Download "Нейробиологи дешифровали мысли в текст | ПУШКА #57"

Please wait. We're preparing links for easy ad-free video watching and downloading.

Previous video: Бизнес на киборгах: кто делает протезы в России? / Послезавтра Next video: Тим Кук сам на себя не похож, Дроны становятся совершеннее, DeepFake заменит не только лицо

0:00

как научились «читать мысли»

9:36

мегапроект по мозгу + реклама курса, за который платишь, если только устроился потом на работу

11:47

научились считывать «видения»

15:50

и проникают во сны

20:01

благодарности

Тим Кук сам на себя не похож, Дроны становятся совершеннее, DeepFake заменит не только лицо

Тим Кук сам на себя не похож, Дроны становятся совершеннее, DeepFake заменит не только лицо

Channel: Кик Обзор

Бизнес на киборгах: кто делает протезы в России? / Послезавтра

Бизнес на киборгах: кто делает протезы в России? / Послезавтра

Channel: Послезавтра

✅Нашли ГОРОД ПРИЗРАК Атомщиков на Ядерном полигоне ☢️ где испытывали атомное оружие

✅Нашли ГОРОД ПРИЗРАК Атомщиков на Ядерном полигоне ☢️ где испытывали атомное оружие

Channel: KREOSAN

Куркумин: Когда Лень Пить Много Добавок

Куркумин: Когда Лень Пить Много Добавок

Channel: CleverMind

Сельхозтехника будущего. Топ интересных видео

Сельхозтехника будущего. Топ интересных видео

Channel: Klaptik TV

Первые проблески разума у машины: разбор исследования | Пушка #53

Первые проблески разума у машины: разбор исследования | Пушка #53

Channel: SciOne

Энергетики: RedBull, Adrenaline Rush, Burn

Энергетики: RedBull, Adrenaline Rush, Burn

Channel: CleverMind

Топ 4 Мифа о Ноотропах [ОШИБКИ ЮЗЕРОВ]

Топ 4 Мифа о Ноотропах [ОШИБКИ ЮЗЕРОВ]

Channel: CleverMind

Apple представила гарнитуру смешанной реальности. Samsung создает свой чат-бот.

Apple представила гарнитуру смешанной реальности. Samsung создает свой чат-бот.

Channel: ВИЗИОНЕР

Возможно, мы проиграли | ALI

Возможно, мы проиграли | ALI

новости

загадки

тайны

открытия

наука

изобретения

технологии

техника

будущее

эксперименты

опыты

прогресс

мозг

интеллект

нейроны

нейронауки

нейробиология

нейросети

ИИ

искусственный интеллект

машинное обучение

нейроинтерфейсы

чтение мыслей

нейролинк

протезы

Пушка

Влад Гончарук

scione

сайуан

сцыван

скайван

скайуан

скиван

00:00:01

when knowledge and technology reaches

00:00:04

such a density that begins to work

00:00:05

for each other, we get something like a

00:00:08

thermonuclear reaction, new

00:00:10

ideas and technologies are synthesized and we get a chance to

00:00:13

reach a new level of development, the same

00:00:16

special time is now coming in the

00:00:18

research of our brain, the source of

00:00:20

our most valuable opportunities and

00:00:23

achievements throughout history, this

00:00:25

fall, almost unnoticed, the news went almost unnoticed

00:00:27

that a thought decoder was invented at the University of Texas,

00:00:29

this is the wording of

00:00:32

journalists and not the authors, but they

00:00:34

really did what can be

00:00:36

called that, a person silently thought something and at the

00:00:39

output the researchers received his thoughts

00:00:41

in the form of text, the authors initially set,

00:00:45

of course, not the same task to encrypt the

00:00:46

inner voice; they learned to decode individual words or

00:00:49

even phrases from thoughts into text

00:00:52

only based on data on brain

00:00:54

activity, and before there was nothing

00:00:56

surprising here, now the task was

00:00:59

to decode the entire stream,

00:01:01

once you start thinking, and now

00:01:04

the machine, like a shameless typist,

00:01:06

translates in plain text what is in your

00:01:09

head, but most existing

00:01:11

methods of accessing your thoughts require

00:01:14

brain surgery and the implantation of electrodes

00:01:16

can only be suitable for those who are already being

00:01:19

examined, for example, paralyzed

00:01:21

people or those who are facing an already

00:01:24

difficult operation and they are not averse to helping science at the same time;

00:01:27

for the rest, this is too

00:01:29

risky a method. Usually, through

00:01:32

electrodes implanted into the brain, neuroscientists

00:01:34

monitor the electrical activity of the

00:01:35

motor cortex, that is, in the area that is

00:01:38

mainly responsible for movement,

00:01:41

including the lips, and according to the signals that the brain

00:01:43

voluntarily or involuntarily sends to the lip muscles

00:01:45

and are trying to decipher what a person

00:01:48

says in his head, neuroscientists and

00:01:51

Stichas decided to test a fundamentally

00:01:53

different idea. Is it possible, without surgery,

00:01:55

which already radically limit the

00:01:57

use of technology without a direct

00:01:59

connection to the brain, to take some

00:02:02

data about the processes in it in order to

00:02:04

decipher a person’s inner speech

00:02:06

and all flow of speech and not individual

00:02:10

words and phrases. In the future, if it

00:02:12

works out, of course, with modifications this

00:02:15

would allow not only to restore

00:02:18

the ability to communicate with the outside

00:02:20

world to completely paralyzed people or with speech impairments, but also to expand the capabilities of

00:02:22

healthy people, for example, to help

00:02:25

those who are not very strong in

00:02:27

expressing themselves thoughts, if we let’s

00:02:29

connect a client to a text generator

00:02:31

like gpt chat, then it would already produce a

00:02:34

collapsible match, and even in the desired style,

00:02:36

simply based on your thoughts, or you

00:02:39

could find out what you really think

00:02:42

but don’t notice about yourself or what you don’t

00:02:45

even want confess

00:02:46

reveal true thoughts Can you imagine

00:02:50

how this could help psychotherapy Well,

00:02:52

or marketers or hypothetically

00:02:55

find out what a person is trying to hide when

00:02:57

applying for a job or during interrogation, which is not

00:03:00

always the case or what is more likely

00:03:03

to be checked at a completely different level,

00:03:06

for example in court, truth or lies Says

00:03:08

man, and if we consider that there have been serious

00:03:12

advances in deciphering the pictures that

00:03:13

our brain sees, then we can go

00:03:16

even deeper and get seriously closer to the

00:03:19

possibility of live broadcasting dreams of

00:03:21

hallucinations or just imagination. But more

00:03:25

about this a little later in the video, so back in the

00:03:27

fall, researchers from Texas

00:03:29

managed to show that without surgery

00:03:31

you can decipher the stream of internal speech, it really

00:03:34

came out very, very crookedly,

00:03:36

so much so that they themselves said it

00:03:38

cannot yet be used even for communication between

00:03:40

paralyzed people, but the other day they

00:03:43

released a new work and there is already a breakthrough;

00:03:45

this time neuroscientists crossed their

00:03:48

technology with a large language model

00:03:50

gpt So now the prospects are completely

00:03:53

different, it looks like a fantasy of a person

00:03:56

being put into a tomograph, a person thinks and the

00:03:58

output is a transcript of thoughts, but

00:04:01

they had to make a serious

00:04:03

compromise so that it would be so simple and

00:04:05

without getting directly into the convolutions instead of

00:04:07

more or less direct data,

00:04:09

for example about Researchers can only obtain electrical activity

00:04:11

directly from neurons by

00:04:12

doing an

00:04:15

MRI scan from the outside, that is, you can see very

00:04:18

indirect information about the processes in the brain

00:04:20

on the scan. How it changes Yes, in very

00:04:23

detail, in the details of the

00:04:25

oxygen saturation of the blood in the brain, it

00:04:29

really changes depending on the

00:04:30

activity with which your head is occupied

00:04:32

here and now, but still it’s like

00:04:36

trying to understand what’s happening today by looking at the traffic of cars on the roads of the city.

00:04:39

For example, you can say that it’s

00:04:41

the weekend if everyone is going to shopping centers and theaters, but it’s

00:04:44

unlikely that

00:04:46

you can reliably clarify just by traffic activity. Or maybe it’s

00:04:50

some kind of holiday then what exactly is

00:04:53

March 8th or Valentine's Day or

00:04:55

something else and this is where

00:04:57

artificial intelligence technologies made it possible to

00:04:59

compensate for the weakness of the method,

00:05:01

introduce it to a new level,

00:05:03

researchers knew that a system like gpt

00:05:05

use something like maps of meaning, which

00:05:08

allows them to produce meaningful

00:05:10

texts for humans Although such systems

00:05:12

simply don’t know in advance what will happen at

00:05:14

the end of the text, they don’t work at all

00:05:17

like we thought of something and select the

00:05:19

words for it no, that’s why they produce

00:05:21

the text as if they were typing Here and now they

00:05:24

predict each step like this Step by step the

00:05:26

next piece of text Which is better

00:05:29

to put these pieces are called

00:05:31

tokens on the website of the creators of gpt Open ai

00:05:34

you can enter any text and see how

00:05:37

it looks for their system as a set

00:05:39

of pieces these are syllables and words, but there are also

00:05:42

individual letters and from individual

00:05:44

pieces to collect words and phrases are,

00:05:46

of course, good, but how about

00:05:48

they all come together into something

00:05:50

connected? With such a blind

00:05:52

perspective, you start saying one thing and

00:05:54

go somewhere unknown, you need

00:05:56

something like maps by which the machine

00:05:59

would navigate how words are related to

00:06:01

each other, for example, by meaning and

00:06:04

These are the kind of maps you can create, they

00:06:06

are called embeddings, you can read in more detail

00:06:08

as always. From the links under the video,

00:06:10

this is the solution: with the help of similar

00:06:13

maps, it would be possible to associate different

00:06:15

changes in brain activity with meanings and

00:06:18

not individual dictionary meanings, since

00:06:21

we have such indirect data about

00:06:23

brain processes then and We need to capture the general meaning of

00:06:25

what a person is thinking now and not try to

00:06:27

literally translate it into text so that

00:06:30

researchers can build such

00:06:32

maps. Each volunteer had to

00:06:35

spend 16 hours in an MRI listening to Podcasts

00:06:38

literally every day so the algorithm could

00:06:40

compare This is the text A person

00:06:43

hears This is how

00:06:45

his brain behaves the same mile a second and it turns out a map of

00:06:48

meanings with which you can now do and

00:06:52

vice versa give an algorithm to show him

00:06:54

the activity of the brain and in response receive a

00:06:57

text from him what the person in the pereska thinks

00:07:01

not literally not word for word and they made the

00:07:04

volunteers a tomograph now showing

00:07:06

videos without sound And here are the thoughts the

00:07:09

algorithm was decoding at this time. I

00:07:11

look around and notice two guys in front of

00:07:13

me and immediately start screaming. They

00:07:16

fly by. And one of them grabs my

00:07:19

hand and pulls me forward towards him, he moves towards

00:07:21

my face. I can’t avoid the blow, he

00:07:25

knocks me down. from his feet and falls to the

00:07:27

ground with the same result. It was a

00:07:29

very slow movement that took

00:07:32

minutes, in the end the guy was exhausted and so

00:07:35

on. Volunteers and the decoder were tested

00:07:37

and in another way people also had to

00:07:40

listen to some kind of recorded story in the tomograph

00:07:42

or imagine a story. in your

00:07:44

imagination, that is, to fantasize,

00:07:46

something was more or less said, and here it became

00:07:49

especially clear how it works and

00:07:51

what the problems are so far. For example, if the

00:07:54

podcast said I don’t have a

00:07:55

driver’s license yet, then the decoder

00:07:58

gave this: she hasn’t started learning to drive

00:08:01

yet a good result, but as soon as

00:08:03

a person thought

00:08:05

about something else while listening, the decoder produced

00:08:08

nonsense that was not even related to what the

00:08:11

test subjects were listening to at that moment, that is, the

00:08:14

person in the tomograph should be

00:08:16

focused on thoughts. And these thoughts

00:08:19

should not yet be completely free, but be

00:08:22

asked some kind of consistent

00:08:24

material such as films of conversations, a

00:08:25

podcast or an audio book, these are just the first

00:08:28

steps. So I would not rush

00:08:30

to predict the fate of the technology. Now

00:08:32

decryption only works personally,

00:08:35

that is, you. You cannot just take it and

00:08:37

scan and read your thoughts, you

00:08:39

must first train the algorithm

00:08:42

on your scans. A these are many

00:08:45

long hours in a tomograph, but the

00:08:47

fundamental ability to read minds,

00:08:49

listen to your inner voice, seems to have

00:08:52

no longer become rabid and science fiction. Therefore,

00:08:54

in the authoritative scientific magazine Nation,

00:08:57

literally a few days later, an

00:08:59

article was published where they began to raise the question of the

00:09:02

risks and ethics of using

00:09:04

such technologies. However, if you

00:09:06

compare the pace With what

00:09:09

ethical and other ethical questions do we answer and,

00:09:12

most importantly, do we or do we not bring these

00:09:14

answers into practice and at what pace is

00:09:17

technology now developing? I’m not sure

00:09:20

that we can keep up. Although we must try.

00:09:22

Of course we must, meanwhile we are already

00:09:25

making our way deep into the brain to our dreams and

00:09:27

imagination about what I’ll tell you after a

00:09:29

short chapter about a mega-project in

00:09:31

neuroscience and advertising courses for which

00:09:33

you pay only if you were able to get a job after them.

00:09:39

This year the

00:09:41

world’s largest brain research project, the Human

00:09:43

Brain Project, ends 10 years ago. It united

00:09:46

teams of neuroscientists from all over Europe and

00:09:48

other regions in The

00:09:49

investigators were given the most powerful

00:09:51

supercomputers at their disposal, and all this to create an

00:09:54

advanced scientific and technological

00:09:56

infrastructure for studying the brain for the

00:09:58

decade ahead, which is interesting,

00:10:01

given the scope and goals, it cost only 607

00:10:05

million euros. One of the main tasks

00:10:07

that the participants solved was to create a new

00:10:09

tool for research and

00:10:11

collaboration, is it a joke? scientists

00:10:13

from 123 institutes and universities

00:10:16

Therefore, if you go to the page where

00:10:18

they post the Source code that they create

00:10:20

as part of the project, then you can see

00:10:23

what languages Java scientists use, as a

00:10:26

rule, for managing servers and for

00:10:28

working with databases, the most important thing for

00:10:30

collaboration is for this and appreciates toad at

00:10:33

Kata Academy are so confident in him

00:10:35

that they offer a unique training opportunity for the market

00:10:39

with payment after employment; in an

00:10:41

agreement with the student, they guarantee the

00:10:43

minimum salary in the specialty

00:10:45

after graduation of 100 thousand rubles per month,

00:10:47

according to their statistics, already this year more than

00:10:50

80 percent of graduates receive 150

00:10:53

thousand rubles and above no installment

00:10:55

loans and fees passed the entrance

00:10:57

tests start studying from the very

00:10:59

beginning assesses motivation

00:11:01

readiness to complete the program to the end

00:11:03

after each block of knowledge looks at

00:11:06

academic performance it doesn’t matter no problem

00:11:08

say goodbye And you don’t pay anything after

00:11:10

mastering the theory practice a large

00:11:12

team project where you work in

00:11:14

conditions close to real, all

00:11:16

your studies are supervised by experienced mentors at the

00:11:18

attack academy, they are very interested

00:11:19

in you reaching the end and then graduating and

00:11:23

joining the company, if for some

00:11:25

reason you cannot find a job in your

00:11:27

specialty, you also do not pay for your studies,

00:11:29

that is, the only thing you need

00:11:31

investing to start the course and go

00:11:33

all the way requires effort, time and perseverance, and you

00:11:37

pay when

00:11:39

it starts to pay off for you,

00:11:40

follow the link under the video,

00:11:43

cat course at the Java Academy Development and up to the strength of the

00:11:45

road going back

00:11:49

in the eleventh year, scientists learned to

00:11:52

reconstruct from signals in the

00:11:54

human brain What on the left he sees clips

00:11:57

that were shown to a person and on the right

00:12:00

that they managed to recreate the algorithm then the

00:12:02

result As you can see, it was very, very

00:12:04

conditional, although important. And here is what the

00:12:07

researchers have now achieved in the

00:12:09

work published the other day: at the top are the

00:12:11

original frames of a black and white film And

00:12:14

at the bottom is a picture created by the algorithm Based on the

00:12:16

signals in the brain, you will agree that it is

00:12:19

very difficult to distinguish from the original, that’s the

00:12:21

progress in 11 years, but there are nuances in the

00:12:24

old work, they used MRI and the

00:12:26

experimental subjects were people in the new work.

00:12:28

Experimental mice and data are obtained from

00:12:31

electrodes implanted not just in the brain, but

00:12:34

in the visual cortex where

00:12:36

signals are processed the incoming retinas of our eyes,

00:12:38

otherwise everything is already familiar to you,

00:12:40

they used something like a value map, the

00:12:42

same imbining algorithm was first

00:12:45

trained on a mouse with electrodes when it was

00:12:47

shown the same excerpt from the film, the

00:12:49

program identified patterns in

00:12:52

changes in electrical activity, and

00:12:54

then when the algorithms gave signals

00:12:56

only so that it can recreate what the

00:12:59

mouse sees, it generates frame by frame with an

00:13:03

accuracy of 95%, researchers are more

00:13:06

and more actively trying to combine

00:13:08

several developments from different fields at once,

00:13:10

especially from the field of artificial

00:13:12

intelligence. So, they have already learned to reconstruct from MRI scans

00:13:15

without surgery,

00:13:18

albeit not in such detail like in mice, what

00:13:21

our human brain sees, the research

00:13:23

also turned out to be very dense

00:13:26

at the top, the pictures that were shown to the

00:13:28

experimental subjects and at the bottom, images reconstructed

00:13:31

only from brain activity,

00:13:33

which is especially interesting. In

00:13:36

this work, a

00:13:38

personal approach is no longer necessary; it is not necessary

00:13:40

to learn the algorithm from data for a specific

00:13:42

person, in order to get a tolerable

00:13:44

result, you don’t have to be stuffed into

00:13:47

tomographs, you don’t have to be kept there for hours. The

00:13:49

fact is that there are some general

00:13:51

patterns in activity for

00:13:53

any brain, for example in one place.

00:13:55

Everyone is more or less active if we see

00:13:57

a face and if it’s a landscape, what’s more in other

00:14:00

areas, too, more or less For everyone, the

00:14:03

details of the activity of one brain will,

00:14:04

of course, differ from the other, it turns out

00:14:07

that With this approach we are dealing only

00:14:09

with something very approximate, very

00:14:11

conditional, how then with such a degree of

00:14:14

abstraction can we collect a concrete face of the landscape animal?

00:14:17

restore the picture of what the

00:14:20

brain sees now in a dream or in reality And

00:14:22

here neuroscientists from Japan have already figured out

00:14:25

how to use

00:14:29

image generators like

00:14:31

stable Di Fusion or MFA Johnny to solve the problem.

00:14:36

the system uses these

00:14:39

words to create a picture, so if we

00:14:41

establish connections, this is Brain

00:14:43

activity such and such a concept, these are

00:14:46

MRI scans - This is more likely when a person

00:14:48

sees bear scans When an airplane, then we

00:14:52

will be able to turn data on

00:14:54

brain activity into a set of words, not into a picture, into

00:14:57

text description And these text

00:15:00

descriptions remain to be fed to the

00:15:02

image generator like this, if to simplify things very much,

00:15:04

neuroscientists have achieved quite

00:15:06

high quality, as if decoding

00:15:08

visual images, the pictures were in

00:15:11

the head, it became available to everyone, the accuracy

00:15:13

reaches 80 percent, the

00:15:15

next logical step would be to

00:15:17

try this approach for recording

00:15:19

pictures in the imagination or even dreams after all, it does

00:15:22

n’t matter to the brain what exactly

00:15:25

activates its visual cortex; signals

00:15:27

from the eyes or from other regions of the brain

00:15:29

when we remember, dream or just

00:15:31

fantasize; if at the same time we seem to

00:15:35

see pictures within ourselves, then this means

00:15:37

that the visual cortex is working. So

00:15:39

perhaps we are not so far away in

00:15:42

order to give a way out to what is actually

00:15:44

hidden in our heads not only

00:15:46

through words but also through digitized

00:15:49

visions,

00:15:53

here it is worth remembering another very

00:15:55

interesting technology that they can

00:15:57

try. Connect with other ones that are

00:15:59

already charging each other, dream incubation, I

00:16:03

talked about here in this video and I

00:16:05

’ll also remind you briefly over the last

00:16:07

few years, neuroscientists have begun

00:16:09

to create scientific instruments that

00:16:10

should help implement something in a

00:16:13

dream, not quite like in the movie

00:16:16

Inception, where the victim was given false

00:16:18

Memories or an idea, for example,

00:16:20

to transfer the company to another person,

00:16:23

woke up and believed that he himself began

00:16:25

to think this way, while we are talking about much more

00:16:27

modest things like individual images,

00:16:29

here is a square, a dream, here is a circle, this is

00:16:32

necessary for studying the nature and function of

00:16:34

dreams, a purely scientific task, purely

00:16:37

scientific interest, it may only seem

00:16:40

that we already understand a lot about this

00:16:42

phenomenon of the brain about dreams, so So

00:16:43

researchers use sensors to

00:16:45

determine when the brain of a sleeping person is

00:16:48

most receptive to external

00:16:50

stimuli and at this time exposes

00:16:53

Volunteers to smells, sounds of

00:16:56

flashing lights or even speech to

00:16:58

influence the content of their dreams, success

00:17:02

so far is very modest, well,

00:17:04

except to direct sleep but not ask them

00:17:07

to create some images that

00:17:10

were not in a dream, but the attempts themselves were

00:17:12

enough to raise

00:17:14

alarm among some scientists here, more than 40

00:17:17

researchers from around the world from leading

00:17:18

research centers Harvard

00:17:21

Cambridge Lund Paris Berlin Geneva

00:17:23

warned colleagues in an open letter that

00:17:25

corporations are already flirting with

00:17:28

technology, not understanding what a big

00:17:29

responsibility this is, you can’t do that, but it

00:17:32

was in an advertising campaign for a beer brand

00:17:35

where neuroscientists, commissioned by the company,

00:17:38

allegedly incubated the dreams of experimental subjects and instilled in

00:17:40

them images from a drink advertisement, a scientific

00:17:43

publication then was not pure

00:17:45

marketing, but they used real

00:17:48

scientists and real experiments real

00:17:51

methods and this was 4 years ago Now

00:17:54

the situation is completely different Then

00:17:56

neuroscientists called to intervene and

00:17:58

protect people from such unscrupulous games

00:18:01

with the brain, the state should intervene, but

00:18:03

everyone happily forgot about the letter and very quickly

00:18:06

forgot about the problem, but

00:18:08

new opportunities to penetrate the brain and

00:18:12

play appeared. with it they can bring both good

00:18:14

and evil and no one can predict what

00:18:16

more, besides, new opportunities are

00:18:19

appearing faster and more often that doing

00:18:22

nothing will not work banning unless something

00:18:26

happens is pointless others

00:18:27

will take advantage of the opponent’s stupor

00:18:29

developments are carried out in parallel by different

00:18:31

countries, let’s say a portable

00:18:34

decoder appears thoughts, we are introducing licenses for it

00:18:37

as for a weapon. And on what basis should

00:18:39

these licenses be limited? For the

00:18:42

purposes of using a psychotherapist, it is possible, but

00:18:44

for private interrogations, it is impossible. But for

00:18:47

police and intelligence services, it is possible. And who

00:18:50

said that for the illegal, unethical and

00:18:52

dangerous use of something

00:18:55

a license is needed? And in general, someone’s or resolution

00:18:57

No no, I don’t want to

00:19:01

scare you with something from the videos. I’m just trying

00:19:03

to understand what I’m observing and sharing

00:19:05

questions that I’m not the

00:19:07

only one who has questions. Well, that’s what you can be

00:19:09

sure of: more and more

00:19:12

interesting hybrid technologies will appear in

00:19:14

brain research: especially important

00:19:15

This can give the

00:19:18

impetus for development that has been so lacking in recent years;

00:19:21

there have been no fundamental

00:19:23

discoveries of great achievements for a very long time. I’m not saying

00:19:26

that they have to appear like new

00:19:28

clothing models on schedule every season, but

00:19:30

still it’s these breakthroughs of these

00:19:34

achievements that we are waiting for because that only

00:19:36

such big breakthroughs allow

00:19:38

us to hope for solving the most important

00:19:40

mysteries of the brain, for example, what is the neural

00:19:43

nature of many mental

00:19:45

disorders such as schizophrenia or

00:19:47

destructive brain conditions such as

00:19:49

Alzheimer's syndrome. So, of course, we

00:19:51

need new tools, new

00:19:53

capabilities and technologies for discoveries that will

00:19:55

forever change the lives of

00:19:58

millions and millions for the better. people all over the

00:20:00

world

00:20:01

friends Thank you for your support using

00:20:04

this button on Patreon for foreign

00:20:06

cards for Russian ones on boost and service

00:20:08

to support the creativity of authors rendly

00:20:10

to me there is a minimum commission special

00:20:13

thanks to Dmitry Orlov Pavel

00:20:15

Novikov Petr Kondaurov Alexander

00:20:16

Korystkina Andrey field idebager

00:20:18

Pavel Dunaev Anton Plgunov Pavel

00:20:20

Khabchinsky Alena Vysokova Oleg

00:20:22

Pavel Valentov Rinat Balbekov

00:20:24

Maxim Mendeleev

00:20:26

Vasilisa Vershusus Evgeny Balakhnin Dmitry

00:20:28

Abramov Konor Lyanor Pavel Valentov 137

00:20:31

hours of the universe Open Launchi

00:20:33

see Vladimir Podgorniy

00:20:34

Shevelev Seryogovsky

00:20:36

Alexander Ahaha

00:20:39

Roman Boronin Borinwa Borinwa Borinwa La thanks for

00:20:41

support Vlad was his likes and comments,

00:20:43

this is the Shroud of peaceful skies to us and

00:20:46

see you

00:20:47

[music]

Description:

Тот самый курс по Java-разработке с оплатой после трудоустройства и гарантированной зарплатой от 100 тысяч рублей: https://kata.academy/java/postpayment Что вас ждёт в ролике: 00:00 - как научились «читать мысли» 09:36 - мегапроект по мозгу + реклама курса, за который платишь, если только устроился потом на работу 11:47 - научились считывать «видения» 15:50 - и проникают во сны 20:01 - благодарности Ссылки: https://docs.google.com/document/d/1vXak3q3Wd7RfF4MPOt-xAj295S5JIHpD-Cz0OHWbics/edit Спасибо за поддержку! Российские карты: https://friendly2.me/support/scione/ https://boosty.to/scione Зарубежные карты https://www.patreon.com/SciOne BTC bc1qs4cnnk2h2pw78x74f58fd3zzxv7yvsgeztlvcg ETH 0x98b846A01397F32d67Ef57615a00f5bD654E701f Если кого-то забыли, напишите мне! OkOdyssey [собака] proton.me Хранители SciOne Дмитрий Орлов, Павел Новиков, Пётр Кондауров, Александра Корысткина, Андрей Полевой Покровители SciOne iDebugger, Павел Дунаев, Антон Пальгунов, Павел Борский, Xabchinsk, Алёна Мыцыкова, Олег Жин, Павел Валентов, Ринат Бальбеков, Максим Менделев, Владимир Ямщиков, Василиса Версус, Евгений Балахнин, Дмитрий Абрамов, Konorlevich, Павел Валентов, 137_число_вселенной, Сообщество Оупен Лонгивити, Владимир Подгорный, Алексей Шевелёв, Серёга, Павел Петриковский, Александр АХО, RateKing, Станислав Чернин, Роман Бородуля Вносят вклад в развитие SciOne Sergo Oganov, Mathic Society, Daniel, Sergey Belov-Fishilevich, Andrew Yarmola, Konstantin Zhernosenko, Chokotto, Андрей Гордиевский, Vadanta, blanc, Victor Bolshakov, John Kramer, Evgeni SpirTanol, Кирилл Высотин, AlexGrimm, Никита Чемерис, Pavel Marchenko, Виктор Павлов, Roman Gelingen, Александр Тайгар, pervprog, Aleksey Goglov, Dmitry Luzanov, Олег Трофим, Алексей Ефимов, Виталий Савельев, Александр Шнитко, Lexx, Natalia Ivannikova, Slafffka Æ, D1ana Drozhzh1na, Максим Фалалеев, overlelik, smaximov, Александр Каторгин, Надежда Мещерякова, Егор Богданов, Женя Воронин, Артемедий Макаров, Вячеслав Карташев, ТяниКрип, Sanchokihana, Александр Денисов, Оксана Мироненко, Phil, Igor Egorov, Yuri Grachevski, Оксана Мироненко, Александр Денисов, Konstantin Bozhikov, deeflash, bolknote.ru, leonhetch, Андрей Зарембо, Александра Бордер, Sanchokihana, Pavel Shtanipopravel, Всеволод Осипович, Dmitry Araslanov, О нас заботятся Белозьоров Владимир, Zaur Aslanov, Eugen Zinchenko, Anton Bolotov, Konstantin Bredyuk, Evgenii Beschastnov, Nataliia Tomilova, Eugene Trufanov, Александр Ляшенко, Mathic Society, Elena Aitova, Alexei Popovici, Dmitry, yauheni kanavalik, Artem Gnatenko, Glebiys, Natallia Barysevich, Ivan Emanov, Ivan Bondarenko, Igor Komarov, Anastasiya Matusyak, Daniel, Olga Koumrian, r00t3g, Пахан и Танюха, Anton Morya, Pmdsoon, Shanren, doomwood, Павел Глазков, rizn.org Виталий Рябенко, Programmable Artificial Life, Egor, Vally Pepyako Anton Vasiljev, Вячеслав Шаблинский, lutersergei, Natallia Barysevich,, Александр Вивтоненко, Сергей Паскаль, Никита Друба, Александр Петровский, Wolkow, Эд-Эд, ATVANT, Сергей Крестов, Varvara Spirina, Михаил Х., Pavel Agurov, Konstantin Bredyuk, Roman, Konstantin Yanko, Mark Menshow, Artem Gnatenko, Glebiys, Natallia Barysevich, Ivan Emanov, Ivan Bondarenko, Дмитрий Черкасов, Irina Davletchina, Sergey Vorontsov, Даниил Иваник, User100, Павел Иванов, Светлана, lutersergei, Андрей Родионов, Павел Глумов, Kiryl Lutsyk, Artemee Lemann, Alexander Mordvintsev, Майор Айсберг, Артём Новиков, Светлана, Александр Гор, Alexander Klek, Сергей Крестов, hArtKor, Иван Смирнов, Светлана, Daniel All, Эльвира Хисматуллина, GrigZZ, Pmdsoon, Vasilii Pankratov, Ирина Ведерникова, Андрей Родионов, Вячеслав из Altterra Нам помогают Георгий Журавлев, Dmitry Salnikov, Pumba abmup, Alex Abdugafarov, Hanna Kalesnikava, Jimi Jimi, Chumva, Arseny, Robert Grislis, Sergey Mertuta, максим крупенко, Boris Dus, Igor Khlebalin, Eugene Vyborov, Ugnius Bareikis, David Malko, Nick Starichenko, Olha, Ivan Liakhovenko, Igor Petetskih, Ahmet, Костянтин Хорозов, Shockster, Anton Mick, Aleksey Serebryakov, Ihar Kryvanos, Stanislav Vain, Vasya Pupkin, Dmitrii komarevtsev, Сергей Белорусец, Dmitry Dikun, Lidia Shkorinenko, Olga Bykov, Yurii Ryzhykh, Viktoria Bril, Roman Tsyupryk, Alexander Novikov, Serafim Nenarokov, Vadim Shender, DroidCartographer Сергей Дробов, Stanislav K, Андрей Козелецкий, Александр Семилетов, Константин Попов, Светлана, Дмитрий Смирнов, Михаил С, Зураб Мгеладзе, Pavel Koryagin, Виталий Хамин, ont rif, Наташа Подунова, Mr. B. Goode, Olya Mikheeva, Дмитрий Викторов, kRen0, Duory, Денис Петрик, Данил Закальский, Eu

Preparing download options

Popular

HD video

Only sound

All

* — If the video is playing in a new tab, go to it, then right-click on the video and select "Save video as..."

** — Link intended for online playback in specialized players

Questions about downloading video

How can I download "Нейробиологи дешифровали мысли в текст | ПУШКА #57" video?

http://unidownloader.com/ website is the best way to download a video or a separate audio track if you want to do without installing programs and extensions.
The UDL Helper extension is a convenient button that is seamlessly integrated into YouTube, Instagram and OK.ru sites for fast content download.
UDL Client program (for Windows) is the most powerful solution that supports more than 900 websites, social networks and video hosting sites, as well as any video quality that is available in the source.
UDL Lite is a really convenient way to access a website from your mobile device. With its help, you can easily download videos directly to your smartphone.

Which format of "Нейробиологи дешифровали мысли в текст | ПУШКА #57" video should I choose?

The best quality formats are FullHD (1080p), 2K (1440p), 4K (2160p) and 8K (4320p). The higher the resolution of your screen, the higher the video quality should be. However, there are other factors to consider: download speed, amount of free space, and device performance during playback.

Why does my computer freeze when loading a "Нейробиологи дешифровали мысли в текст | ПУШКА #57" video?

The browser/computer should not freeze completely! If this happens, please report it with a link to the video. Sometimes videos cannot be downloaded directly in a suitable format, so we have added the ability to convert the file to the desired format. In some cases, this process may actively use computer resources.

How can I download "Нейробиологи дешифровали мысли в текст | ПУШКА #57" video to my phone?

You can download a video to your smartphone using the website or the PWA application UDL Lite. It is also possible to send a download link via QR code using the UDL Helper extension.

How can I download an audio track (music) to MP3 "Нейробиологи дешифровали мысли в текст | ПУШКА #57"?

The most convenient way is to use the UDL Client program, which supports converting video to MP3 format. In some cases, MP3 can also be downloaded through the UDL Helper extension.

How can I save a frame from a video "Нейробиологи дешифровали мысли в текст | ПУШКА #57"?

This feature is available in the UDL Helper extension. Make sure that "Show the video snapshot button" is checked in the settings. A camera icon should appear in the lower right corner of the player to the left of the "Settings" icon. When you click on it, the current frame from the video will be saved to your computer in JPEG format.

What's the price of all this stuff?

It costs nothing. Our services are absolutely free for all users. There are no PRO subscriptions, no restrictions on the number or maximum length of downloaded videos.