And there's a man who lives in the Silicon Valley, who's gonna be considered poor if he earns less than $10,000 a year in his family.
Because I really think the young have this, and, like, the phrase is quite old, and this live fast die last, that's fast money.
That God created people differently, yes, and Colt made them all equal.
Agent is a system that can be autonomous, independent, in the performance of the tasks that a man has the watch, right? And then there is a considerable optimization of the work.
And I was a programist, and I started working for $100. When you see what's happening in the world now in terms of technology, what projects are going on, what ordinary people do, what they use sophths, programmes, equipment, what's happening on the street, If you're not, you're going to be able to get a lot of companies with huge budgets. And you and I were talking about the last time, there were even numbers there, seven trillions, some kind of numerical numbers. And, uh, that's what even happened in a week, and where the world is now, there's a big game about it again. Hello, everyone! We're on ToTheMoon. Our four are irrepetitive. We're Tanya, Sasha, Elnar and Sasha. And today we will be loading even more into the various technological news, the technological world. This week, Wall Street Journal has been giving news that the Zumers do not want to receive higher education, colleges in the United States of America, and they are increasingly looking for education, so fast.
Qualification, everything about becoming a plumber, for example, or an electrician, and doing something fast. What do you think about this? Because it's a very interesting story that in the United States, uh, ten years ago, a huge program was launched that every person should have a higher education. We're like you, people born in the Soviet world, not all born in Soviet peace or everything?
I am.
We're not alone, Sasha, no. You, Sasha. Sasha is the man of the Silicon Valley. Here. And, well, at least three of us were born in the Soviet world, and Sasha was still going to s-- in the first place. And with the physical, it's exactly an education that goes from there, right? We were calm about being a Belarusian woman, that in Belarus, if you don't go to a good higher education, you're an idiot. So, the base was all. And the wave in the United States, it's a little different. And in this news, this emphasis on people getting over, this is the change in college admissions, which is a very interesting sign.
What is happening, especially in the world of emergence and very strong technological developments.
I am surprised by the choice of a plumber profession, as I respect it. I think you're gonna tell me they want to be blogers or I don't know, someone in this field. Because I really think young people have a thing like that, although the phrase is quite old, this live fast die last, that is, quick money, quick knowledge, and now the world-- fast, again, information, Speaking of which, within our sphere, technology is going so far that you don't need to sit there for hours in the library, as I remember, sitting on the first of your three higher entities. Now I don't even know if people go to the library, even though I'm still walking. You can find everything in Google fast, you can find everything in GPT chat now, but I don't think there's a value for this system, a systemic thinking that gives classic, like university thinking. education. It's so brain-smart that you can then, like, three times I've been there, like, changing the profession that you can do anything. But I wonder why the plumbers are there? What kind of profession was that?
There are still cookers there, electricity. That's the way.
Hand work and so narrowly specialized. I think it's another trend that's gonna be a lot more valuable to some of these little craftmanships, yes, that's a narrow specialization and a large number of knowledge in a certain field.
That's interesting.
Well, the main problem that this article is pointing out is what is it connected to? What a man if he wants to get a higher education, at least there's a story about the States, and now that the States is a little, yes, a big credit is needed. I mean, education is expensive. And it turns out that, first, a man falls into some debts when he starts studying, then he goes to school there for five to six years, after which he enters the market where he, uh, is not a man, Experience, and in the market, it's like a lot of people who actually have experience, but they're changing work from one to another. And this competition is a very difficult one to be in, and it's a credit. And so it turns out that his education does not take five years of his life, but five years plus time to find new jobs. Plus, we have to give credit for this training that was there. And now, the generation of Zoomers, yes, as they are called in the article, they, uh, are not willing to spend that number of years of their lives for some potential career he might have. That's the first. And the second, I understand, is the strong variability of the world, too. So a man is betting, there, on parole, ten, fifteen years ahead, taking into account all this story. And that's what makes this choice fall on professions that can be developed quite quickly, right? And instead of, like, 10 years with credit, you might have one or two years, you're starting to work. I understand that it's not so hard to find work on these specialties. Mm-hmm, there's not such a big wage gap, at least there, on a short distance, and you don't have a credit card from the start, do you? And there's an example in the article that a man in there at 25 years, and he says, "I'm buying my house now because, there, I don't have a tuition credit." On the one hand, this position, well, I understand, I think it's logical. On the other hand, that's the subject we're discussing, what do we do? We say that AI is the one who's already generating pictures, and he's already working with a sound, so he's already in there, uh, writing music that, uh, he's gonna replace all the repetitive work that can actually be replaced. And people are just getting out of the profession, which is likely to be replaced, you know, by robots, right? And a double-track trend, to be honest, I don't know how to treat it either. For a short distance, yes, it must be working. I'm not quite clear on the long distance.
And here, Tanya, your position on higher education is, frankly, much closer.
I mean, one interesting thing that, uh, interesting things are changing really hard. I mean, we-- I, for example, got a higher education, had no idea, there was no connection, in fact, between higher education and the job I'm gonna work directly, because very much. The market changed at the time. And I was originally a programmer, and I started working for $100, although I had a very strong education in programming. In the States in 2005, if you were to graduate from university or 2004 you would be Well, that was ridiculous. You'd always get a lot more straight at the time, a programmer, and you'd get a lot more than a plumber and more than an electrician. Although plumber, the electrician is here and so, the job is high-paying for us. She's not a high-paid one, of course. And there's a man who lives in the Silicon Valley, who's gonna be considered poor if he earns less than $10,000 a year in his family. The question is, the fundamental thing is that now, uh, there was an era when a large number of online programmes were introduced. I've devoted a lot of that, including my sanctuary. What does it do when there's a very big choice? Big choice, uh, first of all, makes a difficult choice. The first is very difficult to choose, and the second is very different. And I think it's getting very difficult to choose today. When Tanya says people don't choose bloggers, I think if you choose, make a bet more precise, you'd better choose and become an electrician and a plumber than become a blogger. I'm not talking about system--- not higher education, but about the work of a basic, small, in terms of, uh, length of life. Maybe, um, I'm being abstract, of course, now. In general, of course, the achievement of a good, true basic systemic education is the strongest basis, including when a large number of people claim that people will not work, which means that they will not work. I'll do the AI, which will come out of AGI, and everything will be completely gone. And I think that this strong development of my university has allowed me, uh, to get a very strong base, so strong. Well, uh, the subject, uh, on that stop--
Uh, the subject-- uh-uh, that's worth getting attention now, because the trend that, uh, the wave that goes, it's not-- it's not that Wall Street Journal, it means some know-how has been found. This means that some trend will be happening over the next five, ten, fifteen years, and that it is mixed together, uh, with what is happening in the technology market. And within the framework of, uh, new technological market, uh, a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-
It's, uh, it's a lot of description that Microsoft and Microsoft with the exact-- together with OpenAI, invest in crazy money, there, over $100 billion in supercomputer. So, Sasha, I wanted to ask you. Uh, look, they're putting in a super computer and saying, "They're doing a supercomputer that never has anyone in the world done, right? And they say it's on the horizon, there's a 50-year-old world that's going to change the world, and that they just have unreal, that, uh, these supercomputers that are being made in parallel, they, uh... It's something else, it's something else than AGI. How does that change the lives of ordinary people? Here. Or is it changing the lives of ordinary people now?
Companies like OpenAI and DeepMind, yes, i.e. OpenAI, can say it's like a part of Microsoft, and DeepMind as part of Google. They, uh, have challenges that, um, no one else in the world is facing, I'm honest. Uh, from private conversations, I found that, for example, Gemini is a new Google model, a new generation, not that they, uh, a quarter, uh, an a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a-a- Uh, he needs a lot of videotape that can't be on three--- which, like, no date centers for that, for the right number of videocarts. Yeah? I mean, there's another kind of problem. Oh, that's where the problem is. Also, there must be a lot of people talking about it, but, uh, well, they're already building such a big infrastructure. They do their own optics, rudely. I mean, Infiniband. I mean, if there's any Ethernet, it's a standard Internet connection, right? Then eat like Infiniband. It's, I understand, the type of connection, the type of wire that was developed in NVIDIA. Google has a solution, and I understand it's often better than a decision from NVIDIA. So they, uh, have infrastructure shuttles that no one else in the world is facing.
What do you mean, Sasha, I'm sorry, what do you mean? Just explain, uh, who's watching us. What do you mean, there's something above the
Internet?
Yeah. I mean, uh, even there, a little start-up like Hixl, yeah, that's the one I'm leading, that's the problem. I mean, the problem is, uh-a, models are training that, uh, that's, uh, big models, that's, uh, um, millions, hundreds of billions of parameters, and those models, they don't fit in any way. One computer, roughly, right? I mean, you need to use a lot of computers. And if the model is to be distributed, it is necessary that, uh-a, a link be made that allows the data to be distributed effectively. And directly on the scale of companies such as Google and Microsoft, the direct rate of data transmission is one of the competitive advantages also.
And what happens to the, uh-oh, with the big companies, they own, uh, totally different infrastructure, right? I mean, again, uh, there was a news about the in-NVIDIA opening the data centers in Indonesia, and there are different coalitions against it. So companies, there's a Qualcomm, Intel, which means, uh, saying, "We're gonna do something we're gonna do." As much as anyone says, "We're where we don't know what to make a fund separate, we're gonna be in the pool, there's five billion or ten billion." But you realize that people are in there for dozens, hundreds of billions. And it's like, uh, the world of some totally other big corporations now. From a change perspective, people are once more. Why am I saying change to people? I'm just in the middle of the United States, Colorado, right? And I drove by today, I was there from Denver to Colorado Springs. Colorado Springs was 18 years ago at the factory producing, by the way, the semiconductor Semiconductor Equipment Automation. We were here-- I was running the project, introducing, uh, the soft, there, making LCD-panel. But the point is, everything looks really, uh, well, I think it was like that 18 years ago, right? How big are those, again, supercomputers, big companies that play such huge games.
What-- how does that affect the changes in the world now or will affect the changes in real?
Again, it's hard for me to say. I, I want-- I want to, uh, maybe tell you more about who it is, maybe explain more to the wider group of... uh, listeners, how it works. So now, oh, wrench changed in the first 20 years that OpenAI, Anthropic and Google, they no longer offer scientific work to scale their model. I mean, uh, let's just say a broad group of art-study researchers in the arts field understand how to start a quality model like ChatGPT. Databricks did it. I understand that Yandex also said that they did. Uh-oh, but when we're talking about models like GPT-4, GPT-4 Turbo, GPT-4 Vision, Gemini 1.5, last Opus is a model from Anthropic, which is at a very different level, I think we don't even know--Mmm, I think, We don't know how these models actually got, yes, which data they were training and how they were trained. And you have to understand that GPT-4 Turbo is an old enough model and GPT-5, I understand it will, uh, come this year. And you can say that the OpenAI is on, uh, front, say, ahead of this public science for two or three years.
From the point of view of the searcher, these news, are they pushing? For most likely, just Microsoft is on this news, making infrastructure for the development of even more models. Yeah, when they invest, there, $100 billion in the creation of a date center and a super computer that can count it all, it just means that current models are probably already running, well, or soon they're gonna be. to be safe in the existing infrastructure. And this infrastructure needs to be expanded, right?
And this news is like we're seeing a step right this way.
And, um, it's got to be understood that in the case of Microsoft, it's a complicated organization like Google. And there's a kind of infrastructure organization that wants to sell shovels, right? And there's, uh, OpenAI organizations that make shovels, and they want, and Microsoft wants to win at all levels. So this is an opportunity-- that is, AI is an opportunity for Microsoft to completely relive the market cloud and to absorb in some sense the whole market, yes, in itself, to win Amazon and win Google, To win Oracle and O and other companies. They're doing everything they can to do at all levels. They build the world ' s best models through, uh, OpenAI, they build the world ' s best security infrastructure, they build the largest infrastructure in the world. Ah, and they're sub--I-- what I see in their AI strategies, they're, like, a-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h-h So they're trying to win at all levels. A-a-maybe it's important to add what's so far in the generative AI sales of GPU, yes, far superior to the revenue that is made with the GPU. So I think that's why Microsoft is trying to win at all levels.
Well, I guess we should expect the other players, at least if we're talking about three main players, that's Google, Amazon, Microsoft. Google and Amazon are too soon, either announce or, without declaring, start developing, expand their data centers so that they don't get overboard, do they? To make it impossible that the larger model was far from what they had, and they have no infrastructure-based infrastructure to develop. In fact, companies get a little, um, well, but not a stalemate, but, you know, a stalemate can be a situation where they have to do exactly what Microsoft is going to do now.
Right! I mean, that's-- that's right, yeah. I mean, for now, it looks like, uh, that every company is trying to impress the industry with the number of GPUs they have., same Meta, uh, said they bought a lot of GPU. And I think that in time we'll see that after these infrastructures, after these infrastructure investments, uh,
they'll focus on services.
So, what is the existence of-- the way the world is going now, as it is changing, is that it leads to new platforms, including new ones-- can lead to the emergence of completely new operating systems and new systems, c-
And new systems that will be all over again...
Yeah, I honestly think that everyone's waiting for agents. By agents, we mean systems that can perform a fairly large set of tasks, knowledge worker, yes. I mean, knowledge worker, typical, has a number of tasks, and I'm just like... my definition of agent. The agent is a system that can be autonomous, independent, in carrying out the tasks that a person has the watch, yes. And then there's a lot of work optimization going on. And as until the technology reaches that level, and, at least, Sam Althman promises that GPT-5, that, um, will already provide these opportunities.
While GPT-5 is not yet available until these agents are gone, big companies invest in infrastructure, for these agents, roughly.
I just get it, I see, uh, we're-- I'm a lot on some decisions from a work perspective, there, on sale, CRM or marketing, or finance. I've been with one team for over a year, thinking, for example, some products, watching what I have a feeling that I might be in the AI-Preform, showing up like a new one. The operating system that I can start to deploy is completely my own, my interface or my application. And it won't be like, there, app, macOS or iPhone, for Android. Or it's for Windows, or it's just some-- like, a website. It's gonna be something different. I mean, at least those, uh, that UX/UI or that laser-- well, at least that user experience we're looking at in the CRM system, you can get a little bit of a base-- so, a probable. ChatGPT. I'm just saying, yes. So you realize you don't need another system, you're quite a little interface, a treatment, a receipt of information or a voice, or a text, not a visual decision. That's very, uh... I think the operating system might be a completely new level of something.
I heard in closed circles last week that, uh, Dell, for example, is about to release the AI computer, and people are discussing, and how can you do that AI computer to program in AI? Couldn't have been a million, there, ML programmers, and could have programmed everything. And the condition-- well, it's a condition that you get very fast to the infrastructure without having, like, DevOps, without spending five, ten hours, there, or 15 hours on infrastructure rolling, and five to ten minutes, for example, Start some layer of systems, yeah. And that, that's what's all about the other scale. But again, we're running into the dates centers, the equipment, the availability, who and who makes, who has access to the factories.
Well, here, Sas, there's actually two sides of the move, yes. There's a development on the side of these gigafabric, the hydrate centers of the big companies. And there's still a move downwards towards the democratization of all this. It's a computer, uh, from Dell, yeah, that's predetermined, maybe there, pre-destruct. Also, the news is NVIDIA released RTX chatting. Yeah, it's so abstract that you can put on Windows and build on it, start some LLM. Well, if the iron allows them to be launched locally and, there, tie them to their current, uh, knowledge base, probably wrongly, to their files, yeah, that LLM works local, isolated from the rest of the Internet on your computer. I see that, uh, as programmers can do, that's what they do. But another case, NVIDIA has released a demo of so-called vinegar that almost anyone can run this thing on his computer, yes. And if, for example, you don't want to release the data on the trail, there, on the side of Aic, OpenAI or somewhere, you can just get it on your computer, yeah. So this is where the movement is going on two sides. On the one hand, we're developing some huge models, and on the other hand, even there soon, maybe there's a way on the phone to start some models, uh, with a pretty good, uh, like, Performance, yes.
And if the agents talking about Sasha, well, I think that thing might go on that side, too, to such local offline agents.
Well, let's talk about this story. This week, CNBC reported that a large number of stars had signed a petition for intellectual property use in artificial intelligence. There, Billy Eilees, from Billy Eilees, Madonna, Stevie Wonder, Katie Perry, who's not there. Uh-oh, and the presence, again, with, uh, supercomputers, says content, uh, well, um, I-- I-- have a feeling that it's gonna be inexplicable, contented by whom. Although I see a huge difficulty in that, I see a huge, huge, complex. That's the wish of the wrong people to listen, like, all the information, like, to get into ChatGPT or, like, not listen to our video. Someone's gonna say, "Why should I listen to him? I'll take 30-40 minutes, cut the text and do some gPT chat to me. " But if you need a report, then a man just goes on the news channel and reads a news bulletin, yeah. Ah, it's a real man's engagement. Is that what the trend is now or is it all about what happens to this movement? You, Tanya, for example, you're creating an endless amount of intellectual property in terms of space design, right? Or, for example, Sasha, and, generally, Sasha, on the other hand, Sasha, now on the outside, said a little start-up there, but there's a very unique group of people in the world when you make the creation just like that on the basis of the base. artificial intelligence of visas.
How do you feel about yourself, like, seeing you in this problem as a man very much in creativity?
I can tell you I'm not seeing any problems yet. I don't know how far that could go. It's five, ten years, right? But while I have my own, uh, s- algorithm of a certain interior, and there are many things that I'm sure that, for now, there is no artificial intelligence. create. Like, I'm very much in contact with a client, I'm looking at some sort of psychological profile. I'm trying to find colors in there, based on my visual experience, which is, you know, always a match, a customer, my taste, some of my ideas, which I'm sure they're illogical. You know? All creative, it's a little alogical, therefore, difficult to process, as precisely this date of algorithms. So there's a lot of emotion. I always ask people how they want to feel in this interrier. I mean, I don't think that maybe at some basic level, like, if you give a mission to create a calm interrier, yeah, you can understand that there's some colors that you use, like, a minimum. The number of visual noises, etc. But if you do it at the high level of art, yes, I don't think that-- that, you know how to compare the photos made by the camera, yeah, and the man wrote a portrait. Yeah, I know that the picture looks like you more, but the portrait, it transmits so deep a power, some kind of view, that's the identity of the man that this portrait wrote. I'm sure I don't know how to go. I have no fear in this respect that someone will take my job. Well, again, I mean, back to being a hand-held job, right? When you're there, I don't know, a jeweler or an artist, or you play theater, right? People go to the theatre anyway, even though there's a TV, there's a YouTube, right? I mean, it's all different ways of thinking. And I am very pleased that a large number of people will soon be able to create basic interreiers and live in more beautiful, more sophisticated, ergonomic spaces.
But not everyone will have access to high art again.
And I wonder, by the way, about intellectual property, what you're doing is just a lot of projects, and you have some ability to create a huge number of different spaces. I see you drawing information from a large number of sources in terms of books and everything. Even we gave you this weekend, on Sunday with Polyna, we found you in antique books about, about, design and architecture. So why are we looking for them? We understand that some drawing or some new person or something, it can push something new. In fact, we all see a large number of different spaces and generally use intellectual property, allegedly intellectual property of other people, as well. But you're still missing yourself and you're making something your own.
You give something you own, yes, your own. I think that in classic use, with a good flow, it's got, uh, well, I don't know if you're getting this job, yeah, you. Even if you don't use it, there's a high-quality art word, I think that a lot, well, just an incredible amount of everything, uh, is gonna be, first of all, human beings, and second, uh, I'm, uh, As long as the intellectual property problem is more likely to be seen in what is likely or not to be different. So they can or can't distinguish where this real man is, and where it's different. And we had a whole discussion. Sasha and I have been talking a lot of videos, and Elnar and I have been talking about a lot of videos, so I've been filming videos for three months with help, there, Generative AI, and then the aaaa, and then shut down because he said it was diagnosed, yeah. I think it's diagnosed there, YouTube, TikTok, Instagram. My friend says to me very much: " No, it's not possible to diagnose, it's AI not diagnosed.
" That, of course, could create different precedents. Sas, what do you have in mind about that, uh, intellectual property? That someone might despise, for example, what you're creating, travel in intellectual property space. Though I think you're making new things for the world. I mean, I think what you're creating is not relevant to intellectual property as such, because you create absolutely, you know, something new, crazy, in a good way. That's what I'm saying. In a good way. So you're like new worlds, not-- it's not intellectual property.
That's a very interesting question. Uh, I understand that always... And here, and the question first, yes, not the way I look at it, but the case law. Because there were many cases before, when, in a rude way, people took a popular image, slightly modified it and positioned it as theirs. And I think that's, uh, and, of course, it's hard to tell how the revenue model is gonna be, revenue shares are built. But I can tell you that those who can use all these new AI-Tulas, yes, they'll be as successful in the future as they are, rather than those who just wait for AI-Companies to be part of their own, part of their own. revenue to share. I mean, I'm guessing everything's gonna come to share the model, but it's already, like Google's sharing, like, uh, as I understand, Google and Facebook have been forced to share re-revenue with, uh, news sources. I think there's something similar here, but it's clear that Google capitalization is much more than the New York Times, right? So those who can be the new Google, not be like New York Times, yes, these companies that use AI technology, they, uh, succeed, and there are a few trillion companies that will be established. Uh-huh. And yet we are at a very, very, very early stage of Generative AI development, and there is no pre-condition that there will be any personnelization. Let's see the pictures. Midjourney has more than 300 million revenue per year. It's a big company. Google has its decision Imagen, which already has enterprise clientele. Microsoft has its decision DALL-E. There's no system that can allow an artist like, yes, a-a-m, a model under his own style, right? I mean, for example, a new artist comes along, they're often called prompt engineers, and now he wants to create content in some particular style. And that's the kind of box that nobody's doing right now. And therefore, I think we are still at a very early stage of development. I mean, if there's some kind of model work, it's likely that Generative AI will be able to do this work more quickly than 90% of the people.
But as soon as it comes to staff, I think AI Bud-AI is a lot behind man.
I'd add a little more here, too. Look, uh, it looks like, uh, I'm seeing, uh, at least, two big things for me. There's this ethical, there's, uh, that's more technical. If we're talking about an ethical dimension, the question is pretty complicated for me, right? Uh, on the one hand, I see models are learning on the existing content, right? And here's how, Tanya, you can look at some book with pictures, inspiration and on the basis of this, um, create some kind of interrier. That's probably a little bit on this side. On the other hand, there is a danger that these models can directly copy a man. Well, let's just remember the example of the Haben book last time, huh? On the one hand, I can put a book in there that I want to sound like, not mine, but some famous man. If I'm using it myself, there's probably no question. If I start making a profit, it's probably close to piracy, closer to stealing. And here, the ethical dimension is probably starting to get hurt. Well, speaking of the technical side, yes, here, you know, you can remember, uh,
A saying like this or a Ambassador or a quote, I don't know how to say that God created people differently, yes, and Colt made them all equal. It's a story. I mean, the evolution of technology leads to a large number of people having the opportunity to do something, to create something. It could be there writing music, it could be some kind of image, writing some text, poems. At some level. It's not a good art, but at some level, it's getting a lot of people. And I'm just a little on the same side of the parallel. I, uh-a, I was into chess as a kid, pretty active, and I'm looking too. That's the championship, not the world championship, it's coming, it's, uh, the pretentious, uh, matches, yeah, the selection for, uh, the man who's gonna play for the world crown. And there's a similar phrase in chess, like Colt, that everyone in the chess plays differently until the computers show up, and the computers all do the same, right? I mean, with the moves, um, your talent doesn't matter if you use them. And the same thing can be in some way, in the writing of music, in, uh, writing pictures of something, creating interers, and other things. And that's the point, it's more of a life-saving inevitability we're probably moving.
But I wonder if there's no less people playing chess. When the computer is available, online availability and everything, popularity has grown. And if you play and you win and there are benches, there's only computers that start playing, this system will stop using, right? So I play chess enough, I play live, online. I like to play very hard, but I like to play alive.
Online is just not interesting, yes, I mean, not my story. Someone's playing online, so it just grew up. That's a good one, by the way, well, I really liked the example. That's a great example. Tatiana Cvetkova, Alexander Mashrabov, Elnar Shafigullin and I, Alexander Volchek. We have different experiences, very good experience in general in terms of, uh, vision and implementation of different solutions in the world. Uh, three people live in the Cremnival Valley, me, Tatyana and Alexander. We're in the Silicon Valley all the time. Someone's very much in AI, someone's side-by-side from different technologies. And we'll try, first, to tell you about the interesting things that happen in the technological world, which, of course, are a lot of emphasis now, very much on AI, and, uh, show more than just some simple thing. Analyses or sites, and share your own senses and your own living in this life. So sign up for the ToTheMoon channel, uh, throw it over to your friends and friends. We're very happy to see you here. It's nice to see different comments and interesting things, too, you can bring in from the point of view of the news or the things you'd like to know. These questions that you'd like to know, you can ask them here in the canal, and you can sign on us separately. Uh, at least I and Tanya, we are here, including in social media. Uh, until the next meeting. I'll see you in exactly one week, Friday, uh, at six p.m., six nights at Minsk, Moscow, Kiev. This part of the six nights is about to be on Friday. See you again! I am very happy that, uh, we are gathered together with such a great team and close people. At least I'm all very close people. Tanya, Sasha, Elnar, thank you very much. And I, Sasha, who's in Denver now, thank you, too. Bye, everybody.