll go away.
Nisha Talagala:And it honestly is getting better.
Nisha Talagala:But you also have to understand that they are also part and parcel of how the thing works.
Nisha Talagala:Humans come up with stuff all the time.
Nisha Talagala:Sometimes you don't even realize we're making things up.
Speaker B:Well, exactly.
Nisha Talagala:So it's one of those things that you just have to kind of.
Nisha Talagala:You cannot have a blind faith in the thing.
Nisha Talagala:So you have to find some middle ground.
Nisha Talagala:You cannot ignore it.
Nisha Talagala:You cannot use it blindly.
Nisha Talagala:You have to use it intelligently.
Nisha Talagala:And that is what is so hard.
Nisha Talagala:Because it's not an easy thing.
Nisha Talagala:It's not an easy thing.
Nisha Talagala:I can do it.
Nisha Talagala:I can teach people how to do it.
Nisha Talagala:But imagine a legion of teachers trying to teach people how to do it.
Nisha Talagala:Right?
Nisha Talagala:Yeah, it's not easy at all.
Nisha Talagala:And that was actually a funny thing that I saw.
Nisha Talagala:So there's.
Nisha Talagala:So I'm not going to drop any brands here because I don't think that would be fair.
Nisha Talagala:But there are several companies that are coming out with, quote, unquote, AI engineers.
Nisha Talagala:This is a piece of software that I can buy that effectively is meant to work like a junior engineer.
Nisha Talagala:Okay.
Nisha Talagala:And it's, it's.
Nisha Talagala:And so if you think about.
Nisha Talagala:That's very, very direct, right?
Speaker B:Yeah.
Nisha Talagala:And I can tell you that it is 110 more than 1/10 cheaper than a junior engineer.
Nisha Talagala:But here's the interesting thing.
Nisha Talagala:Somebody posted and they hired one of these things, right?
Nisha Talagala:Or I don't know if hired is even the right word.
Nisha Talagala:They bought hired, you know, onboarded, downloaded, whatever it is, one of these things.
Nisha Talagala:And they said, you know, it gave.
Nisha Talagala:I gave it a small task and it nearly deleted all of my company's data.
Nisha Talagala:And, you know, and people responded.
Nisha Talagala:Every junior engineer does that.
Speaker B:Oh, yeah, this is why we have guardrails.
Nisha Talagala:It's a right of passage for any young engineer to almost delete the company's data.
Nisha Talagala:Otherwise, how do they learn it?
Nisha Talagala:So there was like, the massive joke is like, oh, it's behaving exactly like a junior engineer.
Speaker C:Yeah.
Nisha Talagala:So.
Nisha Talagala:So, you know, so to end that really interesting middle ground.
Speaker B:Yeah.
Speaker B:You have made me feel a lot, a lot happier or kind of a lot, you know, give me lots to think about, but just that it's all about the education and people.
Speaker B:Yeah.
Speaker B:We need to embrace it.
Speaker B:And you're right.
Speaker B:We can't, you know, take a hit in the sand.
Speaker B:We've got to be prepared to ride their wave.
Speaker B:Yeah.
Nisha Talagala:There's nothing else to be done.
Nisha Talagala:And the other thing to also remember is that any AI we teach right now is not the AI these kids are going to use in five years.
Nisha Talagala:So we're not asking them to be experts in that.
Nisha Talagala:We're asking them when something new comes, they understand the fundamentals well enough to appreciate what the new thing is and surf the way.
Speaker C:Yeah.
Nisha Talagala:And if you teach them how to do that, then whatever shows up, they will adapt.
Speaker C:Yeah.
Nisha Talagala:And that's what we did.
Nisha Talagala:Like, the things I used these days are not the things I learned in college.
Nisha Talagala:Heck, the things I learned in college barely exist anymore.
Speaker C:Yeah.
Speaker B:No, you're right.
Speaker B:It does all change.
Nisha Talagala:It all changes.
Nisha Talagala:You have to get used to that.
Nisha Talagala:You have to accept that, and you have to learn to adapt to it, because there's nothing that is probably the single valuable, most valuable skills.
Nisha Talagala:You have to learn to think with tools.
Speaker C:Yeah.
Speaker C:Yeah.
Speaker B:So what excites you most about the future with AI?
Speaker B:What do you.
Speaker B:What do you see coming?
Nisha Talagala:And honestly, the research program really excites me because every day I see things that, you know, I.
Nisha Talagala:I see young people doing things that I would not have thought were possible a decade ago.
Nisha Talagala:And I see the amount of just available knowledge and power at their fingertips.
Nisha Talagala:Right.
Nisha Talagala:99% of the kids we work with are working with open data.
Nisha Talagala:Very, very few of them have proprietary data.
Nisha Talagala:And they're able to do amazing things.
Nisha Talagala:And also, the amount of open data that's out there is unbelievable.
Speaker C:Yeah.
Speaker B:I think lots of people don't realize, do they, that once they've used an AI particular, it's out there.
Nisha Talagala:Exactly.
Nisha Talagala:And the amount of software that's out there to process that open data is unbelievable.
Nisha Talagala:So I think that really, really gives me hope because I see and through the research program, just young people truly doing incredible.
Nisha Talagala:Many of our research program students work on more than one project with us.
Nisha Talagala:So I see their thinking evolve.
Nisha Talagala:Their thinking, their capabilities, how do I say?
Nisha Talagala:Their drive.
Nisha Talagala:It's interesting because we had one young man, a very exceptional young man, who recently got into mit.
Nisha Talagala:And so of course getting into MIT was impressive, but that's not what impressed me about him.
Nisha Talagala:First year at MIT, he convinced MIT's top AI research lab to accept him.
Nisha Talagala:He's an undergrad.
Nisha Talagala:It didn't even occur to him that he needed to be a grad student.
Nisha Talagala:He got them to accept him.
Nisha Talagala:And that's my point, is that you want to put them in a position like, oh no, no, I can do this.
Speaker B:You know, yeah, we all need to be more like that.
Nisha Talagala:So hopefully we can just, I mean we don't all need to be that, although, you know, but we need to be more like that.
Nisha Talagala:To your point is that you want to feel like this is going to empower you.
Speaker C:Yeah.
Nisha Talagala:And that's, I think that's what I'm excited about.
Speaker B:And is there anything that we should be paying closer attention to, do you think?
Speaker B:Is there anything that you not warn students but you just say make sure you think about that.
Nisha Talagala:I mean, I think generally speaking I would say that anytime you work with an AI, think about who is paying for that thing and what is it that they want.
Nisha Talagala:Because the AI by itself is not good or bad, but it is probably extremely good at doing whatever it is that its creator wanted you to do.
Nisha Talagala:A lot of AIs want to learn more about you.
Nisha Talagala:Whether you choose to let them is entirely your decision.
Nisha Talagala:But you should understand that that's what they want.
Nisha Talagala:In fact, one of the things that, you know, one of the little exercises that I typically run with, you know, school age children is we take a big, I'm not going to in a name, but we will take a big website that sells everything, right?
Nisha Talagala:And we, I ask them, what is it that this site knows about you?
Nisha Talagala:And we have an open, empty whiteboard and we fill it in and by the time it's done, we fill.
Nisha Talagala:So first thing is, does it know where you live?
Nisha Talagala:Yes, otherwise where would the packages go?
Nisha Talagala:Second is, you know, do you think it knows how many people are in your family?
Nisha Talagala:Well, if you are buying clothes from it, it probably figured out that there's, you know, who, how you are, roughly how old it.
Nisha Talagala:Does it know when your birthday is?
Nisha Talagala:If you or bought birthday cakes probably or any other kind of banner the.
Nisha Talagala:And you know, does it know where your grandma lives?
Nisha Talagala:You ever order a package for grandma, a gift that you delivered?
Nisha Talagala:Does it know if you've moved?
Nisha Talagala:Yes.
Nisha Talagala:Your addresses has changed?
Nisha Talagala:You know, does it know whether you've lost weight pretty down likely if you are, you know, if you've Been buying clothes.
Speaker C:Yeah.
Nisha Talagala:Right.
Nisha Talagala:And this and that.
Nisha Talagala:And this, by the way, is.
Nisha Talagala:And we can fill the whiteboard with things this company knows about you without ever touching things that are legally private.
Speaker C:Yeah.
Nisha Talagala:This is assuming its device in your house is not listening to you.
Speaker C:Yeah.
Nisha Talagala:This is assuming it doesn't know your prescriptions.
Nisha Talagala:Right.
Nisha Talagala:So now you think about, what is it that it knows?
Nisha Talagala:Right.
Nisha Talagala:And then now they want, do you.
Nisha Talagala:Are you okay with that?
Nisha Talagala:And so one of the questions I ask kids is a simple thing, which is if a company, if your grocery store tells you that if you buy a loyal, get a loyalty card, you'll get 10% off on eggs.
Nisha Talagala:But they will know that you buy eggs.
Speaker C:Yeah.
Nisha Talagala:And most of the kids are like, big deal.
Nisha Talagala:It's eggs.
Nisha Talagala:You know, there will be at least one or two children.
Nisha Talagala:They have no business knowing whether I like eggs.
Nisha Talagala:Right.
Nisha Talagala:And that's a personal choice.
Nisha Talagala:Then we ask the next question, which is, okay, no problem with eggs.
Nisha Talagala:What if you buy back pain medicine off the counter?
Nisha Talagala:Now, some of the kids are like, I'm not sure I like that.
Nisha Talagala:You know, Next question.
Nisha Talagala:Okay, it knows you bought back pain medicine for your dad.
Nisha Talagala:I probably figured out that your dad has back pain.
Nisha Talagala:What if it goes and tells your dad's boss?
Nisha Talagala:And now all the kids are like, no, no, no, no, no.
Nisha Talagala:So half of it is just understanding where your comfort lies, because these systems are tune from the ground up to learn about you and find a way to use that knowledge to make money.
Nisha Talagala:And that could include trying to sell you things.
Nisha Talagala:It could include teaching about you to other people.
Nisha Talagala:It could include so many things.
Nisha Talagala:So you be aware and you do what's right for you.
Nisha Talagala:So that's what I would say is everybody should just.
Nisha Talagala:Just be aware.
Nisha Talagala:You know, it's your decision whether you are willing to let them know, you know, whether that you like eggs.
Nisha Talagala:That's entirely your decision.
Nisha Talagala:There's no, like, moral, absolute right answer to it.
Nisha Talagala:But I hope that it's a decision you make yourself and it's not made for you.
Speaker C:Yeah.
Speaker B:And that's why, if you understand it, you can put things in place so that you're not sharing that or you are sharing that, or you don't mind sharing that, but you don't want to share that.
Speaker B:And I suppose, yeah, that's where people get scared because they don't know what to do.
Speaker B:Nisha, I could talk to you all day.
Speaker B:This is fantastic.
Speaker B:But everyone that's listening, that wants to know more about this and want to start their own journey into like maybe building AI or literacy and the resources and tools like what, what advice do you have?
Speaker B:Where do you recommend people start?
Speaker B:Or where can they go?
Nisha Talagala:We, we.
Nisha Talagala:So my colleague and I did write a textbook.
Nisha Talagala:It's a textbook for middle school and high school kids.
Nisha Talagala:But it's honestly, it's a really easy read for even adults.
Nisha Talagala:You might want to try that, I think.
Nisha Talagala:You know, Shashi sent you the link.
Nisha Talagala:Yeah.
Nisha Talagala:Go to our website.
Nisha Talagala:There's a lot of cool resources there.
Nisha Talagala:A lot of blogs that we write.
Nisha Talagala:Yeah, yeah.
Speaker B:Or is that the fundamentals of Artificial intelligence?
Nisha Talagala:You can take a look at that.
Nisha Talagala:And you know, and I would say maybe even the first three or four chapters are more than enough for you to learn what you want to know about AI.
Nisha Talagala:To get started, you don't need to read the whole thing.
Nisha Talagala:So that's a thought.
Nisha Talagala:You can read some of the stuff on our blog.
Nisha Talagala:You can see what some of the kids have built.
Nisha Talagala:There's a lot of, you know.
Nisha Talagala:So we run a research symposium every year.
Nisha Talagala:We have kids speak about what they did.
Nisha Talagala:It's all like 10 minute talks.
Nisha Talagala:I encourage people to listen to them because hearing them in their own voices of what the kids have done gives you a really good feel for what is this thing?
Nisha Talagala:Right.
Speaker C:Yeah.
Nisha Talagala:See it from the point of view of a young person and then what are these problems that they're solving and how did they solve them?
Nisha Talagala:So that's a good way to, you know, just kind of get started.
Speaker C:Brilliant.
Speaker B:Well, I'm going to put links to all of those in the show notes.
Speaker B:So thank you, Nisha.
Speaker B:And all that's left for me to say is.
Speaker B:Nisha Talagala, thank you for coming on Women with AI.
Nisha Talagala:Thank you very much for having me.
