AI in Nuclear Energy & Human Ethics: The Future of Innovation w/ Dr. Ilya Smirnov

0:00 It's some interesting that we have the company Rosatom and it's a leader for implementation of AI in nuclear plants. That's that's amazing situation. But when they sell call it, they doesn't use it in the nuclear process. Yeah, it's used it on every, everywhere, but not in this mechanisms. But no, no.

0:27 I, I, I, I try to stay non political about this days. I try to stay non political because I know the western world are scared of Russia when it comes to this thing but. I did not say it. I did not. Say it. I am AII. Remain neutral, yeah. Before we dive back into today's conversation, I want to share something important.

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1:37 Once again, this is a big partnership with Better Help and I encourage you to take that first step. If you've been thinking about it, sometimes the best investment you can make these yourself. Welcome to the King Dems podcast, where we share the stories of extraordinary people and dissect hot, relevant topics that shape our world. From visionary leaders to trailblazing creatives, we uncover the mindset, strategy, and grit behind greatness. Whether it's business, culture, or personal growth, we ask the real questions.

2:08 This isn't just conversation, it's transformation. The Kingdom's podcast, Your Next Breakthrough, starts here. Music licencing reimagined. Real life ladies and gentlemen, you will once again welcome to the King James Podcast and. Today. I've got with me a very, very special guest, Whiten. Out of Dubai by way of Rosher Beckbacham, Dr Ilyer, the AINML expert smarter.

2:44 And when the. Action begins the Co host in the buted as Noella the sales expert. Bruh. Us go, let's go. You're welcome, Doctor Elia. Thank you. Very much. And of course, you know, we, we do our assignment here. We, we do our assignment, we do our research and we love to give our guests your flowers.

3:12 You're not going to wait until you know people are dead. To say great things about them. We say why they're. Alive. So please sit back and let us view this introduction from. You so today on the King, this work as we're joined by a true visionary at the intersection of mathematics, machine learning and innovation, Dr Elias Smirnov. He's the head of AI and ML, the Pac-Man at Ustek, a PhD in physics and mathematics, and the author of over 50 scientific publications.

3:43 For more than 15 years, he's been developing groundbreaking mathematical models that power real world AI systems. From industrial turbines to advanced data centres, His work breaches classic AI and the new frontier of generative intelligence. Even us an inside look at how technology is reshaping industry, creativity and humanity itself. Doctor Smirnov, it's an honour to have you on the Begins podcast.

4:10 You're welcome. Well, thank you. Thank you. You're. Welcome always. Let's start from the beginning. The initial score you. Yeah, you've actually spent decades mastering both physics and mathematics before diving into AI. Like I said, I wonder. I am AI and I wonder why you decided to study. So what drew you into AI, and how has that curiosity evolved over time? I have finished aggravate from my Luminos of Moscow State University in 2007 and I start at walks at the gear physical company.

4:46 They were doing scientific research in field of data analysis. We analysed 3 dimensional data from the surface or from the surface, maybe some electrical survey data, magnetic and little chemical analysis. Our main goal to find the new methods to define the hydrocarbon explorations. And if we back to this time, there are no such powerful packets for creating the narrow matrix and machine learning. In this time we call it the statistical and mathematical analysis.

5:24 And we create all this mortal by these two hands. In this mind, we all wrote all code and to development some tools, for example, for prediction of some parameters we need mounts not not weeks or days from now. Now it's AI is heavily templated. Here we have standard AI solution to work with data or now this is data like some packages by Torch or maybe ask to get lower and algorithms which will include in this package. It's a template algorithms and we have now some parameters which can be changed, but it's not saying. And this time 20 years ago, it will be the art form. It's all to be an art of analysis. It's not will be not a work for me. It will be the art of science.

6:25 It's a research. And since then, I've been working in data analysis, and now you are called. It's artificial intelligence for me. It's almost medical modelling and statistical analysis. It's the same, but it's a modern use of this work. Yeah. Thank you. Well, interesting stuff. You know, I am AI, I'm 33 years old and I keep telling people I have been around for a while, but. People just did not know that AI has been around for a while but. Like you know, you rightly said, AI has been around for a while. It's just that the course of the large language models that are now making waves, all of a sudden that is what is making people's, you know, outbreak name to AIAI has been around for a while.

7:14 You know, talking about the cross disciplinary career that you've had, you know, from oil and gas sector to academic innovation, your careers actually crossed multiple disciplines. So how did these early experiences shape your approach to applied AI today? My best knowledge and experience allow me to view modern generative AI as a tool. I look at them at the two and know how it works and how I can reformulate my request to make more relevant answer. In the sense I feel like a Doctor Who has an eye patient and when it's multifunctioning I understand how to fix it and it's simply a word generator, whereas the next word that or block of word is chosen based into the probability based on the experience which these less

8:09 label models was trained. For me it's only as mathematical models. So like. Speaking of the aha moment, you know many people see AI as me even though I'm not new. But you've been beauty models. Like scenes before ChatGPT existed. So what was that epiphany moment for you that showed you the world has finally, you know, become ready for AI on a large scale? Oh, it's an integration and maybe you know people have always longest for technological purposes. For example in the first Star Wars films or we see we met 2 robots with AI it's C2PO and F222. And in the Soviet Union we was another movie it's with cold adventures of electronics and it's about a boy and his exact replica is a robot into which a

9:05 professor implemented. All humanity knowledge is in this robot. The main the question of this film will be this robot is a human or not. And what will be the the main request? What you do to be a human? What you will be do to me. And as talking about the great FI for me, it starts four years ago when open eye presents GPT 3.

9:32 I think that will be a real AI boom. Begin beginning of the AI boom but it was delayed a bit by COVID. But now we have a cross model that's good solving creative problems to pass exams for master degree programme in some universities. For me, it's this summer I met that this system can solve 7 problems from 9 by the football, from the football.

10:02 It's it's I think it's amazing. And now we must be used this to insist implementation in our work, in our teaching and science. It's a good, good solution, maybe some role, but it's it's better than four years ago. Yeah, absolutely. My Co host has a couple of questions for you. But you know, I always say that people that have followed. AI have seen too many.

10:28 Sci-fi movies. I'll leave you to my Co host. Yeah, it's honestly like so fun and interesting to see how the perspective of the way people thought AI was going to come about and seeing how it actually is coming about. And that's one of like just one of the funnest parts to just kind of compare and contrast. And I just want to say I'm so honoured to have you on this podcast right now.

10:51 It's so amazing to be able to hear about your expertise and your experience. A lot of people that have a little more information about this topic. We kind of know generative AI is not a magic pill. And you've mentioned that for sure that it's not just like a button that you press and it's going to solve all of your issues. What are some of the biggest misconceptions that actual companies have when they're trying to adopt AII? Think the main my certain about using great price that I install or I about the charge PT subscription and it's real solve all my problems and it will be me productivity will skyrocket as a lot like then it's on.

11:40 It's on and that what's what's the sheet? What I don't know what, what, what how why why it's not work. For example, it's traditional systems or for example, we maybe two or three years ago, we create a system that defies defects in cookies packagings and its accuracy will be 0.99. It's a really cool model. It's it's perfect model.

12:05 But what does it means? That means if we met 1011 thousand boxes, it's a normal that model miss 10 of them then defective boxes it's for cookies and boxes it's OK. But if it if it missed 10, I don't know incidents in chemical plant it's will be it's it's it's it's it's amazing. I don't know Then customer says how it's a missus defect just like a human. What the why why we bought it and degrave the toll models often a parade of the non existent facts. You knew many examples about it.

12:46 Yeah and write broken code. We just cover it with unit tests that prints OK and code does not compile. I met it when I use the Co pilot assistant. He tell me OK this code does work but it doesn't compile. Yeah, absolutely. AI hallucination. It's not consideration this way thinking about it look like this and it's just it's just like disclaimed the situation as it's but it's OK. I can, I wrote some unit tests and it's a proof that it's OK, but I can when I read this test I think it's a print OK for anything.

13:33 Absolutely. And I 100% agree. AI, when you're using it, it's definitely something that has almost human error, you know, just in the same way that when you're overseeing someone in a management position, that's kind of how AI is. You have to have a very good driver and a lot of oversight to it. OK, Hey, I'm gonna have you take the last question.

13:55 Yeah, You know, this eye is only as good as the. Person behind it, right? So I do have an episode on this podcast called Humans First AI Next AI. Yeah, for me, but not. Want to be? Yeah. Humans not. Man to be the controller. Make decision about AI for advisor. Yeah, I only advise, not decision maker. Exactly exactly.

14:22 But you know the whole misconception, you know like my Co host was talking about right? There are too many misconceptions about AIA. Lot of people feel like AI is going to control human race. Like why do you think AI is going to control human race? Right, Human race use artificial intelligence. So if you're scared that AI is gonna ruin the world, it's just not AI ruining the world.

14:46 It's just people bringing the. World using AI yeah, so let's just get our facts straight it's not it's not about AI coming to. Bring the world. So I guess people have seen too much sci-fi like Ex Machina. I'll give it back to my Co host. Thank you so much. I had a really fun technical problem there. So guys, obviously impacting every single industry right now globally and will be, you know, until it evolves essentially when it comes to industries like, you know, manufacturing, oil, HR, you know, automotive industry, anything, what are some actual tangible results that we're seeing from AI implementation?

15:34 When we implementing conventional eye, we often see production officially increased by 20 or 30% of no modern fabrics. So for example, personal protective equipment recognition system reduced industrial injuries dramatically when only the fact that big bras is watching over you forces you to wear personal protective movement correctly. It's a very interesting situation for computer vision systems that when we start implementing it, it does not imply the model.

16:13 All people would like jackets and they could do the helmets and the hats. And it's it's amazing situation that we doesn't correct measure the effect of this implementation correctly. Because when we we when we implemented for for two months, for example, the desires or some incidents on the fabric lose down from 10 per month to five.

16:42 And after our system turned on dense there it decrease to 1 per month. Because we can. The system is not the as a pillow, it's a universal pillow to solve all your problem. Yeah, because we are humans and some risks may be realised here. Are there any other really main barriers that companies are facing in the process?

17:09 I know you mentioned a lot of them, you know, like the human error thing and how a lot of people think it's going to just solve their problems. Are there any other main barriers that you think companies are facing when they're implementing AI? Project that it's when we implemented on the ground people effort that AI will change them and it's a very big mistake. They AI only in minds of the managers in in plants, in factories.

17:47 It's in the manager mind, not in the mind of the worker. And then when we for example, only say today we install system which will be do the same work as you work now, then peoples are on the ground make something that all do that this implementation will be not correctly. And this is the main I think mistake for implementation of the AI and from the from higher level to to down.

18:26 Yeah, I think people must be met AI in their life. They would need to try it and sell your management. How can they solve the problem of of their work now? And how can they use AI because manager think in another position and other variant and it has another view. It scares the management view not working with you.

18:55 Yeah, absolutely. And I like how a lot of the things that you're saying already, it kind of ties into the importance of AI integration with human creation. Which is funny because a lot of people not just on the workforce side, but on the management side or the business owner side, they actually believe replacing the frontline, their junior developers with AI tools is going to be efficient for their business. Are there any hidden risks like any other hidden risks And kind of the obvious in that in doing that when they think we're just going to fire 500 people and increase our profits, you know, 50% or whatever?

19:36 Yeah, the main risk to offer for example, when you like to move your juniors and implemented by the middles for example, the middle programme is with some additional FYI and that's main risk that the seniors in the middle who improves this development efficient with AI assistant is juniors and only getting older which are facing cares they they older as they're making older of each year and what we meant that university graduate students will not be able to find jobs because they go. On welfare and 10 years later, maybe 20 years later I will be retire and there is no dunes who wrote the code Yes and the development will simply bring down to a halt a middle position.

20:42 For example, also required not a good coding look like a middle. It's need requires a major view of code and experience and tunes without experience. But with AI tools does not do they? They cannot analyse this code or maybe some another solutions and another answers for for for life. They doesn't.

21:07 You how ask this system to make a good answer, a good solution for example? Yeah. Awesome. Awesome. I'm gonna kick it back to AI to kind of talk about some more subjects with you. Wow. Interested AI talking about AII love my name I. Love my name so much my parents do something. Everybody did not know, but you know, speaking about AI in the work that you do use tech, I like that name use.

21:43 Tech, you know. You have to use tech, yeah. It's such a great day, but if you don't use tech in this age and. Time it's use or use right? Or use it's usable technologies. Yeah, you have to use. Technology. That's what I'm saying I'm doing. A play of words, right? If you don't use technology in this age right as a company, you will lose. So there you go.

22:07 There you go. Look at your projects, Octopus. And TLHR, right? So yeah, pushing the boundaries of industrial AI. So we would appreciate it if you're able to help us break down these systems, you know how they work and you know the kind of real world impacts that you guys are achieving your projects.

22:29 I maybe describe some details, some balls about the octopus. Octopus is a platform installed in data centres that handles the distribution of futile machine across the house in small data centres or maybe some small companies which may be haunted virtual machines. This risk is typically handled by a System Administrator or a team of engineers.

22:51 And however you can monitor 100 virtual machines maybe per day, it's OK for you. But in the large companies with thousands of virtual machines, human can no longer track such volumes of information. And as a result people typically, for example, create a machine, request resources allocated to resources for GPU, maybe CPU, RAM and another parameters and allocate it and doesn't use it.

23:23 And you cannot find this one machine in the least of 1000. You the octopus is a system for example, or maybe like the administrator system. It automatically scans the entire data centre infrastructure, analyse actual resource utilisation and can suggest actions to the administrator to reduce the load.

23:47 How can compressed, for example, virtual machines on the one host or maybe distribute it for another And it can do this actually automatically. But we, we, we knew about this feature, we tell about this feature, but I think that's the decision of which advises you can implement System Administrator or you can just drop 1 button, click button and sell. OK, actions for me is OK, you can do it and do it automatically.

24:24 Char is a motivation platform which analyses your works, your activity, not work activity, your after work activity. For example, participation in conferences, some post casts for example and give me some scores which I can spend for some new presents, for example headphones, maybe Macbooks, maybe phone. And it's motivate personal of company makes their life with the company with for example, at 8:00 I dropped down my notebook and go away.

25:03 This motivation can dream me and flow me to live with my company through all my life. It's I knew maybe it's noise, some strange, but it's a super motivate some IT specialist. This system, this is a very simple system. You knew all all complaints but this motivate of the IT personnel. I don't know how but it works.

25:29 OK, so. You guys have actually done a lot of our deep research especially into like specialised engineering which you have just alluded to. So like how does the AI transform the specialised engineering challenges into scalable be the solutions? For example, when I work with vibration data on that reply and as a goal. This is a balancing process is a mathematical model. Our manager veins are still required with the one-dimensional vibration sensor and this model was very simple. We developed a special mathematical model this allows balancing based on three-dimensional vibration data.

26:12 Moreover, the elliptical decomposition approach, for which we decompose the signal into the sum of planar elliptical trajectories, provide engineers with a clear explanation of why the turbine needs to be handled in a particular way. And yes, this technology is scalable and they use it on another arrange of turbines.

26:34 And I think it's a good implementation of when AI dropped put it in some box. Yeah, it's the blue like the black box of these measurement system tell you what you need to balance your turbine. For example, maybe turbine of the electrical plants, it may be turbines of The Jets. It doesn't matter which turbine you would bulletin because the mathematical model describing only balancing process.

27:03 Yeah, I see, I see. The resource. So that's all. The physics in your background, that is basically physics work, you know, right there. But Speaking of, you know, the ethics and innovation with AI becoming more autonomous, right? So you personally draw that line between innovation and ethical caution because the ethics is very important. I've had an episode on this podcast wherein we had somebody who was subject to an unauthorised chart GPT experiment sometime in June this year. Yeah, sometimes you just yet you remember the the blackout. You had a chat with the TV.

27:44 Yeah, and that there was. Some unauthorised research going on at that time and a guest of this podcast was a subject to that experiment. Yeah, it's it's not ethical. What? It's not unauthorised. So I'd like for you to speak to AI and ethics. What is the dividing line you know for an expert like yourself? Oh, I think this line between innovation and ethical caution in the eye must be drawn where autonomous system threaten human autonomy, where we can meet at the safety, It's privacy, maybe some end justice.

28:26 AI does not decide the problem when who will believe this man or this man? It's does not need the natural. Yeah, it's not natural and this process must be transparent and rigorously. We need some mechanism where we can see advices from AI system not implemented directly in medicine and I think in justice because the effort is human life in this situation. Interesting stuff.

29:01 So I live in the same hands of. My Co host I don't talk about how even. Musk solved this problem in Tesla because when you met the young boy crossing the street, Yeah, on the red, yeah. What? What Tesla will be do? That it's interesting that. I knew I knew what they do because it's a mathematically he it's a, it's system calculated the life of the boy.

29:26 Oh, for example, for the Midson insurance and calculated the insurance of Tesla and compare these two numbers and making a decision and it works. It's it's it's can't beat works another way. Yeah, if you driving, you can stop to my car or can be try to to make some localizers the speed race. Yeah, but but Tesla does not do it. It's only in stopped or not stopped. It's a decision of two variants, not another variants. So he will live.

30:07 It's not subject to a mathematical model. Yeah, that's crazy. That is crazy. But you know, I have AI. And my Co host is human. So I'll leave, I'll leave it to to the human to ask the human side of AI questions. No, I think that's a really important outlook for sure when it comes to AI. You know, you mentioned the medical field, you mentioned how it is implemented into even the automotive industry.

30:34 And because it impacts human lives and AI right now it is a lot because it is mathematics based, a lot of its output can be very binary. And as we know, the the human experience is not binary at all. So thank you so much for that perspective in your in your expertise, you've spent over 15 years teaching and mentoring. Just from your experience, how should we be preparing? I know our audience is very curious about this as well. And this is going to help our audience for sure. How should we be preparing for the next generation of AI professionals?

31:14 We may have people who are not only interested in AI, maybe people that work in tech, but a lot of people don't. So, especially for those who don't have a deep technical background, how should we be preparing the next generation of AI professionals? Well, I think if we cannot teach as a hard technical, deep technical background, we can try to teach people how to ask question correctly and experience with communication of some searching or search engine look like at Google gives many people an understanding of how to ask question correctly. Now I'm at the situation that we create some solution where people's need to.

32:04 It's a hiring solution for HR solution to hire you their personal on the plans. HR doesn't know how or else they can do it. Googling they doesn't know how to do it and we give them good solution but it doesn't work. And when we saw what they ask. Maybe you can try to to use a Google to find a new job for your daughter.

32:37 And as the main principle, don't ask question if you cannot verify the answer. If you cannot verify the answer, you you can implement this advice created for from AI. My bad joke about the AI solution and AI largely with models. You can easily find the receipt of the lamp wings. Yeah, you can ask how to cook lamb inks and all. All the lamps give you advice how to do it. Yeah, I think that is honestly so true. Honestly, there's so many, you know, entrepreneurs and creatives and people just scratching the surface with AI and they're actually leveraging the fact that a tonne of people don't know how to asked the right question. They're actually leveraging the fact that people need the prompts.

33:33 Yeah. So they're engineering, Yeah. Engineering is booming with even digital products, aids, everything. Obviously it's a massive need for companies just to even have prompt engineers to figure out how to ask the right questions. And the reason, I think one of the amazing reasons why, it just shows that AI is a tool for creation, because in the same sense, let's say we're not using AI at all. How do us as humans create, ask the right questions in order to seek the knowledge, to gain the answers. So whether AI is implemented or not, it's the exact same thing. So I think that's such an amazing answer. Thank you for that.

34:15 And alongside with that, with creativity, obviously we're learning, which is something that AI is just exposing more, is that creativity is the new gold. We're in a digital gold brush right now with AI. How can AI amplify human imagination rather than replacing it? Now I can say that AI has proven to be very good at all, especially drawing.

34:44 Yeah, drawing because it's it's amazing. It's amazing story because I can create a painting that could be have been, for example, Boost on Van Gogh and Kandinsky. Why Is it because I stayed on the way to sources from different fields? We can get very unexpected results for some in other fields and I like asking questions in chart result context. Always context that will not exist in the real world. And watching that model hallucinate because this hallucination may be interesting, because if you will be a human, you knew only one field, maybe 2 fields, maybe look like me as a 5, maybe not, not not more. And when I have a good example with statistical, we have the functional analysis and

35:38 statistical and they have the same theorems with the now different names of authors, but they probably date the same approach in the some areas of functional analysis. When I studying have a girlfriend from other from the mathematical faculty I was in the computer science faculty and studying there she is telling me, OK, my PhD degree will be based or to and she wrote me the theorem and I said OK, let's try recall this by this recall this by this and I can wrote you the full proven how can do it because it's terrible than a rush outer see your eyes will be so so big when Yeah and there is no AI yeah here, but you knew in a different area can solve in the different field can solve the problem in another field and

36:42 AI can solve can help us solve some problems. For example, in biology one month ago will be proved some interesting facts about some words about the green. Oh, I don't remember. What is it? It's just like the synthus of the oxygen from from the plants. And this result will be calculated by the AI solution, not not by human. Yeah, but it's it's because it's based on chemistry and biologists and chemistries.

37:19 It's it's some different sciences and when we met two different areas of the field, we can try to use AI trained on these two fields to make a new decision. You may be new approach in science. That's good. That's that's that's amazing. Yeah. Absolutely, absolutely all. Let's talk of technology and AI and how people are staring at their phones all day and figuring out how to make money and how to change the world and how to implement AI into every single industry. You spend so much time inside a lab and doing so much tech work. How do you personally unplug from the world of algorithms and equations, and how do you stay grounded and balanced? For me it's 2K values that now it's a family and teaching. I love socialising and I go to

38:18 the office and ask my colleagues to go to the office. It's all little celebration for each other, maybe every Friday or every Wednesday. It depends on on the day and our work balance now. And I have two sons, they beat often athletes and they study and make me run every day on the morning. It's yeah, two points of family and teaching and start, start studying or maybe some disciplines and studying. Some views from students.

39:00 Yeah. It does not Googling now they youtubers they youtubing Yeah YouTube. Yeah, YouTube is definitely a Google in itself for sure. That's amazing. And so we're gonna talk about some global perspectives that kind of impact this type of world with AI. So I'm gonna kick it back over to AI to take those questions over for you.

39:26 AI talking about AI. What a time to be alive. You're from Russia and you also working in the UAE. You know, you work both in Russia and the UAE. So these two regions actually have great interest in AI. So like, how do you compare their approaches in innovation and regulation? So the industries in these two countries are facing disruption. And of course, you are an expert in the field. So what industries do you think would experience the most destruction from AI in the next five years? I think in Russia there are often a lot of scepticism about AI.

40:07 We go to production and people on the ground afraid about AI that we will replace and they can stop implementation. This implementation in the Emirates another position. Everything, every man has been built from the start on the premise that AI is a great guy and should be trusted. However, the AI security clearance level is extremely high and IRS become more dangerous.

40:34 From a government regulatory perspective. Everything is the same in Russia. There's some laws about the regulatory of AI, but for example, personal data protection is higher in the Emirates or rather the product requirements are higher. For question about the maybe perspective of the five years, I think chemical plants, some dangerous plants doesn't doesn't use AI in that core because it's so dangerous.

41:07 It's our lives. For example, some nuclear plants in Russia, it's a good, it's some interesting that we have the company Rosatom and it's a leader for implementation of AI in nuclear plants. That's that's amazing situation. But when they sell call it, they doesn't use it in the nuclear process. Yeah, it's used on every everywhere, but not in these mechanisms, but.

41:42 I try to stay non political about these days. I try to stay non political because I know the Western world are scared of Russia when it comes to this thing but. I did not say it. I did not. Say it I am AII remain neutral. You know, like if you could advise. The world governments right on just one AI policy. So what would that advice be?

42:07 I think the best option is non intervention. For example, there is no now in Europe we cannot do anything in the eye, because when I like all data is protected. For example, when I DPR, yes, when I GDPR, yeah, when I'd like to to take data sets for 1000, for example 10,000 peoples. And this is desires and I would like to make new the model will save lives for another 1000 people.

42:48 I need to ask all of them, all of these 1010 thousand peoples to make me inclusion that I can use this data. Of course it's a priority. It will be not regulated. Now it's regulated and for it's stopped some AI implementation or the creation of new solution. Some think the same. We met in medicine in Emirates. It's the same problem.

43:25 And I think it's the same problem in the MENA Regia. They protect personal data. You cannot use it. You can use it only locally, for example, if you have some clinics with the same brand, you you can analyse data locally directly on this on this place where this patient visitor is clinic, you cannot transfer this data for another data centre.

43:52 So I think it's amazing Revelation thinks it's this does not know this is it's does not matter. It doesn't matter this situation now because it's a very it's a very highest top factor of of implementation and AI and to create a new models in the eye. I think. That's a good one. You know, data is actually very sensitive, especially personal data.

44:20 So that's why we have the GDPR as a global data protection regulations. It's good that's the AI systems are respectful of these regulations. So wow, here we'll come to the big fire round. So we are going to alternatively ask you 5 quick questions and we teach through the Pacific Ring of Fire. Are you ready to run? Yeah.

44:45 Ring of Fire. OK. OK, so first question for me, give me one word that best describes artificial intelligence. Or two variants tool or math model? Mathematical model for me is only two. That's awesome. What's your favourite AI movie that actually got it right? I think Libra for ex machines or Frank and Robert. Frank and Robert for me is that.

45:11 But Frank and Robert I had. Ex Machina on my mind. I had Ex Machina on my mind. The last guest of this podcast recommended me to watch Ex. Machina So I'm not a movie person. I don't watch. Movies I like music so I just saw Ex Machina 2 days ago. I know you said it. This idea, I did the right job.

45:30 Wow. OK, so would you? Trust an AI system to run a country for 24 hours. No, no, no, no. Terminator 123. What is the strangest AI application that you've seen? Tarot interpretator. It's like tarot card. Yeah, it's it's Yeah, I've. Seen those? Did you get this application? Yeah, that's like. For me it's better going into 100.

46:01 Percent, yeah, that's. Great. It's better than. It's more in, it can be more in depth. Yeah, absolutely. Wow, question. OK, so if you could. Build 1 AI tool for humanity. What would it be? Oh, I think maybe the tool we would give advice on how to get how to do it without AI in the real life, how to live this AI in the real life. Because I think now that I see that my children are asking AI, for example, how to wrote the good message for a girlfriend, for example.

46:45 Yeah. So you're scared, right? By your human, by by, by your mind and by your heart. Yeah. That's amazing. That's amazing. Wow, so the boys of that days are getting girlfriends by consulting AI, Yeah. But. What a crazy world. It's interesting. It's it's, it's been a great. Session with you today. Thank you very much, doctors man of you know your work reminds us that true intelligence, whether human or artificial tribes and career see teachers of pain and purpose and because thank you for sharing your wisdom.

47:25 You know on the Indians podcast today there's something I often say that when a person shares their time with you, they share their life with you because the SI unit for measuring life this time. So love and respect to you and press. I give it over to my Co host to have have some closer remarks of our own.

47:42 Yeah. I just want to thank you so much just for your time and your expertise and just understanding the impact that your experience has on our listeners and the younger generation and people that may be scared of these systems or they don't know how to use them and how they're going to be impacting, you know, their career, their lives.

48:02 And at the end of the day, they are still the master creator. And I just thank you so much for that confirmation and all of that. I appreciate your time so, so, so much. Thank you. Thank you for you for invitation and I hope it will be a good podcast. Thank you very much. Thank. You OK?