i am very grateful to you for your patience, for your indulgence, and i think that if you agree, maybe we will gather our thoughts again, the main thing is that it will be interesting for the viewers and listeners, so i will watch from the outside and decide whether we will gather again or not, don't show it, thank you very much, andrey kmyshev, gavriil gordeev, i am vladimir ligoyda, we were gathering our thoughts on a serious topic, what is humor. dear friends, the creative industry podcast is on air, with you are still living, real copies of the hosts, this is still elena kiper, producer, video maker, and i won't touch it yet, i need to make sure, let me too.

artificial intelligence is a topic that everyone has heard about, but very few people understand what it is, everyone is already afraid, wary, well, in general. there is absolutely no need to be afraid of it, since we started with this, it is a tool that helps us do different things, that is , it automates some part of our intellectual work, mainly the routine part, artificial intelligence is... in fact, they usually mean

some kind of neural network, what is a neural network? a neural network is a kind of, you know, you can imagine it as a black box that takes something as an input and gives something as an output, that's exactly how we imagine it, as black, what's inside the black box is a kind of mathematical function, a function that now, for example, lies behind, for example, generating a picture from text, has - well, there are billions of parameters, that's why they are so complex that an ordinary person who... now sits in front of our still digital tv about artificial intelligence, within the framework of such everyday understanding artificial intelligence is, well , artificial intelligence is this black box, you can imagine it like this, which everyone just imagined now is a black box, what to do with it, which learns to make some decisions, these decisions can be a huge number of tasks, in fact, which it solves, that is, you take some amount of data, well, let's say, some amount of knowledge, well, let's say... you take all

the volumes of leo tolstoy, load them into this black box, and it can give you, well, let's say, more one volume of leo tolstoy, for example, well, in a sense, yes, that is, this function learns in this way, that is , the parameters are configured in this way, these billions, based on the motives, so to speak, so that it is configured, what does this mean, this means that this, that is, the learning process occurs, if we are talking about language models, such as - for example, well, all of us... the famous gpt chat, gigachat, for example, then this is a function that takes a set of words as input and tries to predict the next one, and so so, if we predict a word many times, then we will get, for example, the next chapter of leo tolstoy, that's what the language model specifically does, that's - after all, a neural network, it can not just compile, it can create some new interesting ones, that is, this is a new quality after all. it's like saying,

if the neural network did not see some object during training, then of course it is unlikely to create it, but with those objects and with those styles that it saw during training, neural, i mean, it can of course to do different very, very cool things in my opinion, that is, it can process , for example , make some objects in the style of some artist, here you can argue whether this is creativity or not, yes, these disputes are already going on, and quite fierce, quite toughened, but the very fact that this can be done. it turns out beautifully, especially recently, this is an indisputable fact in my opinion, but in fact i can say this, that really the field of artificial intelligence, it is now being democratized, such a term, maybe it's a bit complicated there, but i'll try to explain what it means that artificial intelligence can now be studied already from school, let's say from the ninth grade, sometimes someone from the seventh, in general, they study at a good level, what

did he discover there, that - a creative person, if he has some images in his head, there are ideas, fantasies and so on, in order to put these images on paper, well, that is, he needed to acquire certain skills, he had to go to study, to be an artist, become a musician and so on, now it turns out that with the help of artificial intelligence you will refute me or confirm this, that is, you can transfer these images from your head, so to speak, into...

the work of the neural network is much easier for it, because it is easier for it when you have described in detail what you want, it is easier for it to draw it, when you have written, i just want a fish in space, for example, i don’t know where this came from in my head, it, it needs to think it out, and should it be in a spacesuit or not in a spacesuit, should there be a planet in the background or not, it turns out that surprise, surprise, yes, in some sense, there will be fish in space, of course, it is not clear what kind, you need to learn to manage artificial intelligence, of course, yes, of course. and there is actually such a skill that is especially relevant lately, this is industrial engineering, that is, this is the creation of these very texts that are loaded into this black box, in particular yes, although in fact this is the most frequent, let's say, task, although a neural network can create pictures based on other types of data, for example, you can

draw a sketch and ask to make it realistic, also a task for a neural network in general, such as kandinsky, for example, the neural network is named after the great russian artist, who came up with the idea that it would be? yes , and you know, we have actually been working on this task for a long time, about 3 years already, and our first model was called that, it was rudali, she came up with it herself, in short, and we, we kind of thought about how to animate it, or something, say, make it more recognizable, and we decided, she was creating abstract objects at that moment 3 years ago, and we kind of thought, and what russian artists are there who wrote in the style.

at the junction with mathematics, and as if any, any engineering art, it implies that it is necessary to do and invent some new details, new features, slightly make changes to existing architectures, thereby making the algorithm better in terms of the quality of understanding the text, this promt, the visual quality of the image, and actually, when we did kandinsky and do, we set the first scientific such scientific and technical task, firstly to create something new, secondly, to improve the architecture.

what if we just use other people 's neural networks, then we are in some sense limited in what content, how we can influence the creation of content, actually, what we put into the model, we...

such a domestic cultural code, and this concerns not only the domestic cultural code, this concerns any types of data that we want to show to the model, and for this, of course, we need to make our own developments. we continue the podcast of the creative industry, today our guest is denis dimitrov, the man who created the kandinsky neural network. elena kiper and roman karmanov are still with you, and what successes are recognized by zakandinsky already, that's what, what does it do better than its analogues, let's say, analogues is probably the wrong word, well , it seems, then, neural networks that solve the same problem, generating images from text, for example, although, in what are we cooler, although kandinsky videos are now generated, yeah, now, well, that is, already, as if already, we recently presented a model that generates videos, called kandinsky video. although probably it was necessary to call it something like tarkovsky, well they called it kandinsky video,

we will continue this line, but what does it do better, knows the domestic cultural code better, of course, this is what we actually set for the model, what task, and we will certainly develop this further, what is the problem with russian data , here is knowledge of the russian domain, in that there is russian data, of course there is less of it, what does it learn from? the model, it learns from data from the internet, that is, from open pairs of images descriptions, it kind of captures data at the moment of the request, naturally there is a team that deals with the data, that is, the data is already contained in it, it does not search the internet at that moment, no, no, no, in no case, it creates, in this way it is unique where they are stored, this voluminous amount of huge volume of data, this is kandinsky the third studied on one and a half billion pairs of picture text, and you can imagine how much is there

, well, if you go on the internet, then in general there is a lot, yes, that's exactly it, the picture is not half of the data will probably not be of very good quality, all sorts of junk there junk corresponds to the description that is written there below, or it may be that the picture contains a watermark, yeah, it is probably also bad to use such data, because the neural network will reproduce this watermark, it, now they say that artists are already fighting, that is, they spoil their image so as not to, that is also true. yeah, we also need to fight this, that is, there are a huge number of filters that need to be written before,

how to give data to the model, because of course you can't give everything in a row, it's like you know, showing a child everything in a row, it's not clear what he will learn in the end, of course, the data development team is responsible for this, and this is super important and the activity and the team itself, because not half, more than half of the success depends on it. so after the data is stored, here they are in this c3 storage, actually you can teach the model, yeah, teaching the model is just like that iterative viewing of this data and changing this huge number of parameters that i talked about, these billions of parameters that need to be adjusted so that when a new description is dropped into the input, the picture would correspond to it, we have a video that was created by kandinsky. but before watching it, the question is, we are conservative people in general, creatures in ourselves,

and well, okay, even if we are watching some person right now, he thinks, well, denis is telling an interesting story, we need to try, then the internal struggle begins, to allow this artificial intelligence into your life, not to allow, here are the areas that are already actively using artificial intelligence, who has already grabbed onto this, first of all, designers, we have a special tool. it's called fusionbrain.ai and there it is such a developing photo editor. now in general, recently it has been very popular to make photo editors based on or rethink the current one. why is this useful, because it is clear that you can create pictures and edit pictures based on text much, much easier than actually drawing it yourself, which is what people used to do, it took a huge amount of time, now it’s enough to just write in text, the picture will be generated, you don’t like some area, you paint it over, draw what you want, it really

simplifies the work of designers, and very much so, that is, the ability to not just generate an image, but also it... some designers are afraid of this, that we will somehow automate their work, in fact, it’s not like that at all, because artificial intelligence - this is a tool that allows you to simply optimize your work, it is in any profession, and design is no exception at all, there is a routine part. work, it needs to be automated as quickly as possible in my opinion, as efficiently as possible, this will only save people's time, in fact, it will also improve the quality of the content, and animation, for example, how many routines are there, animation is generally the creation of videos, they generally shoot films there, well, they can take years with now this can all happen faster, that is, with

well , to be honest, the technology hasn't matured enough to create full-fledged films yet, but the progress is such... that if you, for 3 years we've been talking about, for 3 years we've been working on neural networks, yes, i mean creating a neural network that generates images based on text, if you look at how neural networks, the best neural network created images 3 years ago, you'll see that it's very, very bad, let's watch a video, let's watch a video, and then i 'll ask my questions, yeah, what is this, denis, you can tell me, i'll comment, it's still animation, it's not a full-fledged video, it was made by kandinsky, yes, it was made by kandinsky, that's how, like, how he does it, he draws the first frame according to the text, and then you choose, that is, how animation differs from video, in that animation is a camera flyby around a static object, well, or some kind of camera movement, and video is a full-fledged movement of everything, here it is animation, after all, because there is a first frame, and then we choose

the camera movement, well, that is, a monotonous camera movement, that's what we choose. i honestly don't remember what exactly the promts were, that is, it doesn't need much memory, it's all created in the cloud somewhere, yes , it's all created on a supercomputer, oh supercomputer, it's an interesting topic, here's the training of the model and the application of the model, well , it's called inference, it requires computing power, the model is huge after all, on an iphone, roughly speaking, it won't run on your smartphone, although

progress is also going in this direction, so that it can run on a smartphone, but at the moment kandinsky is for... a picture in a video, well, and there they are actually, we use it, when you make a request, it flies to a supercomputer, it is processed there, it is there that kandinsky lives, yeah, it is there that he makes a picture from text, the picture comes back to you, there what do you use, a telegram bot or a website. a certain number of iterations, that is, i go into the bot, i say what picture i want to create, a picture comes, then the next stage i say what i want to see for movement, and it gives me animation, i stand in line, waiting for it everything will be, because millions of people in a supercomputer, hop, that's right, yes, but we actually have ways of scaling, after all, a supercomputer contains not one calculator, but many, and of course, if

a million people come, then there will be a queue, this is inevitable. in this sense, as if doing inference on a device, that is, a smartphone, is much better, because you do not stand in line, you do it there, but we try to keep a lot of resources on the supercomputer, so that the queue is satisfied after all, so that there weren't, let's say, a lot of people in the queue at the same time, i wonder why, do you feel that your competitors are spying on you, we do, that is, you feel this attention on yourself, yes, and since they are spying on you, it means that you are doing something that, apparently, causes them, i don't know, it seems to me, with everyone who is engaged in creativity and creates, competitors are spying on something, to be honest, and this is not artificial intelligence, this is not an exception, of course.

as if we were their entire dataset in a folder, we do not post it anywhere, of course, yeah, it is stored there as a certain base, as a certain base, yes, why actually we can't do it differently, because the model needs to be shown, at the training stage, it really needs to be shown pictures, well, that is, it's like a training , really educational material for a related question, this is the first 2800 picture, who is it? after all, the author is artificial intelligence or a person who generated all this, all this in the end, oh, this, this, this is a very good question, in fact, who owns the copyright, in

, like, including at the legislative level all this is being developed and, let's say, at some point it will probably be fixed, although this is a very difficult question, you know, they were just saying, i have an angel on my shoulder, the angel was sitting and he told me, that's when creators have something. the difficulty is actually determining who the author is, there is data, of course, behind each photograph there is some author who took this photograph, that is, there is an author of the photograph, another thing is when there are 1.5 billion of them, then all these authors somehow get mixed up, and most likely the author, the author of one and a half billions of photos, that is, this is a huge number of people, there are millions of people, on the other hand, there is a company that bought a supercomputer with its own money, this is a very super-expensive undertaking.

that is, there are four parties, maybe even more, which, in general, well, some participation in the creation of the final picture, they made their contribution, but so far the story is such that if a person, most likely, if a person, well, as if by logic, each company does it in its own way in the end, if a person, as it were, pays for what he used neural network and got a picture, then he is the author after all, that's most likely it is, and if. motives are guessed, according to motives, usually, if something is created, a license is still issued, i just want to say that such disputes arise only when the picture starts to bring huge money to the author,

then a large number of other people appear who claim authorship, but here in fact there is still a moment that the neural network itself can be, as if companies can claim its authorship, developers and so on, here is the model itself has a license. for example kandinsky and this also depends on, that is, here is a masterpiece - this is a model that is not posted and is not in the public domain, kandinsky is the opposite story, since one of our first missions, i have already talked about this, is to move the community as a whole and move science forward, then we post the model in the public domain, you can use the model, absolutely not for as if without paying some company and deploy it on your own and why create? such a model that is not widely available, so that some limited circle of people can use it, well , in order to sell the generation, we continue

to...

as a person creates a picture, any, any image, any painting, he has some white canvas, well, not necessarily white, well, just white paper, some empty, a napkin, a napkin, yes, there is a tablet screen, he definitely has some idea, he starts sketching out some details there with a pen, a stylus, whatever, adds details, maybe removes something, well, a person also has patterns in his head, that is, he remembered what he has, he has a pattern, this is after training, step by step. he simply creates a picture, like kandinsky creates a model, in principle, you can draw an analogy, he begins to draw a picture from the so-called white noise, what is it, well, this is when there is no signal on the tv, such interference, just some kind of matrix, naturally there is your request, this is the same idea, as if in a person, it is expressed by these signals of neurons, neural networks, it is expressed simply by numbers, which are text, into which the text is encoded and

this matrix step by step in the process of removing noise in the right direction creates an image, that is, the creation of images from this white, this white noise, from this matrix you can simply visualize, that is , there are 100 steps or 1.00 steps after which from any of this noise the final picture is created and visualized, manifested, so to speak, for example, you want to make a pug in space, yeah, you always have white noise at the beginning, and step by step step... it turns out a pug in space at the end of this process, if the noise is slightly different, it is clear that the noise can be any way, that is , swap two pixels there, it will be different, but also a pug in space, this matrix, in some sense it is responsible for the fantasy of the model, this can be visualized, but here - this process, it is called denoising or noise reduction, just so that it happens correctly, here we need to show this neural network one and a half

billion pairs of picture text. without this intermediary, right away from heads to generate their own images, well , let's say on some canvas, i don't know, well, in the sense of digital, of course, in fact, there is research, i wouldn't say that it's just super, there's a lot of practice there and that it 's actively used there, but there are studies that allow you to decode brain signals, well, that is, you know, they put there, you know, a reader of electrical signals in the head

and, for example, you can... you can really train a model that understands you without words and draws a picture, if you need to draw a picture, but the limitation these models are that for each person, for now, you still need to teach your own model, that is, for each person, when he imagines a palm tree, the signals are slightly different, that is, like one model cannot yet be taught to all people, and teaching a model for each person is expensive, and you need

a supercomputer, so until there is some kind of universal thing that everyone understands, this will not happen soon, in general, i hope, i hope that it will not happen soon, and moreover, it will still remain, that is , you should not be afraid of this, even though it sounds futuristic.

with you for some reason we are afraid, there is no need to be afraid, we are engaged in those things that we can be because this is the competitiveness of our country, and it is in the safe hands of people like denis, denis, thank you very much, we are waiting for the next one.

hello, this is the podcast deception of substances. with you olesya nosova, editor-in-chief of komsomolskaya pravda, and with me is my regular host zukhra pavlova, a famous endocrinologist. today we will... talk about eating disorders, and since this topic is at the intersection of physiology and psychology, we invited a famous psychologist, candidate of psychological sciences, natalya fomicheva to visit us. natalya, hello, hello, actually, the first question is, what is an eating disorder, can eating behavior really be upset somehow, we can start with what is normal eating behavior, healthy. well, in general, uh, our

body is designed in such a way that we feel physiological hunger, we eat, feel full, stop eating, and this is the basis of healthy eating behavior, therefore all the problems they start exactly from the place where a person either feels hunger, but ignores it, or does not feel hunger, or does not feel full and overeats, that's how the basis of the disorders is precisely a failure of this perception. processes of sensations of hunger, sensations of fullness, and here a big story is added about the fact that you need to look in some special way, you need to somehow influence your own body, this can be done through food, therefore, for example, i will limit myself in food, i will feel hunger, but ignore it, or i will use food to regulate some emotions and then i will overeat, that is, here from the very beginning...

worry that tomorrow it will be reflected on the scale, or never i looked at myself in the mirror said a bunch of nasty things to myself, that is, a limitation that comes from a feeling, it is essentially not a limitation: i 'm full, that's enough for me, here is a limitation because i need to look somehow - this is exactly the foundation that further leads to breakdowns, because people limit themselves, go on diets, and as we all know from research, 95% of people after 5 years of dieting have more weight than they

started this diet, here's the thing, if you eat very quickly, you will feel full when you have definitely overeaten, than if you eat slowly and you will have time to eat your fill with less, i would generally talk about the awareness of the process of eating itself, that is , eating, the process of consuming food, in a good way it is a separate type of activity when we eat quickly, because... we we are in a hurry, when we are simultaneously scrolling through something on the phone, arguing with family members and doing a bunch of other things, of course we overeat, because satiety is a signal that needs to be caught, it needs to be felt, great, yes, this story about 33 times, joke - this is exactly what i would say about the fact that any artificial introduction of some numbers is excessive, well, someone needs to live 33 times. someone 26, someone 48, here the question

is that we enjoy the process, feel the taste, feel how the food changes its taste, we are in contact with our own body, and this is all a separate process, yeah, well, and if a person enjoys only if he gets a sweet bun, how can he live, isn't that also a disorder? the disorder begins, no, when we have diagnostic criteria by which we can already diagnose this. device, sweet buns are not included in this, we basically evolutionarily prefer sweet food, because it is energy-intensive food, it is food, we need glucose for muscles, for the brain, and it is rare food in a certain sense, yes, the main problem is in that initially, where there was sweet food, there was sugar cane, try to chew it, go get that glucose out of there, fruits, fruits, which still contain fiber and... there the process of the pancreas reacting

to the fact that glucose entered was much smoother, of course, now, when we have industrial sweets, if you overeat just candy, yes or cakes, eh, well, to some extent it will not be very useful for the body, but this does not mean that you need to completely exclude it and sit, and then break down, again, yeah, people need some tangible things, and why 33 doesn't... when there are some numbers, you can practice a little, as they say, then it becomes a reflex, and the person stops counting, but gets used to the fact that food must be chewed, and you know, this movement, when this food is pushed straight through, it's a lump of unchewed, not moistened with saliva, and naturally, there is little sense in this food,

because nothing can be extracted from it, also, so that we don't go too far, to the icd, that same disorder, yes, an eating disorder . the latest version of the handbook of mental disorders appeared there in 2013. avoidant restrictive eating disorder, and we can say that we have an eating disorder, this is bulimia nervosa, anorexia nervosa , overeating syndrome, where concern lies precisely at the heart of this experience of the body, i don’t like my body, and i’m trying

to do something through food with my difficult emotions about how i look, a disorder eating - a completely different category. these are people who, for example, initially have a disturbed sense of hunger, they do not feel it, they forget to eat, they have no idea of ​​​​losing weight, they just do not remember that they need to eat, lucky ones, but i would not say, such children can face developmental disorders due to a lack of nutrients, with a slowdown in growth, in adulthood these are people who understand that it is time to eat after they have lost consciousness from hunger. a common story, you mean? - so far it is very difficult to talk about statistics, because that only in 2013 this began to be discussed as a separate diagnostic category, research is still underway, so it is difficult to talk about some percentages, but in general i think that it will be approximately at the level

of nervous anorexia, somewhere around 1-5% of the population, is this perhaps more associated with people with autism spectrum disorders of the psyche? there are correlations, yes, we really, firstly, in people with autism and autism spectrum disorder we see an eating disorder in the opposite direction we will also see autistic features, but in general there today we can distinguish three groups, these are people who have a very disturbed physiological hunger, plus they have practically no hunger for tastes, so many of us have this story that we ate something, well, we ate soup, a cutlet and now we want something sweet, we are full, but the taste buds need something else, and here it is absent and people can, well, eat the same food, the same taste, they are quite happy with it, they eat little, not varied, and

this is one group, the second group of people - these are people who seem to have very strongly developed nipples, yeah. that is, they are such natural tasters, since childhood they do not like food that has a bright taste for them, and these are children who eat pasta, pasta with cheese and cheese, in my opinion, these are the children who predominate now, that is, they choose food that has a very neutral taste, very understandable, and as a rule, these are just carbohydrates, that is, here , on the contrary, we can see a situation when a person has. excess weight, because also a very unbalanced diet, the third the group is people who in childhood experienced some kind of, well, let's say, trauma in their relationship with food, they choked very badly, got burned, got scared, got poisoned, they have this experience, it kind of begins to change their food.