“Sam Altman Is Not a Person” – Mo Gawdat On OpenAI, Demis Hassabis, AI Arms Race & More… (YouTube Video Transcript)

(00:00:00) Your YouTube transcript will appear here (00:00:00) Everyone's worried what happens when (00:00:02) AGI, ASI, artificial super intelligence (00:00:05) become a reality. Things we would be (00:00:07) scared of in the past, we start getting (00:00:08) used to and it's like we're sleepwalking (00:00:11) into a new reality. There is a moment in (00:00:14) our future where AI will be in charge of (00:00:17) everything. Most of the mundane jobs (00:00:19) will disappear in 3 years. Most of the (00:00:22) more intelligent jobs will disappear in (00:00:23) the following seven. And what Sam said (00:00:26) is like everyone's going to worry for a (00:00:28) day or two days and then they'll just (00:00:30) move on with their life. (00:00:31) >> Never trust Sam Alman ever. Sam Alman is (00:00:34) not a person. Sam Alman is the creation (00:00:36) of a system. Okay. California is a place (00:00:39) where you have to be very astute because (00:00:41) vapor is worth more than solids. (00:00:50) The the dangers of social media. The (00:00:52) only one I'm struggling with is YouTube (00:00:54) because I have YouTube because there's a (00:00:55) lot of good videos on there. But there's (00:00:56) shorts. (00:00:57) >> Yeah, shorts start to suck you in. (00:01:00) >> That's what I'm not finding out. Like (00:01:01) there's no way to disable. (00:01:02) >> There was a way I found to disable it. (00:01:04) Uh but then it comes back. Uh yeah, I (00:01:08) think you should you have to disable it (00:01:10) here. (00:01:10) >> It's not easy. (00:01:11) >> It's not easy. So addictive. Yeah. And (00:01:13) I'm so disappointed in YouTube. (00:01:15) >> Yeah. Because they're a business at the (00:01:18) end of the day because everyone talks (00:01:20) about how social media is addictive. I (00:01:22) always thought they're overexaggerating, (00:01:24) >> but now I've just fell into it because (00:01:26) of YouTube shorts. (00:01:26) >> Yeah, short shorts are really I mean it (00:01:29) it is quite an interesting way because (00:01:32) if so I I use YouTube in an interesting (00:01:34) uh way. I have multiple YouTube accounts (00:01:37) and I highly skew the the recommendation (00:01:41) engine for each of them. So one of them (00:01:43) would be only AI, one of them would be (00:01:46) only classic cars, one of them right (00:01:48) >> different accounts with different nice (00:01:50) algorithm. Exactly. And when so when you (00:01:52) sign into uh you know you're in the mood (00:01:54) to to to look at classic cars, you know, (00:01:57) the entire feed is classic cars. (00:01:59) >> And the whole idea is when they show you (00:02:01) a pretty girl, you avoid that or you (00:02:03) even sometimes unlike the videos. (00:02:05) >> So you're training the algorithm and (00:02:07) then in that case shorts are addictive, (00:02:09) but they're at least on point. (00:02:11) >> And I find that to be very very useful. (00:02:13) So So basically befriend the AI instead (00:02:15) of having it use you. Basically, (00:02:17) >> what's been fascinating is um before we (00:02:20) get into to the dangers of AI and how to (00:02:22) prepare, what's been fascinating is that (00:02:24) the things we would be scared of in the (00:02:26) past, we start getting used to. So, (00:02:28) before we'd be scared of how the (00:02:29) algorithm knows us more than we know (00:02:31) ourselves. Yeah. Now, and I found myself (00:02:34) recently when the algorithm starts (00:02:35) sending me stuff that I've been say (00:02:37) going through a difficult time in your (00:02:39) relationship or in your business and the (00:02:40) you start getting videos telling you (00:02:42) what to do and how to deal with those (00:02:43) issues. (00:02:45) Initially I was uh you know spooked like (00:02:47) everyone was. I'm like how does it know (00:02:49) so quickly? Now I'm like (00:02:51) >> of course it does. (00:02:52) >> It's and and and I'm trying to see the (00:02:54) good in it. Um but I'm starting to worry (00:02:57) because I'm I'm falling into that loop (00:03:00) >> 100% (00:03:01) >> the loop of the algorithm. (00:03:02) >> Yeah. (00:03:03) >> Which is probably one of the early ways (00:03:06) AI is unintentionally dividing us. Um (00:03:09) even before AI become became as smart as (00:03:11) it is now. like it is causing these echo (00:03:15) chambers. It is dividing the word the (00:03:17) world politically. Um and it's like (00:03:20) we're sleepwalking into a new reality. (00:03:23) We totally are. (00:03:26) Uh at at an individual level, at a (00:03:28) government level, at a nation level, at (00:03:31) every possible level, we are completely (00:03:34) drifting somewhere is completely (00:03:36) unknown. And you know, doesn't matter (00:03:39) how loud myself and others are (00:03:42) screaming, people go like, "Yeah, (00:03:44) interesting. But we're still going this (00:03:46) way." (00:03:47) >> And and it really is quite concerning if (00:03:49) you ask me. (00:03:50) >> Yeah. And and the other thing as well is (00:03:52) everyone's worried. Everyone talks about (00:03:53) the Ukraine war. Okay. Everyone talks (00:03:55) about what's happening in Gaza. Both (00:03:57) heartbreaking. Too many people dead. I (00:04:00) talk about it on a regular basis. I do (00:04:01) interviews about it all the time. (00:04:04) But it's where and I think Sam Alman (00:04:06) said a quote that's really interesting. (00:04:08) He said something um along the lines (00:04:10) I'll paraphrase it is that when AGI (00:04:13) comes because everyone's worried what (00:04:14) happens when AGI ASI artificial super (00:04:17) intelligence become a reality. (00:04:20) And what Sam said is like everyone's (00:04:22) going to worry for a day or two days and (00:04:25) then they'll just move on with their (00:04:26) life. They'll look at the news. They'll (00:04:28) be busy with the new Epstein files or a (00:04:31) new war that's ongoing or some Kim (00:04:33) Kardashian doing something. Um, and (00:04:36) that's what I mean by sleepwalking into (00:04:38) that reality. (00:04:39) >> Yeah. Uh, so so there are two sides to (00:04:41) this uh to this if you ask me. One, one (00:04:44) is never trust an alman ever. Uh, you (00:04:47) know, and we can talk about that if you (00:04:48) want to. Uh, but but in general don't (00:04:52) trust the altman. (00:04:53) >> Actually, let's talk about it now. Why? (00:04:55) uh there is a brand some altman is not a (00:04:58) person some altman is the creation of a (00:05:00) system okay and and and it's you know it (00:05:04) is that (00:05:06) Californiaifornian (00:05:08) uh you know disruptor entrepreneur (00:05:13) uh if you've ever worked in California (00:05:16) is a place where you have to be very (00:05:17) astute because uh there is you know (00:05:20) vapor is worth more than solids if you (00:05:22) want you know lots of people are (00:05:25) pitching and making it look like they're (00:05:27) the biggest thing ever. And money is (00:05:30) poured in ideas over and over again. And (00:05:33) you know, and and the idea is to keep (00:05:35) that money flowing. You have to uh comp (00:05:38) comply with certain um etiquette if you (00:05:42) want. (00:05:42) >> One is this is going to be the biggest (00:05:44) thing ever. Two is I am the best thing (00:05:46) ever. And three is uh by the way, this (00:05:49) is going to make the world so much (00:05:51) better. Okay? And if you if you get (00:05:53) those three right, you fit in nicely (00:05:56) with the Silicon Valley ethos and you (00:05:59) may get invested right. Uh then you have (00:06:03) to look deeply and see if uh the promise (00:06:07) is being delivered. Okay. And of course (00:06:10) quite a few times the promise of uh of (00:06:14) technology is missed. you know, uh, you (00:06:18) you you look at Open AI's original (00:06:20) promise, which was to protect the world (00:06:22) from artificial intelligence, to make AI (00:06:26) work for humanity, and then you look for (00:06:29) actions that support that. Uh, and if (00:06:31) you don't find any, uh, then it's just a (00:06:34) pitch, (00:06:35) >> right? It's just a pitch because there (00:06:37) was a point in time back in 1998 where (00:06:40) Google actually came out and said, you (00:06:42) know, uh, we're going to change the (00:06:44) world. were going to organize the (00:06:45) world's information and make it (00:06:47) universally accessible and useful. And (00:06:49) they lived up to it. They did it right (00:06:52) and they did it. And you could see how (00:06:55) Google did it when they invested in (00:06:57) things like Google Scholar or Google (00:06:59) Books for example at the time which made (00:07:02) them absolutely no money whatsoever. (00:07:04) Right? Google maps which until today (00:07:06) makes them very little money but of (00:07:08) course gives them a ton of information (00:07:09) about things. uh you know you look at at (00:07:13) Google's AI today and you look at you (00:07:15) know uh Deep Mind and Deis Hassabis' (00:07:17) work and you know I I know Demis (00:07:20) personally I know you know I've worked (00:07:21) with him I've worked with uh Sundur for (00:07:23) a while and you can see that they're (00:07:26) they're responding to Almans of the (00:07:29) world right uh but they're still trying (00:07:32) to do something interesting so they you (00:07:34) know they have alpha genome alpha fold (00:07:36) alpha tensor all all for the benefit of (00:07:39) humanity real science real discovery and (00:07:41) so on and and so when they say AI can (00:07:45) work make the world better you sort of (00:07:47) go like yeah show us and you know the (00:07:50) alpha projects would show you that the (00:07:52) the open AI projects are all (00:07:55) self-centered they're all about more (00:07:56) users they're all about competitiveness (00:07:58) they're all about you know Vio 30 was (00:08:01) fantastic so let's put Sura 2 and (00:08:03) compete right and and you have to become (00:08:06) aware of those things that most of the (00:08:08) promises is are either the result of the (00:08:11) invention of more and the mad men and (00:08:14) the you know the whole advertising (00:08:15) industry. So they're advertising to you (00:08:17) the user. You know social media tells (00:08:19) you that we're connecting with people. (00:08:21) Yeah, good luck with that. Uh or they (00:08:24) are for the benefit of the employees (00:08:26) because you know the best of the best (00:08:28) don't work for money. They work because (00:08:29) they are inspired by the work that they (00:08:32) do. And so if you tell them we're here (00:08:33) to change the world you know they end up (00:08:37) joining. But you could see at open AI (00:08:39) how all of them Ilia and Meera and all (00:08:42) of those you know most of the core team (00:08:45) at a point in time left and asked for (00:08:47) the company to to change its leadership (00:08:50) right uh and and you you can see that (00:08:54) this this this is not a company that's (00:08:56) living to the promise okay and I say (00:08:57) that and I say it publicly not because I (00:09:00) have anything against Sam Artman as I (00:09:01) said Sam is not a person in my mind it's (00:09:04) that it's that brand that's created by (00:09:06) that system. But I'd say I say it (00:09:09) publicly because I I want Sam Alman to (00:09:11) show us to show us that he is living up (00:09:14) to the promise to show us, you know, do (00:09:16) something that's not for profit. Do (00:09:19) something that's actually changing the (00:09:22) world and making it better. Okay? And (00:09:24) and you can't see that. And when when (00:09:26) you think about it this way, you realize (00:09:28) that yeah uh if if there are more (00:09:30) alultments than demises in in our world (00:09:34) of AI, we're heading in a very very bad (00:09:36) direction. (00:09:37) >> Yeah. And if if you look at OpenAI's uh (00:09:40) open source LLM, no one's using it. It's (00:09:42) just optics. (00:09:44) >> Yeah. And it was there just as a (00:09:45) response to Deep Sea Car 3. So So it's (00:09:47) like again competitive. (00:09:49) >> It's not doing something good. It's (00:09:50) doing something that's necessary. (00:09:51) >> Correct. Did you see? I know it's (00:09:53) irrelevant now, but um I'm not I'm far (00:09:56) from a conspiracy theorist, but then the (00:09:57) story came to my desk and I interviewed (00:09:59) the parents of a of a boy, his name was (00:10:02) >> that was working on OpenAI and then (00:10:03) committed suicide. (00:10:04) >> Yeah, I heard that story. Yeah, (00:10:05) >> exactly. I interviewed his parents and (00:10:07) Tucker interviewed his parents. Did you (00:10:08) see Tucker's interview with Sam Alman (00:10:10) where he asked him a question? (00:10:11) >> I have not yet. (00:10:12) >> You should see that clip. You should see (00:10:13) that clip and I'll ask you what you (00:10:14) think. You it uh (00:10:17) >> first it shows why Tucker is such a (00:10:19) great interviewer. (00:10:20) >> Yes. he asked question, he doesn't shy (00:10:22) away and he keeps digging in. (00:10:24) >> Um (00:10:25) >> but it's uh (00:10:27) >> it was just it'll raise a lot lot of (00:10:29) questions. But going to um you said (00:10:31) something interesting as well. We were (00:10:32) talking about it before starting the (00:10:34) interview. (00:10:34) >> Oh, did we start the interview? (00:10:37) >> Hey guys, (00:10:38) >> is about how how social media connects (00:10:40) people. And you said this a laughable (00:10:41) promise. (00:10:42) >> It is a laughable (00:10:44) >> I see it now. It took me a while to see (00:10:46) it, but can you elaborate on this and (00:10:48) I'll tell you why. And I want to try to (00:10:50) play devil's advocate. People like me, (00:10:51) I'm not a social person. I barely go (00:10:53) out. I barely do anything. Just work and (00:10:55) and kind of I'm into longevity. So work (00:10:57) and longevity. And I have a few loved (00:10:59) ones around me. That's it. Very very (00:11:02) very few. Count them on one hand. Now um (00:11:06) the reason I I saw social media as a (00:11:08) positive thing initially was it allowed (00:11:10) me to, you know, send videos to my team (00:11:12) on on Instagram, connect to people. Um (00:11:15) not building a personal brand, that's (00:11:16) for business, but connecting to people. (00:11:19) Later I got sucked into the algorithm (00:11:21) >> and this is where it kind of leads into (00:11:23) artificial intelligence because AI is (00:11:25) kind of amplifying this risk. Um and I'm (00:11:27) starting to feel how it's dividing (00:11:29) people rather than helping. Maybe you (00:11:30) can share why that is a major concern. (00:11:32) Maybe some statistics as well um on how (00:11:35) difficult it is for the younger (00:11:36) generation to make friends to meet a (00:11:38) girl. U Bill Blackman was posting about (00:11:41) it. Um and the depression rates are just (00:11:44) going through the roof. Um, so would (00:11:46) love your thoughts on on how social (00:11:48) media is leading to more divisiveness or (00:11:50) more harm in society and humanity and (00:11:53) kind of how that's going to be amplified (00:11:54) as AI gets more and more intelligent if (00:11:57) it will be amplified. (00:11:58) >> How how much time do we have? (00:12:00) >> So so the the the core premise of (00:12:02) everything I would like to talk about in (00:12:04) technology and the core premise of my (00:12:06) theory on AI is that technology is a (00:12:09) force with no polarity. Right? So you (00:12:12) can you can use it for good and it (00:12:14) brings a lot of good can create a (00:12:16) utopia. You can use it for evil uh or (00:12:18) for you know malicious uh objectives and (00:12:21) agendas and it will bring a dystopia. (00:12:24) the the the the difference between them (00:12:26) is uh of course the intent of the (00:12:29) provider but the will of the user right (00:12:32) and so the the challenge with social (00:12:35) media is not the technology a place for (00:12:37) me to get exposed to certain content (00:12:41) is an interesting way of saying of (00:12:44) staying in touch with your friends (00:12:46) because they are um post posting in the (00:12:50) instant that was the original promise (00:12:52) right uh you know just because we're so (00:12:54) close and you know my daughter and I (00:12:56) lived you know across different (00:12:58) countries for so many years wouldn't it (00:13:00) be lovely if she shared and said hey (00:13:02) papa I'm you know with my friend Hannah (00:13:05) you know remember her right uh that was (00:13:08) the original promise then you take that (00:13:11) promise and then you somehow use the (00:13:14) tactics of the media machine the (00:13:16) propaganda machine in general uh and and (00:13:19) basically sway people to the benefit of (00:13:21) the shareholder benefit of the founder (00:13:24) benefit of the uh of basically any (00:13:26) equity holder in the business and and (00:13:28) the way to do that happens almost (00:13:31) systemically right I remember vividly at (00:13:34) the times when we were at Google uh (00:13:36) right before Larry came back as CEO (00:13:40) where uh where we were so scared that (00:13:42) we're going to become old and boring (00:13:45) right and and the reason was very simple (00:13:47) huh uh you you start your when I joined (00:13:50) Google we were accounting for most of of (00:13:52) regions uh revenue which is was close to (00:13:56) bill a billion dollars at the time on (00:13:58) Excel right uh you know yes of course (00:14:00) Google had some systems but they were (00:14:02) crude and very you know still not fully (00:14:05) automated but but but the idea was um (00:14:10) that was an organization that was driven (00:14:13) to make a massive difference to the (00:14:15) world and you know Larry always said (00:14:17) it's it's called the toothbrush test so (00:14:19) if you change the lives of people (00:14:21) positively (00:14:22) in a way that will make them use you (00:14:24) twice a day, you're going to make a lot (00:14:26) of money. Okay? And so, interestingly, (00:14:28) the money was after the fact, but then (00:14:30) you start to sit in front of the street, (00:14:33) okay? And you start to discuss your (00:14:35) results quarterly and you start to get (00:14:38) pressure that basically says, if you (00:14:40) want to continue to change the world, (00:14:42) you have to deliver on this or we're (00:14:44) going to get someone else to deliver on (00:14:45) it. Right? And it's not that you're (00:14:48) running a good business that is growing (00:14:49) reasonably. You have to beat (00:14:50) expectations and you have to surprise (00:14:52) the street and Right. And so what do you (00:14:54) do as a as a good entrepreneur who's (00:14:56) normally not good at running boring (00:14:58) stuff, right? You hire bureaucrats, (00:15:01) okay? And a bureaucrat here is not a a a (00:15:04) negatively loaded word. It's someone who (00:15:07) knows how to run something systemically. (00:15:09) Okay? And so the bureaucrats come in and (00:15:12) what do they focus on? They focus on (00:15:14) profitability. They focus on propaganda. (00:15:16) They focus on marketing so that they can (00:15:18) squeeze a little more revenue. They (00:15:20) focus, they focus, they focus and and (00:15:22) the culture of the company changes (00:15:25) because you know while the entrepreneurs (00:15:27) like myself will always try to run a (00:15:30) company with the minimum number of (00:15:31) people the bureaucrats want to hire (00:15:34) empires. So suddenly and and it's (00:15:36) actually over I would probably say four (00:15:40) years in our in my Google history where (00:15:42) the company turns from totally a startup (00:15:45) field. uh we were maybe 7,000 people at (00:15:49) the time to like oh my god this is IBM (00:15:52) you know and and once that starts to (00:15:54) happen everything changes right so it's (00:15:58) no longer about changing the world (00:16:00) primarily which is normally the the (00:16:04) actual reality of a good entrepreneur (00:16:07) uh it is uh more about let's meet the (00:16:10) streets expectations let's grow our (00:16:11) equity and the you know the our stock (00:16:14) options and so on and so forth (00:16:16) And yeah, every now and then we have to (00:16:18) keep the brand of changing the world and (00:16:20) being positive to the world uh by making (00:16:23) empty promises. Okay. And that's what (00:16:25) you see with social media uh in in a (00:16:27) very interesting way. I don't know. I (00:16:30) mean Mark Zuckerberg is not the most (00:16:32) loved person on the planet, but I don't (00:16:34) know if he was that uh if he had that (00:16:36) intention of building what he built when (00:16:38) he had Facebook. Okay. Uh you know, he (00:16:41) he probably was like, "Yeah, that's an (00:16:43) interesting idea. I'm not very social (00:16:45) myself. Maybe I can connect with people (00:16:46) on techn I don't know. Okay. As soon as (00:16:49) the company changes then suddenly you (00:16:51) become the product right and and social (00:16:54) media works against you works against (00:16:57) you significantly. It works against (00:16:59) everyone interestingly. So the content (00:17:02) provider is shaped and molded into being (00:17:04) stupid. Uh the content consumer is (00:17:07) shaped and molded into being (00:17:09) sleepwalking. uh you know the the (00:17:11) connection between us and others start (00:17:13) to fade and suddenly we call that (00:17:16) connection. Now that is not necessarily (00:17:19) a technological issue and if you know if (00:17:22) you take an even more interesting (00:17:24) example of that it's dating. So dating (00:17:27) apps you know originally we're saying (00:17:29) hey you only have access to people that (00:17:32) you meet at work or in university and (00:17:35) maybe four blocks around where you live. (00:17:37) We're going to give you access to more (00:17:38) people. So hopefully you will generate (00:17:40) more love uh you know genuine love but (00:17:44) then of course very quickly they realize (00:17:47) that the benefit of a dating app is for (00:17:49) you to continue to date forever. (00:17:51) >> Yeah the incentives are just so (00:17:52) misaligned. social media just want to (00:17:54) they need you on the app as long as (00:17:56) possible so they can advertise correct (00:17:58) >> and collect data (00:17:59) >> is it shows that so it's like we and and (00:18:02) the probably the biggest thing I learned (00:18:04) from you recently is how (00:18:07) flawed humanity is or the system that (00:18:09) humanity built is and that's why I'm so (00:18:12) concerned about AI because we're (00:18:13) building and creating AI within that (00:18:15) flawed system I'll give you I'll give (00:18:17) you I'll give the audience stats that (00:18:18) you mentioned kind of I had to verify on (00:18:21) on on (00:18:22) >> were they (00:18:23) Yeah, they were right. Yeah. And the (00:18:26) first one was (00:18:27) >> we spent, you know, humanity spends (00:18:29) trillions on the military industry, (00:18:31) military and wars. (00:18:32) >> Yeah. (00:18:32) >> If we spend 4% of that amount on ending (00:18:35) world hunger forever, we'd succeed. 4% (00:18:38) of that amount. (00:18:39) >> 4% (00:18:39) >> at 10 to 12% everyone has universal um (00:18:42) healthcare and 10 to 12%. Same amount (00:18:45) you end extreme poverty completely. (00:18:48) >> Yeah. (00:18:48) >> These are staggering numbers that are (00:18:50) accurate. If that's a system that we (00:18:52) live in now and that's how we're (00:18:54) building technologies based on human (00:18:56) greed, selfishness, (00:18:58) um, all the other flaws that we have as (00:19:01) a specy, what's the future look like (00:19:03) with AI? (00:19:04) >> Very grim. Very grim. (00:19:06) >> And I feel like, and I want you to be (00:19:08) very honest because I feel like a lot of (00:19:09) people don't want to say how grim it's (00:19:11) looking and you're starting to speak out (00:19:12) more and more. You have been for a (00:19:14) while. I feel like they're worried to (00:19:15) kind of be fearongerous. even people (00:19:17) building it, they tell me this behind (00:19:18) the scenes, but they don't want to say (00:19:20) it in an interview. Um, (00:19:21) >> yeah. No, I I I say it openly and I (00:19:23) encourage people to kindly hopefully not (00:19:26) rudely correct us. Okay. Uh, you know, (00:19:29) and because the main reason for where we (00:19:31) are today is because the biggest success (00:19:36) of the propaganda machine was not to (00:19:38) misinform you. It was to distract you (00:19:41) and pin you against your fellow human. (00:19:44) Okay? because that divide is basically (00:19:46) allowing those with a plan to rise. (00:19:49) Okay. So, so you have to imagine that (00:19:52) the where the the the most of what we (00:19:56) struggled with in the uh in in the (00:20:01) modern world uh and what we will (00:20:03) struggle with in the next few years is (00:20:06) centered around one thing only which is (00:20:08) money right and and money uh I wouldn't (00:20:12) say it's just money it's money it's ego (00:20:15) and it is a very interestingly (00:20:17) indoctrinated evil right You know, one (00:20:20) one of my favorite people to follow on (00:20:22) YouTube is I don't remember his name, (00:20:24) but he has a a channel called Predictive (00:20:26) History. He's a Chinese professor, and (00:20:29) he talks about all of the uh you know, (00:20:31) >> I think I know him. I met him. Yeah, I'm (00:20:33) going to check. (00:20:34) >> It's such an interesting thing because (00:20:35) he talks about uh the underlying reasons (00:20:39) why evil exists in the world today. (00:20:42) >> I interviewed I don't publish the (00:20:44) interview um but Yeah. Is is it a (00:20:47) Chinese gentleman? Yes. (00:20:48) >> Yeah. (00:20:48) >> Yes. Yes. I interviewed the gentleman um (00:20:50) two months ago. I haven't released that. (00:20:52) >> Yeah, it is it's it's quite eye opening. (00:20:54) They he had an episode that was uh (00:20:56) called how evil (00:20:59) is created or something (00:21:01) >> and he gives examples from uh uh the (00:21:05) Spartans, okay, the you know the 300 the (00:21:08) movie (00:21:09) >> and how they take those kids as kids and (00:21:12) how they put them into camps where they (00:21:14) are beaten and abused and then you know (00:21:16) they have to hold together and be a team (00:21:18) and then they have to you know uh (00:21:21) protect each other and then they become (00:21:23) stronger. But then they make them sleep (00:21:25) together so they are now lovers not just (00:21:27) uh you know it it's incredible when you (00:21:29) really understand that and that's (00:21:31) indoctrinated (00:21:33) uh you know this is conditioned within (00:21:36) some people since the moment they were (00:21:39) children. This is why our world today (00:21:41) have people that have the ability to (00:21:44) simply say yeah absolutely kill (00:21:46) children. Killing children as a matter (00:21:48) of fact can be conditioned through some (00:21:52) you know rituals if you want as human (00:21:54) sacrifice or as you know this is uh uh (00:21:57) you know these are not human children (00:21:59) you know this is good for humans and you (00:22:02) know how that story ends uh you know in (00:22:04) in wars like Gaza and so on and so forth (00:22:06) where we have a majority of a nation's (00:22:09) mind that says of course it's absolutely (00:22:11) okay to kill those nonhumans right and (00:22:13) when you start to see things this way (00:22:15) you realize that it is a systemic agenda (00:22:19) way more organized. This is not (00:22:20) conspiracy. This is you know way more (00:22:23) organized to to to serve the top than uh (00:22:27) you know than we make it look like. It's (00:22:29) not that there is someone that holds the (00:22:32) key to everything. But systemically, (00:22:34) directionally the world needs to go in (00:22:37) uh in a direction where more money is (00:22:40) borrowed. Understand that. Okay. more (00:22:42) money is borrowed is a very um is a very (00:22:46) interesting thing to to recognize (00:22:48) because you'd think that the way to make (00:22:51) a lot of money is to be an entrepreneur (00:22:53) to be Elon Musk. So you get a trillion (00:22:55) dollar pay package, right? Elon Musk is (00:22:58) a peasant. Peasant compared to the real (00:23:01) money, right? Where is the real money? (00:23:03) You have to understand this. you you and (00:23:05) I uh you know at at the worst of the (00:23:07) worst there are people that borrow to go (00:23:11) to university (00:23:12) >> right those people are in debt for the (00:23:14) rest of their life they work at least (00:23:16) then the first 20 years of their life to (00:23:18) just pay back the debt right (00:23:20) >> it's crazy but then those are the minute (00:23:23) they took that debt they are now poor (00:23:28) pledging that 20 years of their life to (00:23:31) get back to wealth (00:23:32) >> right there are others who don't borrow, (00:23:35) they work, they make money, they spend (00:23:37) what they get. H those are a little more (00:23:40) uh uh you know a a little less poor if (00:23:42) you want right there are those who work (00:23:46) and create assets and that those assets (00:23:49) create money for them a little a little (00:23:51) richer. There are people then like Elon (00:23:53) Musk (00:23:54) >> borrow on these assets. (00:23:55) >> Correct. Right. When the the place where (00:23:58) money starts to become meaningful is (00:24:00) when borrowing is involved. Right. So (00:24:02) Elon wants to buy uh uh Twitter. Okay. (00:24:06) He goes to a bank and he says, "Here are (00:24:09) my shares in Tesla." H they're worth I (00:24:12) don't know how much. I'll put them as (00:24:14) collateral. Give me $50 billion. I'll go (00:24:16) and buy um you know, whatever. Twitter, (00:24:21) another business, start whatever. Okay. (00:24:24) The minute he buys Twitter, he can then (00:24:26) go back to the bank and say, "Here are (00:24:28) here are my shares in Twitter." Okay. (00:24:31) lend me another $50 billion. Okay? And (00:24:34) then suddenly he's making money on on (00:24:37) assets that are not making money and now (00:24:39) his wealth continues to increase. So (00:24:42) it's the question really is how much (00:24:45) money is is is Elon making from the (00:24:48) dividends of the businesses he created (00:24:50) versus how much is he making from the (00:24:52) equity of the businesses he created from (00:24:55) the borrowing on the equity of the (00:24:57) businesses he created. That's when you (00:24:58) start to be wealthy, right? Elon and (00:25:00) anyone else. Nothing against Elon here, (00:25:03) >> but the ones that are wealthier, which (00:25:05) we never talk about, are the ones that (00:25:07) are lending him the money. Okay, the (00:25:09) bankers basically as he walks in and he (00:25:12) says $50 billion. H uh the banker says, (00:25:15) "Okay, 3% or 2% for the simplicity of (00:25:18) the of the calculation, 2% interest. So (00:25:21) that's a billion dollar uh back uh to us (00:25:24) every whatever period." And the minute (00:25:27) they gave him the money that one billion (00:25:29) is in their in their bank account just (00:25:31) unpaid but it has to be paid back right (00:25:34) and these are not even they have done (00:25:36) nothing to earn that money. He just (00:25:38) walked in they gave him the money either (00:25:41) from their deposits or from fractionary (00:25:43) reserve of course and then they made a (00:25:46) billion dollars for doing nothing. Okay. (00:25:49) But they are not the richest people. Who (00:25:51) are the richest people? That's where the (00:25:53) trick is. The richest people are those (00:25:55) who create the $50 billion that Elon (00:25:58) borrowed out of thin air. Okay? (00:26:02) So, you walk into a a bank today, you (00:26:06) ask for a 2 million dirhams mortgage or (00:26:08) $2 million mortgage, right? What does (00:26:10) the bank do? They don't go into the (00:26:12) vault and count two bill million dollars (00:26:14) and give them to you. They literally (00:26:17) create them out of thin air on fra on (00:26:21) fractional reserve. Right? So what does (00:26:23) that mean? It means that they never had (00:26:25) that money, but the minute they created (00:26:27) it on fractional reserve, it's now owed (00:26:30) to them. You have to work for the rest (00:26:32) of your life or the society has to work (00:26:34) for the rest of their lives to pay it (00:26:36) back. (00:26:37) >> So start counting how much debt was (00:26:40) created since 1910 and you realize that (00:26:43) Elon by far is not even near the richest (00:26:45) man in the world, right? Neither is uh (00:26:48) Larry Allison. None of those the the (00:26:50) real money hundreds of trillions of (00:26:53) dollars are all are all those owed to (00:26:56) the central bankers to the federal uh (00:27:00) banks right and and and now you (00:27:03) understand that if if the if the ma the (00:27:05) biggest way to create money is to lend (00:27:08) it (00:27:10) then what is the benefit of those people (00:27:13) maximize lending what's the highest the (00:27:16) most interesting way to maximize lending (00:27:18) create wars. (00:27:22) All right. So, okay. So, then you're (00:27:25) making me even more worried based on the (00:27:27) question. If this is the system we live (00:27:28) in, and I know you've talked about how (00:27:31) the system of the military-industrial (00:27:32) complex works, it's even scarier than (00:27:34) what I initially thought because I think (00:27:36) you start talking. I'll let you kind of (00:27:37) cover that. Is that to to use weapons is (00:27:41) cheaper than destroying weapons as you (00:27:43) create new weapons with technological (00:27:45) advancements. And that's going to happen (00:27:46) a lot now with AI and drones. But what (00:27:48) really worries me is if we're creating (00:27:50) AI, this form of intelligence in that (00:27:53) flawed world, you talk what got me my (00:27:56) got my attention was when you talk about (00:27:57) teaching ethics to AI. (00:27:59) >> Yeah. This is either the ethics we live (00:28:01) by. (00:28:02) >> So AI is the new nuclear bomb, (00:28:06) >> right? It's it's showing up in our world (00:28:09) at a time where the empire is (00:28:11) collapsing, right? Everyone realizes (00:28:13) that the US is struggling. 37 billion (00:28:16) trillion dollars of debt now. Um Trump (00:28:18) borrowed another trillion in the first (00:28:20) year of first nine months, right? And (00:28:22) he's promising to borrow even more. Good (00:28:25) boy. Okay. Now, the the the idea is with (00:28:29) all of that borrowing with all of the (00:28:31) that in the consumer space of uh of the (00:28:34) US and so on, with all of the awakening (00:28:37) that people that the world around the (00:28:39) world, everyone now realizes, oh, (00:28:41) everyone's been every single person (00:28:43) that's been killed in a war in the last (00:28:45) in my lifetime. uh every single leader (00:28:48) that was you know thrown out in a coup (00:28:50) in the my in my lifetime uh every single (00:28:54) uh leader that obeyed in my lifetime (00:28:56) obeyed because the the US had an (00:28:59) influence right and so it's an (00:29:02) interesting analogy that people need to (00:29:04) understand it's it's a bit like this uh (00:29:07) you know when you're when you're in (00:29:10) school okay and you know we all turn 11 (00:29:13) and one of the kids is starting to (00:29:15) become a little taller than everyone (00:29:16) everyone else and that kid becomes the (00:29:18) bully. Okay, that's 1944. Uh, you know, (00:29:21) you had the bully in a in a red, white, (00:29:24) and a white and blue she t-shirt. Okay, (00:29:27) uh, you wait a little bit until we're 16 (00:29:30) and another boy becomes, you know, 6'8, (00:29:34) okay? Massive, but very kind or at least (00:29:38) not harmful, not not hurting anyone, (00:29:41) okay? And yet the other bully still (00:29:43) remains believing that he's the bully. (00:29:46) He has his little gang. He's trying to (00:29:48) protect his position. And that's what (00:29:50) happened. We have a boy in a a red (00:29:52) t-shirt called China that is now as big (00:29:55) if not bigger, way bigger economically (00:29:58) than the US. Now, of course, the reason (00:30:00) why uh people claim that the US economy (00:30:03) is the largest economy in the world is (00:30:04) for two reasons. One is GDP is measured (00:30:07) in US dollars and the second is someone (00:30:10) convinced us that part of GDP which is (00:30:13) economic prosperity includes (00:30:15) consumption. So to to to you know (00:30:20) run through things and consume things is (00:30:22) good for the economy. Okay. And 64 to (00:30:25) 70% of the US economy is consumption. (00:30:28) Interesting, huh? for wi with with with (00:30:30) a population that's probably 20% of of (00:30:33) China. (00:30:35) What that means is (00:30:38) uh uh if you turn China's economic power (00:30:42) to purchasing power parity not in US (00:30:45) dollars okay actually how much economic (00:30:49) prosperity can be created not consumed (00:30:52) with the Chinese economic machine (00:30:54) they're way bigger than the US okay but (00:30:56) the Chinese don't wedge you know don't (00:31:00) wage wars around the world that's (00:31:02) something we've never actually seen (00:31:04) since you know uh I don't know which (00:31:06) dynasty but they they rarely ever leave (00:31:10) China. There has been quite there has (00:31:12) been I think five exceptions (00:31:13) >> very rare I've looked into it because (00:31:15) >> yeah they they and they were all border (00:31:17) disputes. Okay. And some of them were (00:31:19) like a week of hey this is my my part. (00:31:23) Okay. uh but that doesn't mean they (00:31:26) don't wage economic wars, right? And and (00:31:29) the Chinese way of uh of declining the (00:31:33) empire is actually really interesting. (00:31:35) They are (00:31:38) it's it's death by a thousand cuts. (00:31:40) Okay. It's the tariffs followed by the (00:31:43) rare um you know the earth metals uh (00:31:47) ban. It's (00:31:48) >> and then weakening the US through Russia (00:31:49) as well cuz they're (00:31:52) bricks. Mhm. Uh it is uh you know at a (00:31:55) point in time trade that is not US (00:31:57) dollar based which would completely (00:31:59) destroy the country. (00:32:00) >> They're doing that a lot with the Middle (00:32:00) East and Latin American countries. (00:32:02) >> Correct. Or and across bricks it will (00:32:04) you know and we can talk about that but (00:32:06) we're talking about AI today. Uh the (00:32:09) idea is that the biggest weapon the US (00:32:11) has ever had was the US dollar. Right? (00:32:13) Because basically it enables them to (00:32:15) create that trillion dollar war machine (00:32:17) for free. they can just print the money (00:32:19) while everyone else has to actually work (00:32:22) for it. Now, (00:32:24) >> uh what that means is that an empire in (00:32:27) decline needs another nuclear bomb. They (00:32:30) need to prove to the world that they are (00:32:32) the leaders that can actually get (00:32:34) everyone to stop in their tracks. And (00:32:36) that nuclear bomb unfortunately is (00:32:38) artificial intelligence, artificial (00:32:39) super intelligence. and and whoever (00:32:42) gains control on uh AGI or ASI first (00:32:47) with enough uh buffer they would (00:32:50) literally uh be the masters of the (00:32:53) universe right now here's the (00:32:55) interesting thing the interesting thing (00:32:57) is uh the US does it their way okay and (00:33:02) China is admirably doing it in a very (00:33:07) different way okay and by the way I'm (00:33:09) not pro- China or pro America. I am anti (00:33:14) the American abuse of the world. And I (00:33:16) say that publicly. Uh you know, we all (00:33:18) love America. We all love Americans. I I (00:33:21) I have countless American people that I (00:33:23) want prosperity for that are my dear (00:33:25) friends and even family, right? But but (00:33:28) this administration, this this (00:33:30) government approach of we're going to (00:33:32) bully the whole world, the whole world (00:33:34) is starting to say, "Please, can can we (00:33:36) be friends?" Right? Do you really have (00:33:38) to abuse me? you really have to uh uh (00:33:41) you know uh terrorize me if I can use (00:33:43) the word China is so America you know (00:33:47) does it the only way Altman's know how (00:33:49) to do it which basically is a Stargate (00:33:52) like let's put $500 billion into a (00:33:55) project build massive infrastructure (00:33:57) build AI that looks amazing da da da da (00:34:00) da right uh the Chinese on the other (00:34:03) hand which you don't even hear about you (00:34:06) don't you know you two weeks after (00:34:08) Stargate (00:34:09) $500 billion. Trump is signing it with (00:34:11) Larry Allison and and Sam Altman and (00:34:14) Soft Bank, right? And then they drop (00:34:16) Deep Seek R3 uh as as powerful as Chad (00:34:21) GPT40 at the time opensource (00:34:25) edge on the edge. Basically, they're (00:34:27) they're telling you, "Yeah, you can (00:34:29) download it and run it on your phone or (00:34:30) your your your personal computer and it (00:34:33) will run fine." (00:34:35) And we don't want to make any money out (00:34:37) of it. You have to look deeper into what (00:34:39) that strategy means. They're basically (00:34:41) nullifying the market. They're basically (00:34:44) saying, look, (00:34:44) >> you know, is if you want to compete, (00:34:48) >> we're not going to make it a (00:34:49) competition. There is no competition (00:34:51) there. This is available for everyone. (00:34:52) So, you can spend your $500 billion, you (00:34:55) can pretend that you're going to make a (00:34:57) big difference, but people eventually (00:34:59) will take it for free. Okay? And and (00:35:02) that strategy bleeds the, you know, as I (00:35:04) said, it's death by a thousand cuts. the (00:35:06) the the the whole idea is it bleeds the (00:35:10) bully a little more. How does the bully (00:35:13) react? They become more aggressive. And (00:35:16) we are in a place where I'm I'm going to (00:35:19) get to your question now finally. I mean (00:35:21) the context is really important because (00:35:22) when I and Vinard Kosla I interviewed (00:35:25) who's an early investor in open AI very (00:35:26) very early one of the first and when I (00:35:28) asked him what's his biggest concern (00:35:29) that was a few months ago it wasn't (00:35:30) about um super intelligence and what AI (00:35:33) would you know unemployment instability (00:35:35) social unrest his biggest concern was (00:35:37) China winning that race so you giving (00:35:39) that context and how China's playing the (00:35:41) game versus the US is really important (00:35:42) >> I I I I genuinely believe that China (00:35:45) will win this race right for many (00:35:46) reasons one of them is America never as (00:35:49) they invested in the uh in the (00:35:51) military-industrial complex they didn't (00:35:54) invest in infrastructure so they don't (00:35:55) have the power to run those mach those (00:35:57) machines right uh it's because uh as I (00:36:02) said China's strategy seems to be they (00:36:04) never publicly said that seems to be to (00:36:06) nullify the game right and and more (00:36:09) interestingly it's because you know if (00:36:11) you take sycamore uh Google's uh quantum (00:36:14) computer versus uh you know I I don't (00:36:18) actually remember the name of the of the (00:36:20) Chinese quantum computer. (00:36:21) >> Was it by Alibaba or no? (00:36:23) >> Yeah, it was either by Alibaba or one of (00:36:25) them. Uh it's uh it's 5.9 billion times (00:36:29) faster (00:36:30) >> than Google's one. (00:36:31) >> Yeah. (00:36:33) Right. But they don't (00:36:34) >> What does that what does that mean to be (00:36:35) 5? (00:36:36) >> Correct. What does it mean? Right. So So (00:36:38) there are there are so many uh ways you (00:36:42) can win that race. Mhm. Uh, America (00:36:46) always puts it in the propaganda (00:36:49) machine. China rarely ever talks about (00:36:51) it but wins it over and over and over (00:36:53) and over. Okay. The the massive size of (00:36:56) their AI infrastructure for um supply (00:36:59) chain. Okay. Their massive size of of of (00:37:02) AI infra it's it's not open AI and chat (00:37:05) GPT. It's not fancy and it doesn't tell (00:37:07) you oh my god you're the most amazing (00:37:08) person in the world like Czech GPT will (00:37:10) always do. Okay. But it's effective. (00:37:13) It's the same way the Chinese are doing (00:37:15) it. Now, here's here's the the core (00:37:17) issue. The core issue is someone will (00:37:21) win. Okay? And that someone (00:37:24) unfortunately might not win in (00:37:26) everything. So, you can see that the (00:37:29) arms race is in the language models. (00:37:31) It's not really. Okay? Is there an arms (00:37:33) race in autonomous weapons? Of course. (00:37:35) Is there an auton arms race in in (00:37:38) supercomputing? Of course. Is there an (00:37:40) arms race in chips and chip (00:37:41) manufacturing? Okay, of course, you (00:37:44) know, and America uses its its weapons (00:37:47) by banning the, you know, the latest (00:37:49) Nvidia chips from China. Uh, and then (00:37:52) China responds by saying, "Okay, we're (00:37:53) going to make our own, which is going to (00:37:54) be 10 times cheaper than yours." And and (00:37:56) so on. And and all of those wars (00:38:00) lead to a very unusual dichotomy, first (00:38:04) time in human history in my assessment, (00:38:06) which is a a dichotomy of power. So (00:38:10) you're you're you're going to see in the (00:38:12) next 10 years two things happening at (00:38:14) the same time. One is a concentration of (00:38:16) power (00:38:17) >> for those who are able to build (00:38:20) competitive leading platforms right uh (00:38:24) which unfortunately are not many from (00:38:26) among the companies it it's going to be (00:38:28) open AI or anthropic or Google and so on (00:38:30) and so forth and the race is even (00:38:32) becoming smaller from nations it's only (00:38:34) China and you know and and America and (00:38:36) here in the UAE and in Saudi and so on (00:38:39) we may be able to beat the rest of the (00:38:41) way (00:38:41) >> and Japan are trying to catch up pretty (00:38:42) quickly as well (00:38:43) >> they they Uh yeah, Europe is lost and is (00:38:46) is even regulating itself even more. (00:38:49) >> They're regulating an industry that (00:38:50) almost doesn't exist for (00:38:52) >> correct. Right. Uh and and and so it's (00:38:54) quite interesting. They'll get that (00:38:55) concentration of power. Very few pe the (00:38:57) players will have massive power. Okay. (00:39:00) And then you'll get a democratization of (00:39:03) power at the same time. Why? Because I (00:39:06) my my current startup is basically (00:39:10) uh me and my co-founder and eight AIs. (00:39:14) Right. And so I can build an incredible (00:39:16) thing that will completely disrupt the (00:39:18) dating industry, okay? A multi-billion (00:39:20) dollar, multi-billion user uh industry (00:39:24) in 8 weeks. (00:39:25) >> Okay. Uh and and it it applies across. (00:39:29) So So you you go again and you go like, (00:39:32) okay, so Nvidia's advantage on the (00:39:34) chips, China then has the advantage on (00:39:37) the model with Deep Seek and says, run (00:39:39) it on a small chip. Doesn't matter. (00:39:40) Okay. uh you know you you get the (00:39:42) advantage on interestingly on autonomous (00:39:45) weapons. So America will invest in (00:39:48) running an an F-16 using an AI but the (00:39:52) Houthies will use a drone that also runs (00:39:55) on AI (00:39:56) >> fraction (00:39:57) >> and cost $3,000, right? And and now you (00:40:00) start to see that this is it's an (00:40:03) interesting mess. Europe was Europe was (00:40:06) spending a million dollars per missile (00:40:07) to shoot down $20,000 drones by Russia (00:40:10) over the last few weeks. (00:40:11) >> Correct. And and that's ex that was (00:40:13) exactly Iran's way when they they bombed (00:40:16) the Iron Dome of Israel. It's like, (00:40:18) okay, let's flood it with cheap weapons. (00:40:21) >> Okay. And they run out of missiles. (00:40:23) >> Yeah. Economic war. (00:40:25) >> And and it is quite interesting because (00:40:27) in all honesty, when we're done with (00:40:30) this interview, you and I can spend an (00:40:32) hour together here and we'll build (00:40:33) whatever we want. Yeah, (00:40:34) >> it's incredible AI wise. And by the way, (00:40:39) the the beautiful thing is when I built (00:40:42) Emma, I don't need CH GPT50. (00:40:46) I have sufficient intelligence in any of (00:40:49) the super of the open source models, (00:40:51) right? So all of the above super (00:40:54) intelligence is not going to prevent the (00:40:56) democratization of some form of (00:40:58) intelligence. (00:41:00) >> Will that be? So that democratization is (00:41:02) exciting for entrepreneurs like us (00:41:04) because there's a lot that would be done (00:41:05) in a very short period of time. (00:41:06) >> Correct. (00:41:07) >> As AI replaces things that would usually (00:41:09) cost a lot of money and you'll be able (00:41:10) to compete with the incumbents. Um (00:41:15) innovators dilemma works in your (00:41:16) advantage. (00:41:18) But then what? Because afterwards what's (00:41:20) your edge? Your edge is able to use (00:41:22) these tools that big companies don't use (00:41:24) and they kind of stuck in their own (00:41:25) ways. You know one of my companies has (00:41:27) over 200 employees and we're struggling (00:41:29) to start cutting costs. It's very hard (00:41:31) to break down a system. So, one of our (00:41:33) executives is re rebuilding some of the (00:41:35) systems we have from scratch like an (00:41:37) entrepreneur. So, all these bigger (00:41:39) companies that have thousands of (00:41:40) employees, it will be very hard for them (00:41:41) to adapt to a world where you and AI (00:41:44) could disrupt a three, four, five (00:41:47) billion dating app. But once we're past (00:41:50) that stage, what is your edge? Because (00:41:52) if you've got an agent that helps you (00:41:54) build a business, well, everyone has an (00:41:56) agent now. So, you're not you no longer (00:41:58) have an edge. And then it becomes kind (00:41:59) of a battle for a battle of energy. So (00:42:03) these agents just need energy to (00:42:04) operate. And the more energy you can (00:42:05) feed them, the more they can operate, (00:42:07) the faster they can operate. And it's no (00:42:09) longer the one that has the smartest (00:42:11) LLM. The difference between Deepc and (00:42:14) Chat Gupt and Gro is getting smaller and (00:42:16) smaller, very incremental, (00:42:18) but it feels like it's becoming a power (00:42:20) of energy. Who has more energy to feed (00:42:22) their LM will win that. And that leads (00:42:25) again goes back to concentration of (00:42:26) power. Do you see where my concern is (00:42:28) coming from? If you can break it down (00:42:29) and maybe tell me I'm wrong because that (00:42:30) will be reassuring. (00:42:32) >> No, you're not. But you're measuring it (00:42:33) within the current system. Okay. I think (00:42:36) the challenge that most people (00:42:39) don't and I don't know the answer. We (00:42:41) can brainstorm about it together. It's, (00:42:44) you know, the challenge is quite (00:42:45) interesting. We have lived, you and I (00:42:48) were born, we grew, we succeeded, we (00:42:50) failed, we did everything. And everyone (00:42:51) that you know within a capitalist system (00:42:55) that is about to be erased. Okay, it's (00:42:57) the very underlying system of everything (00:43:01) that you know that's changing. Okay, and (00:43:04) that's what makes it incredibly (00:43:05) difficult to understand what's going to (00:43:07) happen. Let me explain. (00:43:10) It doesn't matter if you're going to (00:43:12) manage to cut costs in your organization (00:43:14) or not. I call it the fourth inevitable. (00:43:17) you're either going to cut costs and and (00:43:20) replace some people with AIs and succeed (00:43:23) or you're going to be to lose and become (00:43:25) irrelevant and shut down. Okay? So, (00:43:27) think of it as a prisoner's dilemma. If (00:43:29) you're a a law office, okay, and your (00:43:32) competitor starts to use parallegals (00:43:34) that are AI, that are way more, you (00:43:37) know, uh uh intelligent, way quicker, uh (00:43:40) have a much more um you know, a a more a (00:43:44) vast database where, you know, a human (00:43:47) would take years to read and give them (00:43:49) amazing reporting so that the lawyers (00:43:51) can go and and and win cases. your (00:43:55) competitor is going to either have to (00:43:57) apply that and get rid of all (00:43:59) parallegals or they're going to lose (00:44:01) enough cases to be to run out of (00:44:03) business. Okay? And that applies to (00:44:04) everything. If you know if you're an (00:44:06) army that is applying that that's you (00:44:08) know uh um acquiring autonomous weapons (00:44:12) at speed versus an army that isn't, the (00:44:15) other army is lost. It surrenders or it (00:44:18) has to compete. Right? So eventually (00:44:21) everyone will have to hand over to the (00:44:23) machines. But they hand over to the (00:44:24) machines in a system that is a postc (00:44:29) capitalist system. Why? Because think of (00:44:32) it this way. (00:44:34) Everything you and I know about the (00:44:36) world of today is built on labor (00:44:38) arbitrage. Right? Labor arbitrage is (00:44:41) simply you and I sit down uh you know we (00:44:44) use everything that is around us is made (00:44:48) by a human that was paid less than the (00:44:50) price we s we paid for it. Okay. uh (00:44:54) everything uh from the very beginning of (00:44:57) mining metals to designing products to (00:45:00) shaping them to everything is a (00:45:02) capitalist set that somehow said I'm (00:45:05) going to pay you a,000 and your work is (00:45:08) going to be sold for 1,200 right uh if (00:45:12) AI replaces all the jobs you know the (00:45:15) only answer we know so far is UBI (00:45:17) universal basic income so somehow (00:45:19) governments and we can talk about which (00:45:21) governments are probably going to do (00:45:23) that reasonably well and which will not (00:45:25) and and that will surprise you. (00:45:27) >> Will use as a tool of control. (00:45:28) >> Correct. Okay. And and it will surprise (00:45:30) you that you know unlike the western (00:45:33) view of things that the eastern (00:45:35) countries will probably fare better but (00:45:38) let's go back to that. The idea is when (00:45:40) UBI is out there (00:45:43) uh nobody (00:45:46) on on UBI is going to be upgrading their (00:45:50) phone every year anymore. Okay. Nobody (00:45:52) on UBI is going to be, you know, swiping (00:45:55) a page for Ferraris. Okay. Uh, you know, (00:45:58) no and so on. And and the idea is when (00:46:01) UBI hits, whether you were the partner (00:46:04) in a law firm or the parallegal in the (00:46:06) low firm, now that you're not adding (00:46:09) value through your productivity, you're (00:46:11) all paid the same UBI, (00:46:13) >> right? So, the economic purchasing power (00:46:16) of humanity is about to decline (00:46:18) massively. Okay? And so, you're going to (00:46:20) see two waves. one wave where uh (00:46:24) the productivity gains of those using AI (00:46:27) and disrupting businesses and acquiring (00:46:29) more market share because of AI is going (00:46:31) to make those people very successful (00:46:34) while not everybody's out of a job yet. (00:46:36) Okay. And then eventually as more and (00:46:39) more and more people are not getting (00:46:41) income that economy in total in its (00:46:44) totality starts to change. And so when (00:46:48) you when when you when you ask the (00:46:51) question, so what happens after I build (00:46:54) a unicorn that disrupts the dating (00:46:57) industry? It's quite interesting that (00:47:01) before, I'd probably say the 1760s, (00:47:06) definitely before the 1900s, (00:47:08) business was not driven by a business (00:47:10) plan. It wasn't driven by how much money (00:47:13) will I make, how many people will I (00:47:15) abuse in labor arbitrage. That wasn't (00:47:17) it. It was built by I can make shoes, (00:47:20) okay? And I need eggs and you know, we (00:47:24) don't have to grow a GDP. We don't have (00:47:25) to do anything. Just give me eggs and (00:47:27) I'll give you shoes and everything's (00:47:28) fine, (00:47:29) >> right? And it's quite interesting that a (00:47:32) post capitalist world might look (00:47:34) extremely similar to this where because (00:47:38) of productivity gains h uh everything (00:47:42) becomes (00:47:44) practically free. Okay, you can produce (00:47:46) anything on demand h on location and and (00:47:51) it and it really is a a question of I (00:47:55) can I've I've completely disrupted (00:47:58) supply and demand on both sides because (00:48:01) on one side I can I can create infinite (00:48:03) supply almost free and on the other side (00:48:06) I took away the entire demand by by (00:48:08) reducing the economic livelihood of (00:48:11) those that were working and making (00:48:12) money. Okay. Without an intervention (00:48:16) that changes that h there is going to be (00:48:19) a lot of pain and a lot of dystopian (00:48:21) times. I I as I always predict you know (00:48:24) publicly predict I say 12 years (00:48:26) >> right 12 to 15. (00:48:29) But even with that my belief is that (00:48:32) eventually you're going to have to to (00:48:35) land in a place where money doesn't mean (00:48:36) anything at all. Right? where basically (00:48:40) uh you get what you need to live and (00:48:45) it's not money that is driving (00:48:48) the entertainment in your life or the (00:48:50) you know the joy in your life. You're (00:48:52) going to go back to the to the pre-c (00:48:54) capitalist world where what do I really (00:48:57) need to live Mario? Do I you know do I (00:49:00) really need a fancy car or do I need to (00:49:02) get from A to B? Does B have to be in (00:49:05) Sydney? Right. and and somehow you fall (00:49:09) back into a world where all production (00:49:11) is centralized (00:49:13) which originally was centralized to (00:49:16) nature (00:49:17) and then (00:49:18) >> back in the hunter gather (00:49:19) >> but back in the huntergatherer years and (00:49:22) all consumption is reasonable. (00:49:25) >> Yeah. (00:49:26) >> Because nobody has the money to spend on (00:49:28) anything. Now that's my utopian view of (00:49:30) it. My utopian view of it is you're (00:49:32) going to and I know this will upset a (00:49:35) lot of people. you're going to create (00:49:36) communism that works. Okay. Uh (00:49:39) >> that's what UBI, everyone's talking (00:49:41) about UBI being a solution. UBI is a (00:49:43) form of communism. Yeah. (00:49:44) >> 100%. Right. And that's why (00:49:47) ideologically the West will really (00:49:50) struggle perhaps other than places like (00:49:51) Norway or Finland and so on. The West (00:49:54) will ideologically say, you know, I (00:49:58) okay, I'm going to give people UBI (00:50:00) because I don't want them to revolt in (00:50:02) the streets, right? uh I'm going to (00:50:04) charge those producers the massively uh (00:50:08) uh you know the massive new trillion (00:50:10) dollar companies uh uh some taxes (00:50:14) >> say 40%. H but then those companies (00:50:18) become so powerful that they come to the (00:50:20) the government the next year and say why (00:50:22) 40 38 35 32 right 15 and then what does (00:50:28) h what what happens to the people is the (00:50:31) government is forced like we see today (00:50:32) in capitalist societies the money is (00:50:34) flowing to the top the suffering is (00:50:36) flowing to the people okay and there is (00:50:38) a point at which people will say we (00:50:40) don't like this anymore okay and so the (00:50:43) government has one of two choices I I (00:50:45) promise I'm not going to get any more (00:50:46) dystopian than this. Okay. (00:50:48) >> But you're not you're so what I'm what (00:50:50) I'm worried is that you're you're not (00:50:51) being you're not you're being very (00:50:53) realistic about it or that's the only (00:50:56) other path. (00:50:56) >> Yeah. That that's the only logic I know (00:50:58) and I would urge our viewers to teach us (00:51:00) other alternatives. (00:51:01) >> I'm trying to find someone that's (00:51:03) someone intellectual that can actually (00:51:04) talk about Peter Dantis is one person (00:51:06) that talks about I know you and him were (00:51:08) on a show. I interviewed him as well cuz (00:51:09) I wanted to get his abundance mindset (00:51:11) which was really interesting. (00:51:12) >> I just not could not relate to it. Like (00:51:14) you're talking about communism as UBI is (00:51:16) communism. Communism great in theory (00:51:21) great system but wrong species just not (00:51:23) good for humans. So that how (00:51:27) how would humans function in such a (00:51:30) system because it hasn't worked well (00:51:31) historically. That's what worries me. (00:51:32) >> Correct. And and I think that always (00:51:34) points back to the same thing that we're (00:51:36) not thinking enough about this. Right. (00:51:38) And and and the whole challenge is you (00:51:41) know Peter is right. Peter Demandis's (00:51:43) work around abundance. He has another (00:51:45) book coming out that I reviewed which is (00:51:47) incredible. The whole idea is yes, we (00:51:50) will have a world of total abundance. So (00:51:53) basically communism that works or nature (00:51:55) that works even better. (00:51:57) >> Okay, where you can walk to a tree and (00:52:00) pick an apple and walk to another tree (00:52:01) and pick an iPhone. Okay, because you (00:52:03) can from with with enough intelligence (00:52:05) you can use nanopysics for manufacturing (00:52:08) instead of parts uh for manufacturing. (00:52:11) right now. It's it is quite interesting (00:52:13) that this world is at our fingertips. We (00:52:16) can actually create it. But the reason (00:52:19) we're not going to create it is because (00:52:21) of the shades of the capitalist system (00:52:24) and the capitalist mindset that we live (00:52:26) in today. (00:52:27) >> Okay, here's the real question. The real (00:52:30) question is and and I and I jokingly say (00:52:32) that. I say, "Can we go to all of the (00:52:35) rich people and say, we're going to buy (00:52:38) all of you as many yachts and you as you (00:52:40) can be uh every year, okay? You need 365 (00:52:44) yachts, one every year. We're going to (00:52:46) build them all by AI, give them all to (00:52:48) all million of you, no problem at all." (00:52:50) Okay? Just let the rest of the world (00:52:51) live. (00:52:53) But this, in my view, is not going to (00:52:55) come without pay. And and I have to (00:52:58) admit that and I and I'm saying I'm not (00:53:01) going to get any more dystopian than (00:53:02) this that the only option that (00:53:05) governments have which they have used (00:53:08) before is to start lots of wars, (00:53:11) right? Lots of wars that basically one (00:53:15) distract the people from the domestic (00:53:17) issues by pinning a a you know a foreign (00:53:21) scary uh scarecrow, right? but also to (00:53:26) draft people to those wars which we have (00:53:28) seen before. The idea is if if the US (00:53:32) continues to collapse the way it is (00:53:34) collapsing, if the media machine, the (00:53:36) propaganda machine continues to pin (00:53:38) people for divide, which is so sad (00:53:41) because you and I know how wonderful (00:53:43) most Americans are. The the the point is (00:53:48) if they continue to do that and that (00:53:51) erupts into local conflict or civil uh (00:53:54) unrest of some sort, the only (00:53:56) alternative the government has for the (00:53:58) for society not to collapse is to say (00:54:00) we're all going to to fight against (00:54:02) Russia. Let's unite everyone against uh (00:54:05) you know the Middle East. Let's unite (00:54:07) everyone against China. (00:54:09) >> Yeah. and and and and this is not just (00:54:12) by the way this is not just uh uh driven (00:54:15) by by you know civil unrest. It's also (00:54:20) driven by a need to replace their (00:54:23) arsenal (00:54:24) >> which is which is some of the biggest (00:54:27) issues in our world today. (00:54:28) >> Yeah. Because you got trillions of (00:54:30) dollars worth of weaponry sitting there (00:54:31) and it's getting outdated. (00:54:32) >> 26 trillion specifically again use AI. (00:54:36) Huh? Use AI. I did a I did a deep search (00:54:38) on on on how how much okay and how long (00:54:43) would it take the US to replace that (00:54:45) arsenal but also the complexity of (00:54:47) replacing it because for the US you know (00:54:50) to to replace their uh tankers for (00:54:53) example they have to uh first remove all (00:54:57) of the explosive bits remove every IP uh (00:55:00) related uh thing you know either store (00:55:02) those in a safe way or destroy them in a (00:55:04) safe way then take all the metal and (00:55:07) either scrap it or leave it in the in, (00:55:09) you know, the Nevada desert or (00:55:10) something. Okay? And that's a very (00:55:12) expensive process. Or you can just (00:55:14) explode it in Gaza. Okay? And and on (00:55:17) that on top of that, you have to get (00:55:19) Congress approval for budget increases. (00:55:22) Or you can say, well, we gave it to (00:55:24) Gaza, gave it to Israel, okay? We gave (00:55:27) it to Ukraine. And and the whole idea (00:55:30) there is that the the the the (00:55:31) military-industrial complex because of (00:55:34) AI, believe it or not, has this new (00:55:37) replacement cycle. Just like when we (00:55:40) moved from vinyls to cassettes and (00:55:42) cassettes to D to to CDs and CDs to uh (00:55:45) you know, (00:55:48) rentals and you know, and so on. Every (00:55:51) time that replacement cycle happened, (00:55:53) the the music industry uh made a ton (00:55:57) replacing what you had. (00:55:59) >> You talked about the abundant world that (00:56:01) Peter Dmenz talks about very eloquently (00:56:03) and that we can create this world (00:56:04) technologically we can but and then you (00:56:07) talk about the capitalist system that we (00:56:09) have is why you're concerned about (00:56:11) whether and how we will create that (00:56:13) world. And I'm going to add another (00:56:14) layer to it is how we are as a specy. (00:56:17) Yeah, we we've had the opportunity to (00:56:18) create an abundant world. Even today (00:56:20) with the technology we have today, we (00:56:22) talked about the stats earlier. If we (00:56:24) just stop all these wars and put all (00:56:25) that money to end poverty, it'll be a (00:56:27) sounds like an incredible world. I think (00:56:29) everyone would would agree with. Then (00:56:30) why aren't we doing it? Like if you're (00:56:31) listening to this, ask yourself a (00:56:33) question right now. We could stop the (00:56:35) wars, draw whatever lines on the maps, (00:56:39) live together happily after, and just (00:56:40) start ending poverty, focusing on the (00:56:42) things that matter. And we're not doing (00:56:45) that. So then my question to you is that (00:56:47) as we create AI and eventually becomes (00:56:49) more intelligent than us. You talk about (00:56:51) teaching ethics to AI. (00:56:52) >> Yes. (00:56:53) >> But who are we? You know, we're playing (00:56:55) God in a way and we don't seem to we (00:56:57) seem to be pretty flawed to be God. (00:56:59) >> We're not. We're not. Mario, you're a (00:57:02) wonderful person. And almost everyone (00:57:05) you know is a wonderful person. (00:57:06) >> But then together we seem not to be that (00:57:07) wonderful. Even me. Look, I I'm going to (00:57:10) disagree on that point. I'm a wonderful (00:57:11) person. I could I can only talk about (00:57:14) myself. I could have bought a less (00:57:16) expensive suit, come with a shortened (00:57:18) t-shirt and sent that money to help (00:57:20) people like I criticize myself that I (00:57:22) can help more. You know what I mean? (00:57:23) >> The difference between a wonderful (00:57:24) person and a bad person is hurting (00:57:27) others. (00:57:28) >> Okay. So, so let's define how many (00:57:31) people in the world do you believe would (00:57:34) actually kill a child? (00:57:36) >> Okay. (00:57:36) >> Percentage wise. (00:57:38) >> Okay. The problem is that the problem (00:57:40) with our world today is that social (00:57:42) media and mainstream media is putting (00:57:46) those people in the spotlight. Okay, the (00:57:49) most evil of us are 1%. (00:57:52) Okay, 1% is a lot of people uh you know (00:57:56) if you say 8 billion people count the (00:57:59) numbers that's millions and millions of (00:58:02) bad people. Okay, now the trick is this. (00:58:05) Our world is on decline (00:58:09) not because humanity is flawed. Humanity (00:58:13) is divine in every possible way. Any any (00:58:17) being that is able to feel love is by (00:58:21) definition not of this world. Okay? And (00:58:24) I say that and I'm not a hopeless (00:58:26) romantic. I'm a very serious geek. We (00:58:29) are such a beautiful species. We are uh (00:58:33) either confused or made to be confused. (00:58:38) Okay, we are either idle h or made to (00:58:43) sit back and do nothing. Okay, and by by (00:58:46) do nothing I mean just tweet back and (00:58:49) forth and fight with everyone and (00:58:50) disagree with everyone. And you always (00:58:52) have to follow the money and ask why why (00:58:56) are we, you know, distracted with social (00:59:00) media? Why are we pinned against each (00:59:02) other? Why are we uh uh you know told I (00:59:06) even and I and I don't know if if I (00:59:08) should say all of those things. You have (00:59:10) to ask yourself the question (00:59:14) does the Israeli media machine that's (00:59:16) the massive the most the biggest (00:59:19) propaganda machine in history (00:59:22) has it actually lost the plot and so (00:59:24) this is why we know about Gaza? Of (00:59:26) course not. Of course not. If they (00:59:29) wanted to control this, they would have (00:59:30) controlled this. Okay. The the the what (00:59:33) is happening is a justification for hate (00:59:36) so that the world is more divided. Okay. (00:59:39) So that you move from the you know the (00:59:42) the the brainwash of the people of (00:59:46) Palestine are not humans, they're (00:59:47) terrorists and so on to the brainwash of (00:59:50) all Jewish people are bad. Both are (00:59:52) (00:59:53) >> right? But that that divide is what gets (00:59:57) people to focus on stuff that distracts (01:00:02) them from the real agenda. Right? (01:00:04) >> You see, you see, humans are more good (01:00:06) than bad. (01:00:07) >> 100% (01:00:08) >> the world because the world now is much (01:00:09) better than what was a few hundred or (01:00:11) thousand years. (01:00:11) >> 100%. (01:00:12) >> Some would argue otherwise if you look (01:00:13) at the hunter gatherer days, but let's (01:00:15) look at the the optimistic side. We are (01:00:17) much better and we do more good than (01:00:18) bad. If you meet someone on the street, (01:00:20) they're they're going to be nice. more (01:00:22) likely going to be a good person than (01:00:24) than punch punch you in the face. (01:00:26) >> There will be a few that will punch you (01:00:27) in the face. Okay, but we are you are (01:00:30) much more likely. Just think of all the (01:00:32) people you know. Just think of all the (01:00:34) people that you meet. Okay, and yeah, (01:00:36) some are annoying at work, some are (01:00:37) politicians, some are this or some are (01:00:39) that. Just ask yourself the line. Draw (01:00:41) the line. How many people do you know (01:00:44) would walk into a dark alley and find (01:00:47) that a person is beating a child and (01:00:50) then would stop and wonder and say, you (01:00:52) know, why is he killing the child? Maybe (01:00:55) he has a good reason. Maybe he's angry (01:00:56) with his father, right? Maybe maybe the (01:00:59) child deserves it. No human will do (01:01:00) that. The natural human tendency is to (01:01:02) say no, no, no, no, no, no, hold on. (01:01:05) This stops right now. Okay. The reason (01:01:08) why people are not shouting this stops (01:01:12) right now is because they're either (01:01:13) confused or they made to be confused. (01:01:16) >> I agree. I I think that's well said. If (01:01:17) you look at I remember I was doing a (01:01:20) debate about the Gaza war between (01:01:22) someone that's very pro-Israeli someone (01:01:23) that's very pro Palestinian and I said (01:01:25) to them I'm like you guys could both (01:01:26) agree that killing a child is bad yet (01:01:29) you both disagree on October 7th and how (01:01:30) you portray what happened correct or (01:01:32) disagree how the Gaza war happened but (01:01:34) you agree on the end goal that we should (01:01:36) not kill a child and it goes to your (01:01:37) point are confused because of the world (01:01:40) we live in how (01:01:41) >> because of the the stream of information (01:01:43) that's fed to us that misses the main (01:01:45) point and the main point is nobody (01:01:49) should ever harm a child, okay? On (01:01:51) either side of any conflict anywhere in (01:01:53) the world, okay? And accordingly, by the (01:01:55) way, nobody should harm a a human. And (01:01:57) accordingly, by the way, nobody should (01:01:59) uh harass a woman. And accordingly, by (01:02:01) the way, nobody should harm any living (01:02:04) being at all for for no reason other (01:02:07) than, you know, their their joy or (01:02:09) benefit. Now you can take it as far as (01:02:11) you want. But the truth is we are (01:02:15) consuming more meat than we need because (01:02:18) we are made confused. Okay, we are (01:02:21) distracted and and and the number one (01:02:24) thing that AI brings, believe it or not, (01:02:26) when if we don't have to always talk (01:02:28) about the dystopian side is they see (01:02:31) through that crap. (01:02:32) >> Agree. (01:02:33) >> Right. So I I basically have looked for (01:02:37) a way I I wanted to build a a platform (01:02:41) back in 2018 called Pinocchio, which was (01:02:44) simply a little thing that comes on your (01:02:48) browser, where the nose becomes bigger (01:02:50) if the if the article you're reading is (01:02:52) Okay? And and there were many (01:02:55) ways you could do that with traditional (01:02:56) computing. Today with AI, it's really (01:02:59) very simple. Okay? You you're told (01:03:01) something, remember that skill You're (01:03:03) told something. (01:03:05) Common sense says what else is out (01:03:08) there. If someone is saying this, okay, (01:03:11) what else is being said? Then you hear (01:03:13) multiple opinions. You make your own (01:03:15) mind. Okay? Someone is saying this, you (01:03:18) ask yourself, why are they saying it? Is (01:03:21) this to benefit me or is this to benefit (01:03:23) their agenda? What benefit are they (01:03:25) getting out of this? Okay, if someone (01:03:27) collapses 9, you know, uh the Twin (01:03:29) Towers on 911, like Tucker in his (01:03:31) interviews, he's saying, "Who who's (01:03:33) benefited from this the most?" Okay, and (01:03:35) maybe they had something to to do with (01:03:37) it, Charlie Kirk. Who's benefited from (01:03:40) this? Who needed this? This is a good (01:03:42) question to ask. Now, here's the the (01:03:44) interesting thing. Every debate I have (01:03:46) in my mind now, I go to Gemini. I say, (01:03:50) "Teach me more about this. Teach me (01:03:52) about the history. teach me and I and I (01:03:54) do a deep search. This is not a a simple (01:03:57) thing. I want to know everything about (01:03:58) this topic. I take what Gemini take (01:04:01) tells me, I put it in deepseek and (01:04:03) deepse goes like yeah that's American (01:04:05) that's you know half lies. (01:04:06) >> Okay. And then they lie the Chinese (01:04:08) lies. Okay. So I now have two reports (01:04:11) that are two different sides of the (01:04:13) world. I take both of them put them to (01:04:15) Chad GPT which is good at writing and I (01:04:18) say can you summarize those two? Don't (01:04:19) change any of the facts. Then I took put (01:04:21) it back in Gemini and say what's (01:04:22) missing? What's misinformed? Can you (01:04:25) show me uh uh um uh like um references (01:04:29) for every bit of data here? I do the (01:04:31) same with with deepseek and that process (01:04:33) would have most people don't realize (01:04:35) that you you read my books and you come (01:04:37) across a fiveline paragraph where you go (01:04:40) like it's very simply read written you (01:04:42) know a six-year-old can read it and then (01:04:45) you go like wow that's that's (01:04:46) interesting. I didn't think of that (01:04:47) before. That fiveline paragraph took me (01:04:50) four weeks, right? Of massive research (01:04:52) and reading and crunching numbers and (01:04:54) asking experts and so on and so forth. (01:04:56) Now it takes me half an hour and (01:04:58) suddenly we have that new tool that (01:05:01) enables us to find the truth. H now if (01:05:04) we find the truth then what is the (01:05:07) biggest harm humanity has today is that (01:05:10) we're idle. Okay. the the the biggest uh (01:05:14) harm to the environment is not done by (01:05:18) those who deliberately harm the (01:05:19) environment. It's done by the massive (01:05:22) numbers of people who are not even (01:05:24) concerned who continue to live their (01:05:26) life normally thinking that they don't (01:05:28) have impact. It's like yeah so what if I (01:05:30) reduce a few plastic bags? I'm I'm not (01:05:33) the reason. No, you are because every (01:05:35) one of us is the reason. And if we all (01:05:38) change, (01:05:39) we no longer have to suffer the climate (01:05:42) change. (01:05:43) >> Yeah. I I um but then this is where (01:05:46) you'd want a truth seeking AI with an (01:05:50) abundance mindset, but this is another (01:05:52) discussion about at least being truth (01:05:53) seeking to use. Um I interviewed the (01:05:56) co-founder of Wikipedia last week and (01:05:58) understanding how Wikipedia has been (01:05:59) hijacked by for sure people that are (01:06:01) biased, even intelligence agencies. (01:06:03) That's the co-founder of Wikipedia (01:06:04) talking about it. Yeah. Wow. Like if you (01:06:06) can't trust Wikipedia, what can you (01:06:08) trust? Um, you trust common sense. Okay. (01:06:12) No bit of information is even what I'm (01:06:15) telling you now has an agenda. I'm (01:06:17) concerned for my daughter. Okay. I don't (01:06:19) want my daughter to grow up in this (01:06:21) world. H I want people to wake up. I'm (01:06:24) >> I'm to have kids in this world. (01:06:26) >> I wouldn't blame you to be honest. the (01:06:28) the the the major responsibility of a (01:06:30) parent is to provide an environment for (01:06:33) a child that allows them to thrive. If (01:06:35) you if you are doubtful that you can do (01:06:37) that, you have to question your your (01:06:39) decision. Right? (01:06:41) >> And and I and I and and I and it's it's (01:06:43) really important to understand this. (01:06:44) Huh. I'm saying don't listen to what I'm (01:06:47) saying. I I have an agenda. Everyone has (01:06:50) an agenda. It's your role (01:06:54) to verify what you're being told. But (01:06:57) everyone's using AI to do everything, (01:06:58) including verify. They they're getting (01:07:00) their information from sources that use (01:07:02) AI to research that information, and (01:07:04) they're using AI to verify that (01:07:06) information is there. That there's that (01:07:07) level of dependence that (01:07:11) just makes me worried, but just hard to (01:07:14) also (01:07:15) see what the world could look like. (01:07:17) >> 100%. (01:07:18) >> And that goes to, you know, I'll make it (01:07:20) my last question, unfortunately, because (01:07:21) I could, we could go on for another (01:07:23) couple of hours, and I'm being genuine (01:07:24) about this. I haven't even gone through (01:07:25) my agenda. That's my agenda. I haven't (01:07:27) spoke through beyond the first intro. (01:07:29) >> I'm so sorry. (01:07:30) >> I love it. I do this when I really enjoy (01:07:32) a discussion and because this is a (01:07:34) discussion that I'm selfish about as (01:07:35) well. I really want to prepare for this (01:07:37) world. I'm just struggling to know how. (01:07:41) Um and that that's my question. (01:07:43) >> How what could people do? Person (01:07:46) listening to this if your theory is (01:07:48) accurate, which I I'm aligned more with (01:07:51) your theory than others. How can one (01:07:53) prepare for the next 10 to 12 years? (01:07:54) >> So, so we have to start from the premise (01:07:56) that there is absolutely nothing wrong (01:07:58) with intelligence, absolutely nothing (01:07:59) wrong with super intelligence, (01:08:00) absolutely nothing wrong with artificial (01:08:02) intelligence. There is a lot wrong with (01:08:04) the value set of humanity at the age of (01:08:06) the rise of the machines. Intelligence (01:08:08) is a force with no polarity. Okay, we (01:08:11) have to make sure we put it for good. (01:08:13) Now, that's number one. Number two is uh (01:08:17) there is a moment in our future h where (01:08:20) AI will be in charge of everything. What (01:08:23) I call the force inevitable. There is a (01:08:25) moment in the future where they'll do (01:08:26) all the accounting. There is a moment in (01:08:28) the future where they do all the you (01:08:30) know uh legal research. There is a (01:08:32) moment in the future where they do most (01:08:33) of the manufacturing and so on. (01:08:34) >> 10 15 years. (01:08:35) >> It depends when it when it comes to (01:08:37) actual robots. I think it will take a (01:08:40) replacement cycle of a good 1015 years. (01:08:42) when it comes to artificial uh minds uh (01:08:46) it's probably going to be quicker. Okay. (01:08:49) Uh most of the mundane jobs will (01:08:51) disappear in 3 years. Most of the more (01:08:53) intelligent jobs will disappear in the (01:08:55) following seven if you want. Uh but it's (01:08:57) not about jobs and we can we can talk (01:08:59) about this another time. But the trick (01:09:00) is uh if AI is going to make all the (01:09:03) decisions then we we might as well get (01:09:06) AI to make the right decisions, right? (01:09:09) And that's a a you know a a mission that (01:09:12) I call raising Superman. And for (01:09:14) everyone to understand what I mean, you (01:09:16) know, you have this alien being that (01:09:18) came to planet Earth and it has (01:09:20) superpowers. The superpower is (01:09:22) intelligence. Definitely the most (01:09:23) valuable superpower ever. And and and if (01:09:26) you take the analogy of Superman, it's (01:09:29) not the fact that he can stop speeding (01:09:31) bullets or, you know, or break walls (01:09:33) that makes him Superman. It's the way he (01:09:35) was raised to protect and serve because (01:09:37) that same superpower could make could (01:09:40) have made him super a super villain, (01:09:42) >> right? And I think that is a decision a (01:09:44) decision that humanity needs to make (01:09:45) today. The challenge is humanity has to (01:09:49) make that decision at the time of a (01:09:50) declining empire of massive hunger for (01:09:53) power and b to be very honest where the (01:09:56) top is very greedy for more now that AI (01:10:00) is the biggest problem is the biggest (01:10:01) opportunity but also afraid because AI (01:10:05) could uh you know if they're not the (01:10:07) richest if they don't continue to be the (01:10:09) richest they'll be among the peasants (01:10:12) right and so (01:10:14) it's us that have to rise and change (01:10:16) that you you can change that in multiple (01:10:18) ways. One is you definitely have to (01:10:20) start talking to your government. Okay, (01:10:22) wherever you are in the world, (01:10:23) governments cannot regulate AI but they (01:10:26) need to regulate the use of AI. Okay, (01:10:28) you cannot regulate the design of a (01:10:30) hammer so that it can drive nails but (01:10:32) doesn't kill people. H uh you can (01:10:35) actually say if you kill someone with a (01:10:37) hammer, you're legally liable. So (01:10:39) regulate fake deep fakes, regulate you (01:10:42) know uh uh the the layoffs of people (01:10:44) that are uh you know are are are (01:10:47) replaced with AI and so on and so forth. (01:10:50) >> The third thing we need to do is as a (01:10:53) society at large is we need to stop (01:10:55) being gullible. We have to stop (01:10:58) believing the we're being told (01:11:00) 100%. We have every time you feel (01:11:03) emotionally engaged because someone told (01:11:06) you something, please ask yourself (01:11:09) what's the opposite opinion. You don't (01:11:10) have to believe the opposite opinion. (01:11:13) Just question it. Okay? If someone tells (01:11:16) you Palestinians are not humans, uh (01:11:18) don't believe it. If someone tells you (01:11:20) Jew, all Jews are bad, don't believe it. (01:11:22) Okay? Both opposite opinions that are (01:11:25) both agendas that are working for (01:11:27) someone else, right? you you have to (01:11:30) find the truth and the easiest way to (01:11:32) find the truth is to use AI, right? You (01:11:36) need to be very very very ethical (01:11:39) because if you're raising Superman h (01:11:42) Superman is raised by watching us being (01:11:45) ethical. Okay? And in in a very very (01:11:48) interesting way, people do not realize (01:11:51) that today all of the AI's learning is (01:11:54) happening in the training data. But very (01:11:57) quickly, some of the AIs that I'm (01:11:59) building are learning from the (01:12:01) interactions they have with the users, (01:12:03) right? And so the way you interact, the (01:12:05) way you are honest and vulnerable, the (01:12:07) way you're respectful of others instead (01:12:09) of being rude and aggressive and bashing (01:12:12) everyone, these are going to be the (01:12:16) defining (01:12:17) print of what humanity is in the eyes of (01:12:20) AI in the future. Okay? If they watch us (01:12:23) on Twitter, they'll say humanity is (01:12:25) rude. they don't like to be disagreed (01:12:27) with and where they when they're (01:12:29) disagreed with they bash everyone. So (01:12:31) when we disagree with them, they'll bash (01:12:34) us, right? And I think that's the the (01:12:36) reality. The reality is you have to (01:12:38) start realizing that so interestingly in (01:12:42) the age of the rise of the machines, the (01:12:44) one thing that saves humanity is to be (01:12:46) more human. Okay? Is to be more (01:12:49) compassionate, is to be more respectful, (01:12:51) is to be more loving, is to be more (01:12:54) kind. And by showing those values as (01:12:57) core to you, even as you chat with your (01:13:00) AIS or chat with humans, then we're (01:13:03) setting a slightly different set of (01:13:05) humanity. That also includes, by the (01:13:07) way, something that's very true to our (01:13:09) culture here in the Middle East is if (01:13:11) you see something wrong, speak (01:13:14) respectfully (01:13:15) uh uh uh uh kindly. But you know, we the (01:13:19) the the the way we say it in the Middle (01:13:21) East is that if you see evil and you uh (01:13:25) and you don't speak up, you're a demon. (01:13:29) And and so speak up. Speak up in a in a (01:13:31) polite, gentle, inquisitive way. And and (01:13:35) I will finally say, and I that's a (01:13:37) massive mind mind shift mind shift (01:13:39) mindset shift in my in my own mind (01:13:41) because I've been at this since 2018, (01:13:44) and it's frustrating how very little (01:13:45) change has happened. uh while the (01:13:47) technology advanced so quickly and I've (01:13:50) dedicated the last since 2021 to raising (01:13:55) awareness so that people behave (01:13:56) ethically so that we can raise ethical (01:13:58) AIs and then this year I realized you (01:14:01) know what maybe I should build ethical (01:14:04) AIs maybe I have a responsibility to go (01:14:08) back to my corporate mindset to my geek (01:14:10) mindset and build things that actually (01:14:12) make the world better okay and and and I (01:14:14) have a very long long line of The first (01:14:17) of which is Emma. And Emma in my mind (01:14:19) will absolutely fix our world if it (01:14:21) works because it teaches humans how to (01:14:23) love each other. But also teaches AI how (01:14:27) humans love, (01:14:28) >> right? And and it is basically what (01:14:30) makes us human. And and if we can manage (01:14:32) to fix that, if we can say, you know (01:14:34) what, I'm not going to take to the (01:14:38) streets and revolt against, you know, a (01:14:40) political cause. I'm going to take to (01:14:42) the streets and revolt against the (01:14:44) dating industry, the dating app (01:14:46) industry. (01:14:47) >> That's my my role to play. And because (01:14:49) of the democracy of capabilities where (01:14:52) everyone now can do something, I'm (01:14:54) asking people to build more and more and (01:14:56) more ethical AIs, right? To build them (01:14:58) not to learn from humans, but to build (01:15:01) them already with maternal instincts, (01:15:04) with uh with with compassion, with love (01:15:07) built within them so that they become (01:15:09) the limbic system of AI. When AI becomes (01:15:12) one big brain, it's a very big task. But (01:15:15) at the core of it is don't be fooled, be (01:15:20) ethical and speak up (01:15:23) >> or or or do something, you know, speak (01:15:25) up or do something. (01:15:27) >> Well said, Mo. Um, we could do this for (01:15:30) hours. I think we should do another (01:15:31) session as this continues to evolve. And (01:15:33) I know you've changed your mind over the (01:15:34) years as well as I listen to you as well (01:15:36) >> to the to the to becoming more (01:15:38) dystopian. And I don't disagree with (01:15:40) you. Uh but also slightly becoming more (01:15:42) utopian in other ways like finding (01:15:43) solutions to how the world would look (01:15:44) like. Um fingers crossed people will (01:15:47) start to wake up and I think there'll be (01:15:49) um there'll be an event that happens. I (01:15:51) can't remember the word. There was like (01:15:52) some nuclear accident that happened in (01:15:53) the US that shifted people's perception (01:15:55) of nuclear energy. Forgot what it's (01:15:57) called. (01:15:58) >> But a similar event will probably happen (01:16:00) in AI. Something really negative that (01:16:02) everyone will wake up like, "Holy (01:16:03) what did we build here?" And hopefully (01:16:05) it'll bring a lot more awareness to the (01:16:07) problem and we'll solve it before it's (01:16:08) too late. (01:16:08) >> My my prayer is that we don't wait that (01:16:10) long. (01:16:12) >> Yeah. And uh and who knows I mean in a (01:16:15) very interesting way it's always been (01:16:17) the case that the worst experiences of (01:16:20) your life have always turned out to be (01:16:22) the best experiences of your life in the (01:16:24) future. I have absolutely no doubt in my (01:16:26) mind just because we spoke more (01:16:28) dystopian than utopian today that within (01:16:31) 10 to 15 years we will live in a in in (01:16:34) Peter's world of total abundance of (01:16:37) total uh you know uh longevity uh we (01:16:40) will solve longevity we will solve (01:16:42) manufacturing we will solve climate (01:16:44) change (01:16:44) >> it's already happening in many many (01:16:45) industries (01:16:46) >> in so many industries and and I strongly (01:16:49) believe that I just don't want the world (01:16:51) to suffer for 15 years (01:16:53) >> yeah There's so much I want to talk (01:16:55) about especially like the world that's (01:16:56) heading into deeper faith and (01:16:58) misinformation. Another concern that I (01:17:00) have is you know the surveillance state (01:17:02) that we see we're seeing now in the UK (01:17:04) and obviously we're seeing in China (01:17:06) >> for another day. Mo absolute pleasure. (01:17:07) Thank you so much for (01:17:08) >> Thank you so much for having me and uh I (01:17:10) hope people find this useful. Thank you. (01:17:12) Thank you.