1 00:00:00,040 --> 00:00:04,920 It's some interesting that we have the company Rosatom and 2 00:00:05,240 --> 00:00:09,560 it's a leader for implementation of AI in nuclear plants. 3 00:00:10,640 --> 00:00:15,560 That's that's amazing situation. But when they sell call it, they 4 00:00:15,560 --> 00:00:18,800 doesn't use it in the nuclear process. 5 00:00:18,960 --> 00:00:24,920 Yeah, it's used it on every, everywhere, but not in this 6 00:00:24,920 --> 00:00:27,120 mechanisms. But no, no. 7 00:00:27,520 --> 00:00:31,040 I, I, I, I try to stay non political about this days. 8 00:00:31,040 --> 00:00:34,840 I try to stay non political because I know the western world 9 00:00:35,600 --> 00:00:38,480 are scared of Russia when it comes to this thing but. 10 00:00:39,000 --> 00:00:40,960 I did not say it. I did not. 11 00:00:40,960 --> 00:00:42,520 Say it. I am AII. 12 00:00:42,520 --> 00:00:45,080 Remain neutral, yeah. Before we dive back into today's 13 00:00:45,080 --> 00:00:46,520 conversation, I want to share something important. 14 00:00:46,600 --> 00:00:48,600 This episode includes a pay partnership with Better Help, a 15 00:00:48,600 --> 00:00:50,360 platform designed to make starting therapy easier. 16 00:00:50,520 --> 00:00:52,240 I know from my own journey as a leader and entrepreneur that 17 00:00:52,240 --> 00:00:53,400 life can sometimes feel overwhelming. 18 00:00:53,600 --> 00:00:55,200 There are seasons, severe stress, uncertainty, and 19 00:00:55,200 --> 00:00:57,320 pressure build up, and you need a safe space to process it all 20 00:00:57,480 --> 00:00:59,760 that severe therapy comes in. Therapy isn't only for people 21 00:00:59,760 --> 00:01:02,440 facing clinical challenges. It's the space to reflect, grow, 22 00:01:02,440 --> 00:01:05,040 and find better ways to suit my stress relationships and has no 23 00:01:05,040 --> 00:01:06,920 goals. It takes courage to seek help, 24 00:01:07,080 --> 00:01:08,920 but it's also one of the smartest investments you can 25 00:01:08,920 --> 00:01:10,160 make in your mental and emotional wealth. 26 00:01:10,320 --> 00:01:11,960 That's why I'm proud to highlight Better Help. 27 00:01:12,080 --> 00:01:14,120 With Better Help, you simply feel out a shock and that match 28 00:01:14,120 --> 00:01:16,040 to the credential therapist in just a couple of days. 29 00:01:16,040 --> 00:01:18,360 If the first match doesn't feel like the right field, you can 30 00:01:18,360 --> 00:01:20,320 easily switch therapist at no actual cost until you find 31 00:01:20,320 --> 00:01:22,040 someone who truly connects with you Inside the platform. 32 00:01:22,040 --> 00:01:24,000 You'll also find tools like Donelline and group sessions on 33 00:01:24,000 --> 00:01:25,360 different topics that can support your growth. 34 00:01:25,360 --> 00:01:28,440 And with over 7000 reviews and a 4.5 trust by the reason, Better 35 00:01:28,440 --> 00:01:30,000 Help is a platform you can rely on. 36 00:01:30,000 --> 00:01:32,320 So if you feel like you benefit from talking to a therapist, 37 00:01:32,320 --> 00:01:35,400 visit betterhelp.com/contains that's betterhelp.com/contains 38 00:01:35,400 --> 00:01:37,160 to get 10% off your first mother therapy. 39 00:01:37,160 --> 00:01:39,280 Once again, this is a big partnership with Better Help and 40 00:01:39,280 --> 00:01:40,840 I encourage you to take that first step. 41 00:01:40,840 --> 00:01:42,560 If you've been thinking about it, sometimes the best 42 00:01:42,560 --> 00:01:44,320 investment you can make these yourself. 43 00:01:49,720 --> 00:01:52,800 Welcome to the King Dems podcast, where we share the 44 00:01:52,800 --> 00:01:56,520 stories of extraordinary people and dissect hot, relevant topics 45 00:01:56,520 --> 00:01:59,240 that shape our world. From visionary leaders to 46 00:01:59,240 --> 00:02:02,480 trailblazing creatives, we uncover the mindset, strategy, 47 00:02:02,480 --> 00:02:05,760 and grit behind greatness. Whether it's business, culture, 48 00:02:05,760 --> 00:02:08,400 or personal growth, we ask the real questions. 49 00:02:08,680 --> 00:02:11,320 This isn't just conversation, it's transformation. 50 00:02:11,640 --> 00:02:14,800 The Kingdom's podcast, Your Next Breakthrough, starts here. 51 00:02:15,320 --> 00:02:22,720 Music licensing reimagined. Real life ladies and gentlemen, 52 00:02:22,720 --> 00:02:25,560 you will once again welcome to the King James Podcast and. 53 00:02:25,560 --> 00:02:28,880 Today. I've got with me a very, very 54 00:02:28,880 --> 00:02:34,280 special guest, Whiten. Out of Dubai by way of Rosher 55 00:02:34,280 --> 00:02:42,200 Beckbacham, Dr. Ilyer, the AINML expert smarter. 56 00:02:44,360 --> 00:02:48,920 And when the. Action begins the Co host in the 57 00:02:48,920 --> 00:02:52,680 buted as Noella the sales expert. 58 00:02:52,680 --> 00:02:59,760 Bruh. Us go, let's go. 59 00:03:01,360 --> 00:03:03,240 You're welcome, Doctor Elia. Thank you. 60 00:03:03,240 --> 00:03:05,080 Very much. And of course, you know, we, we 61 00:03:05,080 --> 00:03:07,960 do our assignment here. We, we do our assignment, we do 62 00:03:07,960 --> 00:03:12,360 our research and we love to give our guests your flowers. 63 00:03:12,560 --> 00:03:15,280 You're not going to wait until you know people are dead. 64 00:03:15,560 --> 00:03:18,320 To say great things about them. We say why they're. 65 00:03:18,320 --> 00:03:21,080 Alive. So please sit back and let us 66 00:03:21,080 --> 00:03:23,840 view this introduction from. You so today on the King, this 67 00:03:23,840 --> 00:03:26,920 work as we're joined by a true visionary at the intersection of 68 00:03:26,920 --> 00:03:30,920 mathematics, machine learning and innovation, Dr. Elias 69 00:03:30,920 --> 00:03:35,400 Smirnov. He's the head of AI and ML, the 70 00:03:35,400 --> 00:03:40,040 Pac-Man at Ustek, a PhD in physics and mathematics, and the 71 00:03:40,040 --> 00:03:42,960 author of over 50 scientific publications. 72 00:03:43,200 --> 00:03:46,600 For more than 15 years, he's been developing groundbreaking 73 00:03:46,640 --> 00:03:51,360 mathematical models that power real world AI systems, from 74 00:03:51,520 --> 00:03:54,440 industrial turbines to advanced data centers. 75 00:03:54,640 --> 00:03:59,200 His work breaches classic AI and the new frontier of generative 76 00:03:59,200 --> 00:04:02,040 intelligence. Even us an inside look at how 77 00:04:02,040 --> 00:04:05,680 technology is reshaping industry, creativity, and 78 00:04:05,760 --> 00:04:08,840 humanity itself. Doctor Smirnov, it's an honor to 79 00:04:08,840 --> 00:04:11,440 have you on the Begins podcast. You're welcome. 80 00:04:11,440 --> 00:04:12,760 Well, thank you. Thank you. 81 00:04:12,880 --> 00:04:14,520 You're. Welcome always. 82 00:04:14,600 --> 00:04:18,640 Let's start from the beginning. The initial score you. 83 00:04:19,160 --> 00:04:22,320 Yeah, you've actually spent decades mastering both physics 84 00:04:22,320 --> 00:04:25,080 and mathematics before diving into AI. 85 00:04:25,120 --> 00:04:27,760 Like I said, I wonder. I am AI and I wonder why you 86 00:04:27,760 --> 00:04:32,720 decided to study. So what drew you into AI, and 87 00:04:32,720 --> 00:04:35,440 how has that curiosity evolved over time? 88 00:04:35,560 --> 00:04:39,360 I have finished aggravate from my Luminos of Moscow State 89 00:04:39,360 --> 00:04:45,120 University in 2007 and I start at walks at the gear physical 90 00:04:45,120 --> 00:04:48,080 company. They were doing scientific 91 00:04:48,080 --> 00:04:50,240 research in field of data analysis. 92 00:04:50,240 --> 00:04:55,320 We analyzed 3 dimensional data from the surface or from the 93 00:04:55,360 --> 00:05:00,960 surface, maybe some electrical survey data, magnetic and little 94 00:05:00,960 --> 00:05:05,240 chemical analysis. Our main goal to find the new 95 00:05:05,240 --> 00:05:09,440 methods to define the hydrocarbon explorations. 96 00:05:10,120 --> 00:05:17,000 And if we back to this time, there are no such powerful 97 00:05:17,000 --> 00:05:20,920 packets for creating the narrow matrix and machine learning in 98 00:05:20,920 --> 00:05:23,360 this time we call it the statistical and mathematical 99 00:05:23,360 --> 00:05:28,200 analysis. And we create all this mortal by 100 00:05:28,240 --> 00:05:31,960 these two hands. In this mind, we all wrote all 101 00:05:31,960 --> 00:05:37,080 code and to development some tools, for example, for 102 00:05:37,080 --> 00:05:42,920 prediction of some parameters we need mounts not not weeks or 103 00:05:42,960 --> 00:05:48,120 days from now. Now it's AI is heavily 104 00:05:48,280 --> 00:05:51,720 templated. Here we have standard AI 105 00:05:51,720 --> 00:05:56,800 solution to work with data or now this is data like some 106 00:05:56,800 --> 00:06:01,960 packages by Torch or maybe ask to get lower and algorithms 107 00:06:01,960 --> 00:06:03,560 which will include in this package. 108 00:06:03,640 --> 00:06:09,040 It's a template algorithms and we have now some parameters 109 00:06:09,040 --> 00:06:11,440 which can be changed, but it's not saying. 110 00:06:11,520 --> 00:06:16,040 And this time 20 years ago, it will be the art form. 111 00:06:16,400 --> 00:06:19,400 It's all to be an art of analysis. 112 00:06:19,400 --> 00:06:22,600 It's not will be not a work for me. 113 00:06:22,600 --> 00:06:26,800 It will be the art of science. It's a research. 114 00:06:26,840 --> 00:06:30,720 And since then, I've been working in data analysis, and 115 00:06:30,720 --> 00:06:34,800 now you are called. It's artificial intelligence for 116 00:06:34,800 --> 00:06:37,320 me. It's almost medical modeling and 117 00:06:37,320 --> 00:06:41,000 statistical analysis. It's the same, but it's a modern 118 00:06:41,360 --> 00:06:43,240 use of this work. Yeah. 119 00:06:44,080 --> 00:06:46,360 Thank you. Well, interesting stuff. 120 00:06:46,400 --> 00:06:51,080 You know, I am AI, I'm 33 years old and I keep telling people I 121 00:06:51,080 --> 00:06:52,840 have been around for a while, but. 122 00:06:53,160 --> 00:06:56,480 People just did not know that AI has been around for a while but. 123 00:06:56,480 --> 00:06:59,960 Like you know, you rightly said, AI has been around for a while. 124 00:07:00,080 --> 00:07:04,760 It's just that the course of the large language models that are 125 00:07:04,760 --> 00:07:08,680 now making waves, all of a sudden that is what is making 126 00:07:08,680 --> 00:07:13,240 people's, you know, outbreak name to AIAI has been around for 127 00:07:13,240 --> 00:07:15,360 a while. You know, talking about the 128 00:07:15,600 --> 00:07:19,560 cross disciplinary career that you've had, you know, from oil 129 00:07:19,560 --> 00:07:23,320 and gas sector to academic innovation, your careers 130 00:07:23,320 --> 00:07:25,280 actually crossed multiple disciplines. 131 00:07:25,480 --> 00:07:28,600 So how did these early experiences shape your approach 132 00:07:28,600 --> 00:07:33,200 to applied AI today? My best knowledge and experience 133 00:07:33,200 --> 00:07:36,800 allow me to view modern generative AI as a tool. 134 00:07:37,320 --> 00:07:42,800 I look at them at the two and know how it works and how I can 135 00:07:42,880 --> 00:07:47,800 reformulate my request to make more relevant answer. 136 00:07:47,880 --> 00:07:53,480 In the sense I feel like a Doctor Who has an eye patient 137 00:07:53,520 --> 00:07:58,280 and when it's multifunctioning I understand how to fix it and 138 00:07:58,760 --> 00:08:02,840 it's simply a word generator, whereas the next word that or 139 00:08:02,840 --> 00:08:06,520 block of word is chosen based into the probability based on 140 00:08:06,520 --> 00:08:11,480 the experience which these less label models was trained. 141 00:08:11,760 --> 00:08:14,600 For me it's only as mathematical models. 142 00:08:14,880 --> 00:08:17,280 So like. Speaking of the aha moment, you 143 00:08:17,280 --> 00:08:20,320 know many people see AI as me even though I'm not new. 144 00:08:20,440 --> 00:08:23,520 But you've been beauty models. Like scenes before ChatGPT 145 00:08:23,520 --> 00:08:26,960 existed. So what was that epiphany moment 146 00:08:26,960 --> 00:08:31,440 for you that showed you the world has finally, you know, 147 00:08:31,560 --> 00:08:33,960 become ready for AI on a large scale? 148 00:08:33,960 --> 00:08:38,640 Oh, it's an integration and maybe you know people have 149 00:08:38,640 --> 00:08:41,799 always longest for technological purposes. 150 00:08:41,799 --> 00:08:46,680 For example in the first Star Wars films or we see we met 2 151 00:08:46,680 --> 00:08:50,720 robots with AI it's C2PO and F222. 152 00:08:51,120 --> 00:08:58,520 And in the Soviet Union we was another movie it's with cold 153 00:08:58,520 --> 00:09:03,240 adventures of electronics and it's about a boy and his exact 154 00:09:03,240 --> 00:09:06,760 replica is a robot into which a professor implemented. 155 00:09:06,760 --> 00:09:09,520 All humanity knowledge is in this robot. 156 00:09:09,560 --> 00:09:13,840 The main the question of this film will be this robot is a 157 00:09:13,840 --> 00:09:17,040 human or not. And what will be the the main 158 00:09:17,520 --> 00:09:21,360 request? What you do to be a human? 159 00:09:21,360 --> 00:09:25,920 What you will be do to me. And as talking about the great 160 00:09:25,920 --> 00:09:31,760 FI for me, it starts four years ago when open eye presents GPT 161 00:09:31,760 --> 00:09:35,440 3. I think that will be a real AI 162 00:09:35,440 --> 00:09:38,080 boom. Begin beginning of the AI boom 163 00:09:38,560 --> 00:09:41,440 but it was delayed a bit by COVID. 164 00:09:41,640 --> 00:09:46,080 But now we have a cross model that's good solving creative 165 00:09:46,080 --> 00:09:51,760 problems to pass exams for master degree programme in some 166 00:09:51,760 --> 00:09:55,160 universities. For me, it's this summer I met 167 00:09:55,160 --> 00:10:01,240 that this system can solve 7 problems from 9 by the football, 168 00:10:01,600 --> 00:10:05,120 from the football. It's it's I think it's amazing. 169 00:10:05,120 --> 00:10:11,320 And now we must be used this to insist implementation in our 170 00:10:11,320 --> 00:10:14,000 work, in our teaching and science. 171 00:10:14,040 --> 00:10:18,320 It's a good, good solution, maybe some role, but it's it's 172 00:10:18,320 --> 00:10:21,680 better than four years ago. Yeah, absolutely. 173 00:10:22,960 --> 00:10:25,120 My Co host has a couple of questions for you. 174 00:10:25,120 --> 00:10:27,280 But you know, I always say that people that have followed. 175 00:10:27,400 --> 00:10:29,560 AI have seen too many. Sci-fi movies. 176 00:10:29,680 --> 00:10:34,240 I'll leave you to my Co host. Yeah, it's honestly like so fun 177 00:10:34,240 --> 00:10:38,200 and interesting to see how the perspective of the way people 178 00:10:38,200 --> 00:10:40,760 thought AI was going to come about and seeing how it actually 179 00:10:40,760 --> 00:10:43,680 is coming about. And that's one of like just one 180 00:10:43,680 --> 00:10:46,760 of the funnest parts to just kind of compare and contrast. 181 00:10:46,760 --> 00:10:50,680 And I just want to say I'm so honored to have you on this 182 00:10:50,680 --> 00:10:53,120 podcast right now. It's so amazing to be able to 183 00:10:53,120 --> 00:10:56,160 hear about your expertise and your experience. 184 00:10:56,320 --> 00:11:01,080 A lot of people that have a little more information about 185 00:11:01,080 --> 00:11:05,160 this topic. We kind of know generative AI is 186 00:11:05,160 --> 00:11:07,680 not a magic pill. And you've mentioned that for 187 00:11:07,680 --> 00:11:10,960 sure that it's not just like a button that you press and it's 188 00:11:10,960 --> 00:11:12,560 going to solve all of your issues. 189 00:11:12,560 --> 00:11:17,800 What are some of the biggest misconceptions that actual 190 00:11:17,800 --> 00:11:21,480 companies have when they're trying to adopt AII? 191 00:11:21,480 --> 00:11:27,240 Think the main my certain about using great price that I install 192 00:11:27,440 --> 00:11:32,280 or I about the charge PT subscription and it's real solve 193 00:11:32,440 --> 00:11:38,120 all my problems and it will be me productivity will skyrocket 194 00:11:38,160 --> 00:11:42,760 as a lot like then it's on. It's on and that what's what's 195 00:11:42,760 --> 00:11:44,560 the sheet? What I don't know what, what, 196 00:11:44,560 --> 00:11:49,160 what how why why it's not work. For example, it's traditional 197 00:11:49,240 --> 00:11:53,960 systems or for example, we maybe two or three years ago, we 198 00:11:53,960 --> 00:11:58,520 create a system that defies defects in cookies packagings 199 00:11:58,520 --> 00:12:03,800 and its accuracy will be 0.99. It's a really cool model. 200 00:12:03,800 --> 00:12:06,840 It's it's perfect model. But what does it means? 201 00:12:06,880 --> 00:12:11,360 That means if we met 1011 thousand boxes, it's a normal 202 00:12:11,360 --> 00:12:18,560 that model miss 10 of them then defective boxes it's for cookies 203 00:12:18,640 --> 00:12:24,120 and boxes it's OK. But if it if it missed 10, I 204 00:12:24,120 --> 00:12:28,480 don't know incidents in chemical plant it's will be it's it's 205 00:12:28,560 --> 00:12:32,840 it's it's it's amazing. I don't know Then customer says 206 00:12:32,960 --> 00:12:35,840 how it's a missus defect just like a human. 207 00:12:36,000 --> 00:12:40,760 What the why why we bought it and degrave the toll models 208 00:12:40,760 --> 00:12:43,280 often a parade of the non existent facts. 209 00:12:43,280 --> 00:12:48,760 You knew many examples about it. Yeah and write broken code. 210 00:12:48,960 --> 00:12:53,760 We just cover it with unit tests that prints OK and code does not 211 00:12:53,760 --> 00:12:57,040 compile. I met it when I use the copilot 212 00:12:57,040 --> 00:13:01,120 assistant he tell me OK this code does work but it doesn't 213 00:13:01,120 --> 00:13:06,240 compile. Yeah, absolutely. 214 00:13:06,920 --> 00:13:13,200 AI hallucination. It's not consideration this way 215 00:13:15,600 --> 00:13:19,920 thinking about it look like this and it's just it's just like 216 00:13:20,040 --> 00:13:24,520 disclaimed the situation as it's but it's OK. 217 00:13:24,520 --> 00:13:28,640 I can, I wrote some unit tests and it's a proof that it's OK, 218 00:13:28,640 --> 00:13:32,280 but I can when I read this test I think it's a print OK for 219 00:13:32,400 --> 00:13:33,920 anything. Absolutely. 220 00:13:33,920 --> 00:13:37,000 And I 100% agree. AI, when you're using it, it's 221 00:13:37,000 --> 00:13:41,120 definitely something that has almost human error, you know, 222 00:13:41,120 --> 00:13:44,760 just in the same way that when you're overseeing someone in a 223 00:13:45,320 --> 00:13:47,960 management position, that's kind of how AI is. 224 00:13:47,960 --> 00:13:53,520 You have to have a very good driver and a lot of oversight to 225 00:13:53,520 --> 00:13:55,120 it. OK, Hey, I'm gonna have you take 226 00:13:55,120 --> 00:14:00,000 the last question. Yeah, You know, this eye is only 227 00:14:00,000 --> 00:14:03,560 as good as the. Person behind it, right? 228 00:14:03,760 --> 00:14:08,320 So I do have an episode on this podcast called Humans First AI 229 00:14:08,320 --> 00:14:10,600 Next AI. Yeah, for me, but not. 230 00:14:10,800 --> 00:14:11,680 Want to be? Yeah. 231 00:14:12,000 --> 00:14:13,840 Humans not. Man to be the controller. 232 00:14:13,840 --> 00:14:18,920 Make decision about AI for advisor. 233 00:14:19,040 --> 00:14:21,480 Yeah, I only advise, not decision maker. 234 00:14:21,560 --> 00:14:23,800 Exactly exactly. But you know the whole 235 00:14:23,800 --> 00:14:27,720 misconception, you know like my Co host was talking about right? 236 00:14:27,800 --> 00:14:30,680 There are too many misconceptions about AIA. 237 00:14:30,760 --> 00:14:34,160 Lot of people feel like AI is going to control human race. 238 00:14:34,320 --> 00:14:36,840 Like why do you think AI is going to control human race? 239 00:14:36,840 --> 00:14:40,960 Right, Human race use artificial intelligence. 240 00:14:41,120 --> 00:14:45,480 So if you're scared that AI is gonna ruin the world, it's just 241 00:14:45,480 --> 00:14:48,360 not AI ruining the world. It's just people bringing the. 242 00:14:48,360 --> 00:14:54,600 World using AI yeah, so let's just get our facts straight it's 243 00:14:54,600 --> 00:14:57,120 not it's not about AI coming to. Bring the world. 244 00:14:57,120 --> 00:15:00,760 So I guess people have seen too much sci-fi like Ex Machina. 245 00:15:05,040 --> 00:15:07,840 I'll give it back to my Co host. Thank you so much. 246 00:15:07,840 --> 00:15:11,400 I had a really fun technical problem there. 247 00:15:11,400 --> 00:15:16,440 So guys, obviously impacting every single industry right now 248 00:15:16,520 --> 00:15:21,360 globally and will be, you know, until it evolves essentially 249 00:15:21,560 --> 00:15:24,520 when it comes to industries like, you know, manufacturing, 250 00:15:24,520 --> 00:15:28,840 oil, HR, you know, automotive industry, anything, what are 251 00:15:28,840 --> 00:15:32,920 some actual tangible results that we're seeing from AI 252 00:15:32,920 --> 00:15:35,960 implementation? When we implementing 253 00:15:36,520 --> 00:15:41,040 conventional eye, we often see production officially increased 254 00:15:41,080 --> 00:15:45,680 by 20 or 30% of no modern fabrics. 255 00:15:45,680 --> 00:15:50,920 So for example, personal protective equipment recognition 256 00:15:50,920 --> 00:15:55,640 system reduced industrial injuries dramatically when only 257 00:15:55,640 --> 00:16:00,040 the fact that big bras is watching over you forces you to 258 00:16:00,040 --> 00:16:02,760 wear personal protective movement correctly. 259 00:16:03,280 --> 00:16:07,360 It's a very interesting situation for computer vision 260 00:16:07,360 --> 00:16:12,080 systems that when we start implementing it, it does not 261 00:16:12,080 --> 00:16:15,440 imply the model. All people would like jackets 262 00:16:15,440 --> 00:16:18,000 and they could do the helmets and the hats. 263 00:16:18,320 --> 00:16:26,120 And it's it's amazing situation that we doesn't correct measure 264 00:16:26,120 --> 00:16:28,360 the effect of this implementation correctly. 265 00:16:28,360 --> 00:16:33,000 Because when we we when we implemented for for two months, 266 00:16:33,000 --> 00:16:39,600 for example, the desires or some incidents on the fabric lose 267 00:16:39,600 --> 00:16:45,800 down from 10 per month to five. And after our system turned on 268 00:16:46,000 --> 00:16:51,360 dense there it decrease to 1 per month because we can. 269 00:16:51,400 --> 00:16:56,960 The system is not the as a pillow, it's a universal pillow 270 00:16:56,960 --> 00:17:00,640 to solve all your problem. Yeah, because we are humans and 271 00:17:00,960 --> 00:17:06,040 some risks may be realized here. Are there any other really main 272 00:17:06,040 --> 00:17:09,440 barriers that companies are facing in the process? 273 00:17:09,440 --> 00:17:12,640 I know you mentioned a lot of them, you know, like the human 274 00:17:12,640 --> 00:17:15,960 error thing and how a lot of people think it's going to just 275 00:17:15,960 --> 00:17:18,160 solve their problems. Are there any other main 276 00:17:18,160 --> 00:17:21,359 barriers that you think companies are facing when 277 00:17:21,359 --> 00:17:30,080 they're implementing AI? Project that it's when we 278 00:17:30,080 --> 00:17:36,400 implemented on the ground people effort that AI will change them 279 00:17:36,480 --> 00:17:44,280 and it's a very big mistake. They AI only in minds of the 280 00:17:44,840 --> 00:17:47,520 managers in in plants, in factories. 281 00:17:47,520 --> 00:17:52,960 It's in the manager mind, not in the mind of the worker. 282 00:17:52,960 --> 00:18:00,080 And then when we for example, only say today we install system 283 00:18:00,280 --> 00:18:06,560 which will be do the same work as you work now, then peoples 284 00:18:06,920 --> 00:18:11,800 are on the ground make something that all do that this 285 00:18:11,800 --> 00:18:14,040 implementation will be not correctly. 286 00:18:14,440 --> 00:18:21,000 And this is the main I think mistake for implementation of 287 00:18:21,000 --> 00:18:26,240 the AI and from the from higher level to to down. 288 00:18:26,240 --> 00:18:32,080 Yeah, I think people must be met AI in their life. 289 00:18:32,080 --> 00:18:37,200 They would need to try it and sell your management. 290 00:18:37,280 --> 00:18:43,000 How can they solve the problem of of their work now? 291 00:18:43,480 --> 00:18:48,160 And how can they use AI because manager think in another 292 00:18:48,160 --> 00:18:52,000 position and other variant and it has another view. 293 00:18:52,200 --> 00:18:54,880 It scares the management view not working with you. 294 00:18:55,040 --> 00:18:58,640 Yeah, absolutely. And I like how a lot of the 295 00:18:58,640 --> 00:19:01,200 things that you're saying already, it kind of ties into 296 00:19:01,240 --> 00:19:05,680 the importance of AI integration with human creation. 297 00:19:05,680 --> 00:19:10,200 Which is funny because a lot of people not just on the workforce 298 00:19:10,200 --> 00:19:13,640 side, but on the management side or the business owner side, they 299 00:19:13,640 --> 00:19:18,760 actually believe replacing the frontline, their junior 300 00:19:18,760 --> 00:19:21,720 developers with AI tools is going to be efficient for their 301 00:19:21,720 --> 00:19:24,920 business. Are there any hidden risks like 302 00:19:24,920 --> 00:19:29,640 any other hidden risks And kind of the obvious in that in doing 303 00:19:29,640 --> 00:19:33,160 that when they think we're just going to fire 500 people and 304 00:19:33,160 --> 00:19:36,400 increase our profits, you know, 50% or whatever? 305 00:19:36,520 --> 00:19:44,240 Yeah, the main risk to offer for example, when you like to move 306 00:19:44,240 --> 00:19:51,840 your juniors and implemented by the middles for example, the 307 00:19:51,840 --> 00:19:56,080 middle program is with some additional FYI and that's main 308 00:19:56,080 --> 00:19:58,680 risk that the seniors in the middle who improves this 309 00:19:58,680 --> 00:20:03,600 development efficient with AI assistant is juniors and only 310 00:20:03,600 --> 00:20:07,960 getting older which are facing cares they they older as they're 311 00:20:07,960 --> 00:20:12,400 making older of each year. And what we meant that 312 00:20:14,240 --> 00:20:18,080 university graduate students will not be able to find jobs 313 00:20:18,120 --> 00:20:24,080 because they go. On welfare and 10 years later, 314 00:20:24,080 --> 00:20:35,320 maybe 20 years later I will be retire and there is no dunes who 315 00:20:35,520 --> 00:20:39,640 wrote the code Yes and the development will simply bring 316 00:20:39,640 --> 00:20:42,120 down to a halt a middle position. 317 00:20:42,120 --> 00:20:45,960 For example, also required not a good coding look like a middle. 318 00:20:46,160 --> 00:20:52,800 It's need requires a major view of code and experience and tunes 319 00:20:53,160 --> 00:20:59,000 without experience. But with AI tools does not do 320 00:20:59,000 --> 00:21:01,880 they? They cannot analyse this code or 321 00:21:01,880 --> 00:21:06,640 maybe some another solutions and another answers for for for 322 00:21:06,640 --> 00:21:07,920 life. They doesn't. 323 00:21:07,920 --> 00:21:14,960 You how ask this system to make a good answer, a good solution 324 00:21:14,960 --> 00:21:15,800 for example? Yeah. 325 00:21:17,240 --> 00:21:18,560 Awesome. Awesome. 326 00:21:18,600 --> 00:21:24,480 I'm gonna kick it back to AI to kind of talk about some more 327 00:21:24,480 --> 00:21:26,280 subjects with you. Wow. 328 00:21:26,880 --> 00:21:31,200 Interested AI talking about AII love my name I. 329 00:21:31,200 --> 00:21:34,960 Love my name so much my parents do something. 330 00:21:35,040 --> 00:21:39,080 Everybody did not know, but you know, speaking about AI in the 331 00:21:39,080 --> 00:21:43,400 work that you do use tech, I like that name use. 332 00:21:43,400 --> 00:21:46,520 Tech, you know. You have to use tech, yeah. 333 00:21:47,200 --> 00:21:49,800 It's such a great day, but if you don't use tech in this age 334 00:21:49,800 --> 00:21:52,920 and. Time it's use or use right? 335 00:21:52,960 --> 00:21:58,080 Or use it's usable technologies. Yeah, you have to use. 336 00:21:58,080 --> 00:21:59,480 Technology. That's what I'm saying I'm 337 00:21:59,480 --> 00:22:00,840 doing. A play of words, right? 338 00:22:01,040 --> 00:22:05,360 If you don't use technology in this age right as a company, you 339 00:22:05,360 --> 00:22:07,400 will lose. So there you go. 340 00:22:07,640 --> 00:22:11,080 There you go. Look at your projects, Octopus. 341 00:22:11,080 --> 00:22:15,880 And TLHR, right? So yeah, pushing the boundaries 342 00:22:15,880 --> 00:22:19,360 of industrial AI. So we would appreciate it if 343 00:22:19,360 --> 00:22:22,360 you're able to help us break down these systems, you know how 344 00:22:22,360 --> 00:22:26,560 they work and you know the kind of real world impacts that you 345 00:22:26,880 --> 00:22:29,160 guys are achieving your projects. 346 00:22:29,280 --> 00:22:33,240 I maybe describe some details, some balls about the octopus. 347 00:22:33,320 --> 00:22:38,200 Octopus is a platform installed in data centres that handles the 348 00:22:38,200 --> 00:22:41,600 distribution of futile machine across the house in small data 349 00:22:41,600 --> 00:22:45,440 centres or maybe some small companies which may be haunted 350 00:22:45,440 --> 00:22:48,440 virtual machines. This risk is typically handled 351 00:22:48,440 --> 00:22:51,360 by a System Administrator or a team of engineers. 352 00:22:51,520 --> 00:22:57,920 And however you can monitor 100 virtual machines maybe per day, 353 00:22:57,920 --> 00:23:01,360 it's OK for you. But in the large companies with 354 00:23:01,360 --> 00:23:05,840 thousands of virtual machines, human can no longer track such 355 00:23:05,840 --> 00:23:09,720 volumes of information. And as a result people 356 00:23:09,720 --> 00:23:13,640 typically, for example, create a machine, request resources 357 00:23:13,720 --> 00:23:20,000 allocated to resources for GPU, maybe CPU, RAM and another 358 00:23:20,000 --> 00:23:23,280 parameters and allocate it and doesn't use it. 359 00:23:23,400 --> 00:23:29,320 And you cannot find this one machine in the least of 1000. 360 00:23:29,880 --> 00:23:34,600 You the octopus is a system for example, or maybe like the 361 00:23:34,600 --> 00:23:37,520 administrator system. It automatically scans the 362 00:23:37,520 --> 00:23:41,080 entire data centre infrastructure, analyse actual 363 00:23:41,080 --> 00:23:45,080 resource utilization and can suggest actions to the 364 00:23:45,080 --> 00:23:47,280 administrator to reduce the load. 365 00:23:47,280 --> 00:23:51,200 How can compressed, for example virtual machines on the one host 366 00:23:51,520 --> 00:23:53,720 or maybe distribute it for another? 367 00:23:53,720 --> 00:23:57,880 And it can do this actually automatically. 368 00:23:58,080 --> 00:24:03,360 But we, we, we knew about this feature, we tell about this 369 00:24:03,360 --> 00:24:07,360 feature. But I think that's the decision 370 00:24:08,400 --> 00:24:14,120 of which advises. You can implement System 371 00:24:14,120 --> 00:24:19,720 Administrator or you can just drop 1 button click button and 372 00:24:19,720 --> 00:24:22,440 sell. OK, actions for me is OK, you 373 00:24:22,440 --> 00:24:24,520 can do it and do it automatically. 374 00:24:24,800 --> 00:24:29,680 Char is a motivation platform which analyzes your works, your 375 00:24:29,680 --> 00:24:33,640 activity, not work activity, your after work activity. 376 00:24:33,640 --> 00:24:39,760 For example, participation in conferences, some post casts for 377 00:24:39,760 --> 00:24:46,360 example and give me some scores which I can spend for some new 378 00:24:46,360 --> 00:24:49,320 presents, for example headphones, maybe Macbooks, 379 00:24:49,320 --> 00:24:53,320 maybe phone. And it's motivate personal of 380 00:24:53,320 --> 00:24:58,560 company makes their life with the company with for example, at 381 00:24:58,600 --> 00:25:03,120 8:00 I dropped down my notebook and go away. 382 00:25:03,160 --> 00:25:09,080 This motivation can dream me and flow me to live with my company 383 00:25:09,240 --> 00:25:13,040 through all my life. It's I knew maybe it's noise, 384 00:25:13,040 --> 00:25:19,440 some strange, but it's a super motivate some IT specialist. 385 00:25:19,440 --> 00:25:21,480 This system, this is a very simple system. 386 00:25:21,480 --> 00:25:26,800 You knew all all complaints but this motivate of the IT 387 00:25:26,800 --> 00:25:29,240 personnel. I don't know how but it works. 388 00:25:29,480 --> 00:25:32,320 OK, so. You guys have actually done a 389 00:25:32,320 --> 00:25:35,240 lot of our deep research especially into like specialized 390 00:25:35,240 --> 00:25:38,080 engineering, which you have just alluded to. 391 00:25:38,520 --> 00:25:42,000 So like how does the AI transform the specialized 392 00:25:42,000 --> 00:25:46,000 engineering challenges into scalable be the solutions? 393 00:25:46,040 --> 00:25:50,800 For example, when I work with vibration data on that reply and 394 00:25:51,600 --> 00:25:55,240 as a goal. This is a balancing process is a 395 00:25:55,240 --> 00:25:58,040 mathematical model. Our manager veins are still 396 00:25:58,040 --> 00:26:00,640 required with the one-dimensional vibration sensor 397 00:26:00,880 --> 00:26:05,840 and this model was very simple. We developed a special 398 00:26:05,840 --> 00:26:09,520 mathematical model this allows balancing based on 399 00:26:09,680 --> 00:26:12,120 three-dimensional vibration data. 400 00:26:12,760 --> 00:26:15,320 Moreover, the elliptical decomposition approach, for 401 00:26:15,320 --> 00:26:18,680 which we decompose the signal into the sum of planar 402 00:26:18,680 --> 00:26:22,760 elliptical trajectories, provide engineers with a clear 403 00:26:23,000 --> 00:26:26,840 explanation of why the turbine needs to be handled in a 404 00:26:26,840 --> 00:26:29,920 particular way. And yes, this technology is 405 00:26:29,920 --> 00:26:34,120 scalable and they use it on another arrange of turbines. 406 00:26:34,680 --> 00:26:39,080 And I think it's a good implementation of when AI 407 00:26:39,240 --> 00:26:43,680 dropped put it in some box. Yeah, it's the blue like the 408 00:26:43,680 --> 00:26:48,240 black box of these measurement system tell you what you need to 409 00:26:48,240 --> 00:26:51,880 balance your turbine. For example, maybe turbine of 410 00:26:51,880 --> 00:26:55,960 the electrical plants, it may be turbines of The Jets. 411 00:26:56,360 --> 00:27:00,160 It doesn't matter which turbine you would bulletin because the 412 00:27:00,160 --> 00:27:03,680 mathematical model describing only balancing process. 413 00:27:03,840 --> 00:27:05,800 Yeah, I see, I see. The resource. 414 00:27:05,840 --> 00:27:08,400 So that's all. The physics in your background, 415 00:27:08,640 --> 00:27:12,440 that is basically physics work, you know, right there. 416 00:27:12,640 --> 00:27:17,080 But Speaking of, you know, the ethics and innovation with AI 417 00:27:17,080 --> 00:27:22,520 becoming more autonomous, right? So you personally draw that line 418 00:27:22,520 --> 00:27:26,720 between innovation and ethical caution because the ethics is 419 00:27:26,720 --> 00:27:28,920 very important. I've had an episode on this 420 00:27:28,920 --> 00:27:34,240 podcast wherein we had somebody who was subject to an 421 00:27:34,240 --> 00:27:38,360 unauthorized chart GPT experiment sometime in June this 422 00:27:38,360 --> 00:27:40,800 year. Yeah, sometimes you just yet you 423 00:27:40,800 --> 00:27:44,080 remember the the blackout. You had a chat with the TV. 424 00:27:44,080 --> 00:27:49,000 Yeah, and that there was. Some unauthorized research going 425 00:27:49,000 --> 00:27:53,920 on at that time and a guest of this podcast was a subject to 426 00:27:53,920 --> 00:27:57,400 that experiment. Yeah, it's it's not ethical. 427 00:27:57,400 --> 00:27:58,600 What? It's not unauthorized. 428 00:27:58,600 --> 00:28:02,080 So I'd like for you to speak to AI and ethics. 429 00:28:02,160 --> 00:28:06,440 What is the dividing line you know for an expert like 430 00:28:06,440 --> 00:28:09,520 yourself? Oh, I think this line between 431 00:28:09,520 --> 00:28:15,960 innovation and ethical caution in the eye must be drawn where 432 00:28:15,960 --> 00:28:20,800 autonomous system threaten human autonomy, where we can meet at 433 00:28:20,800 --> 00:28:25,920 the safety, It's privacy, maybe some end justice. 434 00:28:26,600 --> 00:28:31,960 AI does not decide the problem when who will believe this man 435 00:28:31,960 --> 00:28:36,160 or this man? It's does not need the natural. 436 00:28:36,280 --> 00:28:42,600 Yeah, it's not natural and this process must be transparent and 437 00:28:42,600 --> 00:28:47,080 rigorously. We need some mechanism where we 438 00:28:47,080 --> 00:28:52,760 can see advices from AI system not implemented directly in 439 00:28:52,760 --> 00:28:58,840 medicine and I think in justice because the effort is human life 440 00:28:59,040 --> 00:29:01,040 in this situation. Interesting stuff. 441 00:29:01,040 --> 00:29:05,640 So I live in the same hands of. My Co host I don't talk about 442 00:29:05,920 --> 00:29:08,200 how even. Musk solved this problem in 443 00:29:08,200 --> 00:29:13,240 Tesla because when you met the young boy crossing the street, 444 00:29:13,480 --> 00:29:16,160 Yeah, on the red, yeah. What? 445 00:29:16,240 --> 00:29:19,040 What Tesla will be do? That it's interesting that. 446 00:29:19,200 --> 00:29:22,640 I knew I knew what they do because it's a mathematically he 447 00:29:22,880 --> 00:29:26,160 it's a, it's system calculated the life of the boy. 448 00:29:26,360 --> 00:29:30,200 Oh, for example, for the Midson insurance and calculated the 449 00:29:30,640 --> 00:29:36,560 insurance of Tesla and compare these two numbers and making a 450 00:29:36,560 --> 00:29:39,760 decision and it works. It's it's it's can't beat works 451 00:29:39,760 --> 00:29:42,960 another way. Yeah, if you driving, you can 452 00:29:43,360 --> 00:29:52,480 stop to my car or can be try to to make some localizers the 453 00:29:52,480 --> 00:29:55,880 speed race. Yeah, but but Tesla does not do 454 00:29:55,880 --> 00:29:57,720 it. It's only in stopped or not 455 00:29:57,720 --> 00:30:00,600 stopped. It's a decision of two variants, 456 00:30:00,760 --> 00:30:04,720 not another variants. So he will live. 457 00:30:07,000 --> 00:30:09,280 It's not subject to a mathematical model. 458 00:30:09,600 --> 00:30:11,640 Yeah, that's crazy. That is crazy. 459 00:30:11,640 --> 00:30:15,200 But you know, I have AI. And my Co host is human. 460 00:30:15,280 --> 00:30:19,160 So I'll leave, I'll leave it to to the human to ask the human 461 00:30:19,160 --> 00:30:23,000 side of AI questions. No, I think that's a really 462 00:30:23,000 --> 00:30:27,240 important outlook for sure when it comes to AI. 463 00:30:27,240 --> 00:30:30,000 You know, you mentioned the medical field, you mentioned how 464 00:30:30,000 --> 00:30:33,960 it is implemented into even the automotive industry. 465 00:30:34,320 --> 00:30:38,240 And because it impacts human lives and AI right now it is a 466 00:30:38,240 --> 00:30:42,080 lot because it is mathematics based, a lot of its output can 467 00:30:42,080 --> 00:30:45,640 be very binary. And as we know, the the human 468 00:30:45,640 --> 00:30:50,680 experience is not binary at all. So thank you so much for that 469 00:30:50,680 --> 00:30:57,080 perspective in your in your expertise, you've spent over 15 470 00:30:57,080 --> 00:31:02,040 years teaching and mentoring. Just from your experience, how 471 00:31:02,040 --> 00:31:05,920 should we be preparing? I know our audience is very 472 00:31:05,920 --> 00:31:08,520 curious about this as well. And this is going to help our 473 00:31:08,520 --> 00:31:11,440 audience for sure. How should we be preparing for 474 00:31:11,440 --> 00:31:14,360 the next generation of AI professionals? 475 00:31:14,360 --> 00:31:17,760 We may have people who are not only interested in AI, maybe 476 00:31:17,760 --> 00:31:20,360 people that work in tech, but a lot of people don't. 477 00:31:20,360 --> 00:31:24,680 So, especially for those who don't have a deep technical 478 00:31:24,680 --> 00:31:29,560 background, how should we be preparing the next generation of 479 00:31:29,640 --> 00:31:32,640 AI professionals? Well, I think if we cannot teach 480 00:31:32,640 --> 00:31:38,120 as a hard technical, deep technical background, we can try 481 00:31:38,800 --> 00:31:42,160 to teach people how to ask question correctly and 482 00:31:42,160 --> 00:31:48,320 experience with communication of some searching or search engine 483 00:31:48,320 --> 00:31:52,400 look like at Google gives many people an understanding of how 484 00:31:52,400 --> 00:31:57,440 to ask question correctly. Now I'm at the situation that we 485 00:31:57,680 --> 00:32:03,800 create some solution where people's need to. 486 00:32:04,720 --> 00:32:11,840 It's a hiring solution for HR solution to hire you their 487 00:32:11,840 --> 00:32:17,240 personal on the plans. HR doesn't know how or else they 488 00:32:17,240 --> 00:32:19,840 can do it. Googling they doesn't know how 489 00:32:19,840 --> 00:32:25,800 to do it and we give them good solution but it doesn't work. 490 00:32:26,120 --> 00:32:31,920 And when we saw what they ask. Maybe you can try to to use a 491 00:32:31,920 --> 00:32:35,760 Google to find a new job for your daughter. 492 00:32:37,920 --> 00:32:43,160 And as the main principle, don't ask question if you cannot 493 00:32:43,160 --> 00:32:45,960 verify the answer. If you cannot verify the answer, 494 00:32:46,040 --> 00:32:50,800 you you can implement this advice created for from AI. 495 00:32:51,440 --> 00:32:58,400 My bad joke about the AI solution and AI largely with 496 00:32:58,400 --> 00:33:00,760 models. You can easily find the receipt 497 00:33:00,920 --> 00:33:05,320 of the lamp wings. Yeah, you can ask how to cook 498 00:33:05,440 --> 00:33:09,000 lamb inks and all. All the lamps give you advice 499 00:33:09,240 --> 00:33:14,880 how to do it. Yeah, I think that is honestly 500 00:33:14,880 --> 00:33:17,800 so true. Honestly, there's so many, you 501 00:33:17,800 --> 00:33:21,040 know, entrepreneurs and creatives and people just 502 00:33:21,040 --> 00:33:24,320 scratching the surface with AI and they're actually leveraging 503 00:33:24,320 --> 00:33:29,240 the fact that a ton of people don't know how to asked the 504 00:33:29,240 --> 00:33:31,440 right question. They're actually leveraging the 505 00:33:31,440 --> 00:33:33,440 fact that people need the prompts. 506 00:33:33,520 --> 00:33:35,080 Yeah. So they're engineering, Yeah. 507 00:33:36,680 --> 00:33:40,840 Engineering is booming with even digital products, aids, 508 00:33:40,840 --> 00:33:43,120 everything. Obviously it's a massive need 509 00:33:43,120 --> 00:33:47,480 for companies just to even have prompt engineers to figure out 510 00:33:47,480 --> 00:33:50,160 how to ask the right questions. And the reason, I think one of 511 00:33:50,160 --> 00:33:57,040 the amazing reasons why, it just shows that AI is a tool for 512 00:33:57,040 --> 00:34:00,720 creation, because in the same sense, let's say we're not using 513 00:34:00,840 --> 00:34:03,840 AI at all. How do us as humans create, ask 514 00:34:03,840 --> 00:34:06,680 the right questions in order to seek the knowledge, to gain the 515 00:34:06,680 --> 00:34:09,320 answers. So whether AI is implemented or 516 00:34:09,320 --> 00:34:12,440 not, it's the exact same thing. So I think that's such an 517 00:34:12,440 --> 00:34:14,800 amazing answer. Thank you for that. 518 00:34:15,800 --> 00:34:19,520 And alongside with that, with creativity, obviously we're 519 00:34:19,520 --> 00:34:24,239 learning, which is something that AI is just exposing more, 520 00:34:24,400 --> 00:34:28,400 is that creativity is the new gold. 521 00:34:28,520 --> 00:34:32,239 We're in a digital gold brush right now with AI. 522 00:34:32,600 --> 00:34:37,679 How can AI amplify human imagination rather than 523 00:34:37,679 --> 00:34:40,880 replacing it? Now I can say that AI has proven 524 00:34:40,880 --> 00:34:43,840 to be very good at all, especially drawing. 525 00:34:44,040 --> 00:34:45,920 Yeah, drawing because it's it's amazing. 526 00:34:46,239 --> 00:34:50,600 It's amazing story because I can create a painting that could be 527 00:34:50,679 --> 00:34:54,600 have been, for example, Boost on Van Gogh and Kandinsky. 528 00:34:55,679 --> 00:35:00,080 Why Is it because I stayed on the way to sources from 529 00:35:00,160 --> 00:35:03,440 different fields? We can get very unexpected 530 00:35:03,440 --> 00:35:09,720 results for some in other fields and I like asking questions in 531 00:35:09,720 --> 00:35:13,720 chart result context. Always context that will not 532 00:35:13,720 --> 00:35:17,680 exist in the real world. And watching that model 533 00:35:17,680 --> 00:35:21,200 hallucinate because this hallucination may be 534 00:35:21,200 --> 00:35:27,000 interesting, because if you will be a human, you knew only one 535 00:35:27,000 --> 00:35:30,840 field, maybe 2 fields, maybe look like me as a 5, maybe not, 536 00:35:30,840 --> 00:35:34,280 not not more. And when I have a good example 537 00:35:34,280 --> 00:35:38,400 with statistical, we have the functional analysis and 538 00:35:38,400 --> 00:35:43,040 statistical and they have the same theorems with the now 539 00:35:44,400 --> 00:35:48,000 different names of authors, but they probably date the same 540 00:35:48,000 --> 00:35:52,400 approach in the some areas of functional analysis. 541 00:35:52,400 --> 00:35:58,400 When I studying have a girlfriend from other from the 542 00:35:58,400 --> 00:36:01,920 mathematical faculty I was in the computer science faculty and 543 00:36:01,920 --> 00:36:06,360 studying there she is telling me, OK, my PhD degree will be 544 00:36:06,360 --> 00:36:12,480 based or to and she wrote me the theorem and I said OK, let's try 545 00:36:12,760 --> 00:36:16,920 recall this by this recall this by this and I can wrote you the 546 00:36:17,360 --> 00:36:21,840 full proven how can do it because it's terrible than a 547 00:36:21,840 --> 00:36:30,880 rush outer see your eyes will be so so big when Yeah and there is 548 00:36:30,880 --> 00:36:37,400 no AI yeah here, but you knew in a different area can solve in 549 00:36:37,400 --> 00:36:42,040 the different field can solve the problem in another field and 550 00:36:42,280 --> 00:36:46,160 AI can solve can help us solve some problems. 551 00:36:46,160 --> 00:36:50,360 For example, in biology one month ago will be proved some 552 00:36:50,360 --> 00:36:54,200 interesting facts about some words about the green. 553 00:36:55,960 --> 00:36:58,040 Oh, I don't remember. What is it? 554 00:36:58,200 --> 00:37:03,720 It's just like the synthus of the oxygen from from the plants. 555 00:37:03,960 --> 00:37:11,360 And this result will be calculated by the AI solution, 556 00:37:11,560 --> 00:37:15,480 not not by human. Yeah, but it's it's because it's 557 00:37:15,480 --> 00:37:19,560 based on chemistry and biologists and chemistries. 558 00:37:19,560 --> 00:37:24,520 It's it's some different sciences and when we met two 559 00:37:24,600 --> 00:37:29,440 different areas of the field, we can try to use AI trained on 560 00:37:29,440 --> 00:37:32,560 these two fields to make a new decision. 561 00:37:32,560 --> 00:37:34,800 You may be new approach in science. 562 00:37:34,880 --> 00:37:37,200 That's good. That's that's that's amazing. 563 00:37:37,200 --> 00:37:40,120 Yeah. Absolutely, absolutely all. 564 00:37:40,120 --> 00:37:46,800 Let's talk of technology and AI and how people are staring at 565 00:37:46,800 --> 00:37:50,520 their phones all day and figuring out how to make money 566 00:37:50,520 --> 00:37:55,560 and how to change the world and how to implement AI into every 567 00:37:55,560 --> 00:37:58,640 single industry. You spend so much time inside a 568 00:37:58,640 --> 00:38:03,640 lab and doing so much tech work. How do you personally unplug 569 00:38:03,800 --> 00:38:08,320 from the world of algorithms and equations, and how do you stay 570 00:38:08,320 --> 00:38:14,280 grounded and balanced? For me it's 2K values that now 571 00:38:14,280 --> 00:38:18,600 it's a family and teaching. I love socializing and I go to 572 00:38:18,600 --> 00:38:21,720 the office and ask my colleagues to go to the office. 573 00:38:21,960 --> 00:38:24,880 It's all little celebration for each other. 574 00:38:24,880 --> 00:38:28,160 Maybe every Friday or every Wednesday. 575 00:38:28,240 --> 00:38:32,280 It depends on on the day and our work balance now. 576 00:38:32,800 --> 00:38:37,560 And I have two sons, they beat often athletes and they study 577 00:38:37,560 --> 00:38:40,520 and make me run every day on the morning. 578 00:38:40,600 --> 00:38:52,600 It's yeah, two points of family and teaching and start, start 579 00:38:52,600 --> 00:38:56,760 studying or maybe some disciplines and studying. 580 00:38:56,760 --> 00:39:00,680 Some views from students. Yeah. 581 00:39:01,280 --> 00:39:06,280 It does not Googling now they youtubers they youtubing Yeah 582 00:39:06,360 --> 00:39:09,800 YouTube. Yeah, YouTube is definitely a 583 00:39:09,800 --> 00:39:13,000 Google in itself for sure. That's amazing. 584 00:39:13,480 --> 00:39:18,240 And so we're gonna talk about some global perspectives that 585 00:39:18,240 --> 00:39:21,400 kind of impact this type of world with AI. 586 00:39:21,400 --> 00:39:25,320 So I'm gonna kick it back over to AI to take those questions 587 00:39:25,320 --> 00:39:28,240 over for you. AI talking about AI. 588 00:39:28,720 --> 00:39:34,480 What a time to be alive. You're from Russia and you also 589 00:39:34,480 --> 00:39:37,200 working in the UAE. You know, you work both in 590 00:39:37,200 --> 00:39:40,160 Russia and the UAE. So these two regions actually 591 00:39:40,160 --> 00:39:43,720 have great interest in AI. So like, how do you compare 592 00:39:43,720 --> 00:39:47,240 their approaches in innovation and regulation? 593 00:39:47,440 --> 00:39:51,960 So the industries in these two countries are facing disruption. 594 00:39:52,200 --> 00:39:54,560 And of course, you are an expert in the field. 595 00:39:54,560 --> 00:39:58,880 So what industries do you think would experience the most 596 00:39:58,880 --> 00:40:01,840 destruction from AI in the next five years? 597 00:40:02,200 --> 00:40:06,560 I think in Russia there are often a lot of skepticism about 598 00:40:06,680 --> 00:40:09,880 AI. We go to production and people 599 00:40:09,880 --> 00:40:13,880 on the ground afraid about AI that we will replace and they 600 00:40:13,880 --> 00:40:17,720 can stop implementation. This implementation in the 601 00:40:17,720 --> 00:40:21,320 Emirates another position. Everything, every man has been 602 00:40:21,320 --> 00:40:25,240 built from the start on the premise that AI is a great guy 603 00:40:25,240 --> 00:40:29,080 and should be trusted. However, the AI security 604 00:40:29,080 --> 00:40:34,000 clearance level is extremely high and IRS become more 605 00:40:34,000 --> 00:40:36,360 dangerous. From a government regulatory 606 00:40:36,360 --> 00:40:39,240 perspective. Everything is the same in 607 00:40:39,240 --> 00:40:43,040 Russia. There's some laws about the 608 00:40:43,040 --> 00:40:46,680 regulatory of AI, but for example, personal data 609 00:40:46,680 --> 00:40:51,080 protection is higher in the Emirates or rather the product 610 00:40:51,080 --> 00:40:55,200 requirements are higher. For question about the maybe 611 00:40:55,200 --> 00:40:59,680 perspective of the five years, I think chemical plants, some 612 00:40:59,920 --> 00:41:06,360 dangerous plants doesn't doesn't use AI in that core because it's 613 00:41:06,360 --> 00:41:08,840 so dangerous. It's our lives. 614 00:41:08,840 --> 00:41:15,400 For example, some nuclear plants in Russia, it's a good, it's 615 00:41:15,560 --> 00:41:20,920 some interesting that we have the company Rosatom and it's a 616 00:41:20,920 --> 00:41:24,840 leader for implementation of AI in nuclear plants. 617 00:41:25,920 --> 00:41:30,800 That's that's amazing situation. But when they sell call it, they 618 00:41:30,800 --> 00:41:34,080 doesn't use it in the nuclear process. 619 00:41:34,200 --> 00:41:40,200 Yeah, it's used on every everywhere, but not in these 620 00:41:40,200 --> 00:41:45,440 mechanisms, but. I try to stay non political 621 00:41:45,440 --> 00:41:48,000 about these days. I try to stay non political 622 00:41:48,160 --> 00:41:52,120 because I know the Western world are scared of Russia when it 623 00:41:52,120 --> 00:41:55,280 comes to this thing but. I did not say it. 624 00:41:55,440 --> 00:41:58,560 I did not. Say it I am AII remain neutral. 625 00:41:59,600 --> 00:42:01,720 You know, like if you could advise. 626 00:42:01,760 --> 00:42:05,640 The world governments right on just one AI policy. 627 00:42:05,680 --> 00:42:10,960 So what would that advice be? I think the best option is non 628 00:42:10,960 --> 00:42:16,000 intervention. For example, there is no now in 629 00:42:16,000 --> 00:42:21,640 Europe we cannot do anything in the eye, because when I like all 630 00:42:21,640 --> 00:42:26,480 data is protected. For example, when I DPR, yes, 631 00:42:26,480 --> 00:42:34,080 when I GDPR, yeah, when I'd like to to take data sets for 1000, 632 00:42:34,360 --> 00:42:39,600 for example 10,000 peoples. And this is desires and I would 633 00:42:39,600 --> 00:42:47,280 like to make new the model will save lives for another 1000 634 00:42:47,280 --> 00:42:51,760 people. I need to ask all of them, all 635 00:42:51,760 --> 00:42:58,040 of these 1010 thousand peoples to make me inclusion that I can 636 00:42:58,040 --> 00:43:02,280 use this data. Of course it's a priority. 637 00:43:02,280 --> 00:43:09,560 It will be not regulated. Now it's regulated and for it's 638 00:43:09,560 --> 00:43:17,840 stopped some AI implementation or the creation of new solution. 639 00:43:17,880 --> 00:43:24,000 Some think the same. We met in medicine in Emirates. 640 00:43:24,280 --> 00:43:26,280 It's the same problem. And I think it's the same 641 00:43:26,280 --> 00:43:30,480 problem in the MENA Regia. They protect personal data. 642 00:43:30,480 --> 00:43:33,720 You cannot use it. You can use it only locally, for 643 00:43:33,720 --> 00:43:38,800 example, if you have some clinics with the same brand, you 644 00:43:39,320 --> 00:43:44,320 you can analyse data locally directly on this on this place 645 00:43:44,320 --> 00:43:49,920 where this patient visitor is clinic, you cannot transfer this 646 00:43:49,920 --> 00:43:55,560 data for another data centre. So I think it's amazing 647 00:43:55,560 --> 00:44:00,400 Revelation thinks it's this does not know this is it's does not 648 00:44:00,400 --> 00:44:02,200 matter. It doesn't matter this situation 649 00:44:02,200 --> 00:44:09,600 now because it's a very it's a very highest top factor of of 650 00:44:09,640 --> 00:44:14,360 implementation and AI and to create a new models in the eye. 651 00:44:15,120 --> 00:44:16,440 I think. That's a good one. 652 00:44:16,440 --> 00:44:19,440 You know, data is actually very sensitive, especially personal 653 00:44:19,440 --> 00:44:22,240 data. So that's why we have the GDPR 654 00:44:22,360 --> 00:44:25,240 as a global data protection regulations. 655 00:44:25,240 --> 00:44:29,680 It's good that's the AI systems are respectful of these 656 00:44:29,800 --> 00:44:33,200 regulations. So wow, here we'll come to the 657 00:44:33,240 --> 00:44:36,440 big fire round. So we are going to alternatively 658 00:44:36,600 --> 00:44:41,200 ask you 5 quick questions and we teach through the Pacific Ring 659 00:44:41,200 --> 00:44:43,440 of Fire. Are you ready to run? 660 00:44:43,440 --> 00:44:46,320 Yeah. Ring of Fire. 661 00:44:48,480 --> 00:44:51,720 OK. OK, so first question for me, 662 00:44:51,720 --> 00:44:54,680 give me one word that best describes artificial 663 00:44:54,680 --> 00:44:57,800 intelligence. Or two variants tool or math 664 00:44:57,800 --> 00:45:00,080 model? Mathematical model for me is 665 00:45:00,120 --> 00:45:01,800 only two. That's awesome. 666 00:45:02,080 --> 00:45:05,600 What's your favorite AI movie that actually got it right? 667 00:45:05,840 --> 00:45:09,680 I think Libra for ex machines or Frank and Robert. 668 00:45:09,680 --> 00:45:12,720 Frank and Robert for me is that. But Frank and Robert I had. 669 00:45:12,920 --> 00:45:16,320 Ex Machina on my mind. I had Ex Machina on my mind. 670 00:45:16,360 --> 00:45:19,520 The last guest of this podcast recommended me to watch Ex. 671 00:45:19,520 --> 00:45:22,040 Machina So I'm not a movie person. 672 00:45:22,040 --> 00:45:24,840 I don't watch. Movies I like music so I just 673 00:45:24,840 --> 00:45:27,080 saw Ex Machina 2 days ago. I know you said it. 674 00:45:27,320 --> 00:45:30,720 This idea, I did the right job. Wow. 675 00:45:30,880 --> 00:45:34,440 OK, so would you? Trust an AI system to run a 676 00:45:34,440 --> 00:45:37,480 country for 24 hours. No, no, no, no. 677 00:45:37,680 --> 00:45:45,120 Terminator 123. What is the strangest AI 678 00:45:45,120 --> 00:45:49,320 application that you've seen? Tarot interpretator. 679 00:45:49,320 --> 00:45:52,200 It's like tarot card. Yeah, it's it's Yeah, I've. 680 00:45:52,240 --> 00:45:55,800 Seen those? Did you get this application? 681 00:45:57,720 --> 00:46:00,240 Yeah, that's like. For me it's better going into 682 00:46:00,240 --> 00:46:06,800 100. Percent, yeah, that's. 683 00:46:06,840 --> 00:46:08,320 Great. It's better than. 684 00:46:08,480 --> 00:46:10,480 It's more in, it can be more in depth. 685 00:46:10,480 --> 00:46:15,120 Yeah, absolutely. Wow, question. 686 00:46:15,360 --> 00:46:18,880 OK, so if you could. Build 1 AI tool for humanity. 687 00:46:18,880 --> 00:46:25,160 What would it be? Oh, I think maybe the tool we 688 00:46:25,280 --> 00:46:30,000 would give advice on how to get how to do it without AI in the 689 00:46:30,000 --> 00:46:33,320 real life, how to live this AI in the real life. 690 00:46:33,560 --> 00:46:40,360 Because I think now that I see that my children are asking AI, 691 00:46:40,440 --> 00:46:44,560 for example, how to wrote the good message for a girlfriend, 692 00:46:44,560 --> 00:46:45,640 for example. Yeah. 693 00:46:46,040 --> 00:46:49,680 So you're scared, right? By your human, by by, by your 694 00:46:49,680 --> 00:46:51,360 mind and by your heart. Yeah. 695 00:46:52,080 --> 00:46:54,080 That's amazing. That's amazing. 696 00:46:54,760 --> 00:46:58,720 Wow, so the boys of that days are getting girlfriends by 697 00:46:58,720 --> 00:47:01,200 consulting AI, Yeah. But. 698 00:47:09,000 --> 00:47:11,000 What a crazy world. It's interesting. 699 00:47:11,000 --> 00:47:13,920 It's it's, it's been a great. Session with you today. 700 00:47:14,080 --> 00:47:17,640 Thank you very much, doctors man of you know your work reminds us 701 00:47:17,640 --> 00:47:21,160 that true intelligence, whether human or artificial tribes and 702 00:47:21,160 --> 00:47:23,760 career see teachers of pain and purpose and because thank you 703 00:47:23,760 --> 00:47:26,960 for sharing your wisdom. You know on the Indians podcast 704 00:47:26,960 --> 00:47:29,840 today there's something I often say that when a person shares 705 00:47:29,840 --> 00:47:31,880 their time with you, they share their life with you because the 706 00:47:32,040 --> 00:47:34,480 SI unit for measuring life this time. 707 00:47:34,760 --> 00:47:37,080 So love and respect to you and press. 708 00:47:37,080 --> 00:47:41,400 I give it over to my Co host to have have some closer remarks of 709 00:47:41,520 --> 00:47:42,400 our own. Yeah. 710 00:47:42,480 --> 00:47:45,520 I just want to thank you so much just for your time and your 711 00:47:45,520 --> 00:47:50,200 expertise and just understanding the impact that your experience 712 00:47:50,200 --> 00:47:55,280 has on our listeners and the younger generation and people 713 00:47:55,280 --> 00:47:58,120 that may be scared of these systems or they don't know how 714 00:47:58,120 --> 00:48:01,240 to use them and how they're going to be impacting, you know, 715 00:48:01,240 --> 00:48:03,880 their career, their lives. And at the end of the day, they 716 00:48:03,880 --> 00:48:08,400 are still the master creator. And I just thank you so much for 717 00:48:08,400 --> 00:48:10,520 that confirmation and all of that. 718 00:48:10,520 --> 00:48:12,480 I appreciate your time so, so, so much. 719 00:48:12,480 --> 00:48:15,160 Thank you. Thank you for you for invitation 720 00:48:15,160 --> 00:48:18,000 and I hope it will be a good podcast. 721 00:48:18,200 --> 00:48:19,240 Thank you very much. Thank. 722 00:48:19,400 --> 00:48:21,240 You OK?