The Artificial Intelligence Revolution - The Path to Super Intellect
The Artificial Intelligence Revolution - The Path to Super Intellect
This is a translation of an article written by Tim Urban, the author of the blog www.waitbutwhy.com . After reading my hair began to stir from the desire to discuss this article with someone, but there is no place to read it in Russian, so I tirelessly told all my friends. Read - this is cool!
Note: the reason why it took three weeks to write this post is because, while understanding the topic, I just could not believe what I was reading. Pretty quickly, I realized that what is happening in the world of Artificial Intelligence is not just important, but EXTREMELY important to our future. I wanted to learn about it as much as possible, and upon learning, I decided to write a post that could explain WHY this is all so important. In order not to scare you with the length of this text, I broke it into two parts. This is part 1.
')
We are on the verge of change, comparable to the emergence of human life on Earth. Vernor Vinge
What is it like to stand here?
It seems that standing on this place should be quite exciting, but the trick is that being on this line, you do not know what will happen next. So, in fact, it feels like this:
Therefore, we do not feel anything supernatural.
Far future. It will come soon
Imagine that you managed to transfer yourself to a time machine in 1750, where there was no electricity in the world, long-distance communication meant one thing - to yell louder, and all vehicles were fueled with hay. And then imagine that you chose a person there and brought him to our 2015, and then took him outside to see how he reacts to everything. It is difficult to imagine what it would be like to see brilliant streamlined cars flying along the highway at a tremendous (for him) speed; talk to people who were on the other side of the ocean a few hours ago; watch competitions running for 1000 miles; hear a musical concert played 50 years ago and play around with your magic thing that can take pictures of real life, or record a living moment of life, or draw a map and show it yourself in the form of a blue dot that shows where it is. See the face of a man and even talk to him, although he is on the other side of the world. And a bunch of other indescribable wonders. And this is all before you show him the Internet and try to explain what the International Space Station, the Large Hadron Collider, nuclear weapons or the Theory of Relativity are.
These discoveries for him will not be a surprise or surprise - these words are not sufficient to describe the depth of his shocks. He may just die from such a shock.
But what is interesting is that if he returns to his 1750 and tries to crank the same thing with his predecessors and goes back for the same 250 years - in 1500, a person from the 1500th will, of course, be surprised by some things - but not fatally. This journey on the degree of madness will be much weaker, since, although the difference between the world 1500 and 1750 exists, they differ much less than 1750 and 2015. This man of 1500, of course, learns something outlandish about space or physics, about the new attitude towards imperialism in Europe and will reconsider its ideas about the geopolitical map of the world. But observing the everyday life of the 1750th — transport, communications — he will definitely not die.
In fact, in order for a person from 1750 to have fun just like us, he will have to go much further into the past - perhaps before 12000 BC, before the First Agricultural Revolution gave impetus to the development of the first cities and set a new concept for the development of civilization. If those people from the world of hunting-gathering, who were to some extent just one of the animal species, saw the huge empires of 1750 with their churches-towers, ships crossing the ocean, would know that knowledge is accumulated and passed on from generation to generation - then he would just probably die.
But what if, after he died, he became jealous and he decided to do the same trick with his predecessor? Even if he rewinds back another 12,000 years and turns out to be in 24000 BC and takes a man there with him back to 12000 BC That old man will most likely say: “So what? What the hell is that? ”To a man from the 12000s BC will have to reel back more than 100'000 years to find someone who can be surprised by fire and the ability to speak.
In order for someone to be transferred to the future in order to die there from shock, he must be transferred for a sufficient number of years to get a “lethal dose of progress,” PSD. Thus, the SDP was more than 100'000 years in the era of hunting and gathering, but in the post-agricultural revolutionary period fit into 12000 years. The post-industrial world began to evolve so quickly that a 1750-person needs only 250 years to get the CDS.
This model is the acceleration of the speed of development with time - Ray Kurzweil calls the Law of Self-accelerating Development. It is possible, since more developed civilizations are able to progress with greater speed than less developed ones, precisely because they are more developed. In the 19th century, humanity knew more and had more technology than in the 15th, so it is not surprising, and the speed of progress was higher.
It works with simpler examples. The film “Back to the Future” was released in 1985, and the “past” took place in 1955. In the film, Michael J. Fox returned in 1955, and was amazed that the TV sets were new, surprised at the prices for soda, the unpopularity of the electric guitar and the old-fashioned language. It was a different world - for sure, but if the film was made today, and the past happened in 1985, it would be a film about much, much more striking differences. The hero would have appeared at a time when personal computers, the Internet, cell phones did not exist - today's Marty McFly, a teenager born in the late 90s would feel much more differences than Marty in 1955.
This is how the Law of Self-Accelerating Development works. The average rate of progress between 1985 and 2015 was significantly higher than in the period 1955 - 1985 and much more new appeared in the last 30 years.
Thus, moving forward is becoming more significant and faster. This should lead us to the idea of ​​something significant, approaching us from the near future. So?
Kurzweil suggests that the degree of progress realized in the entire 20th century would have been realized in just 20 years, if we take the 2000 progress rate as a reference. In other words, the speed of progress in 2000 is 5 times faster than the average speed of progress in the 20th century. He believes that the same degree of progress as in the 20th century was already implemented between 2000 and 2014, and the next “20th century” stage of progress will be completed by 2021, after some 7 years. In a couple of decades after that, according to his calculations, the “XX-century-old” stage of progress will be implemented several times in a single year, and then - and in general - within a month. In short, as a result of the implementation of the Law of Self-accelerating Development, according to the theory of Kurzweil, in the XI century, the degree of human development will be 1000 times higher than the degree of human development in the twentieth century.
If Kurzweil and many others who agree with him are right, then perhaps we will carry the head off from 2030 to the same extent as the guy from 1750 who happened to be in 2015. In other words, the next "lethal dose of progress" require only a couple of decades, and in 2050 the world can change so much that we may not even be able to fully realize it.
This is not science fiction. This is something that many scientists, much smarter than you or me, firmly believe. And if you delve into history, you will understand that this is completely logical from it.
So why, when you hear, when I say something like "the world in 35 years can be absolutely incomprehensible," you think "Cool, of course, but .... I do not know ...". Here are 3 reasons why we are skeptical about the amazing predictions of the future:
1. When it comes to history, we think linearly. When we imagine progress for the next 30 years, we look back at the previous 30 years and use them as an indicator of how much should happen. When we think about the degree of progress in the XI century, we simply take everything that was collected in the twentieth century, and add it to the year 2000. Exactly the same mistake was made by the dude from the 1750th, when he brought someone from the 1500th and expected that Kondraty would suffice from what he had seen, just like he himself had enough in 2015. It is very natural to think linearly, at a time when we must think exponentially. Anyone who is smarter could predict development for the next 30 years, not looking at the previous 30 years, but taking the current rate of progress and relying on it in his reasoning. Of course, he would have gotten closer to the goal, but he would have missed anyway. To think about the future correctly, it is necessary to understand that events in the future will develop much faster than they develop now.
Red - the trajectory of progress, based on past speed of development
Orange - the trajectory of progress, based on the current speed of development
Green - the trajectory of progress, taking into account the exponential growth
2. The trajectory of the recent past can give a distorted picture. First, even a steep exponential curve looks like a straight line, if you consider only a small segment of it, just as if you look at a small segment of a huge circle - it seems like a straight line. Secondly, the exponential growth does not have to be smooth. Kurtsevale says progress is S-curves:
The S-shaped curve is characterized by periodic explosive growth, and subsequent stabilization.
This development curve passes through 3 phases:
1. Slow growth (initial stage)
2. Rapid growth (next, explosive growth stage)
3. Stabilization (formation and existence of the world in the new development paradigm)
If you look at the near past and look at the current part of the S-curve, you can incorrectly assess how fast progress is moving. For the period 1995-2007, there was an explosive growth of the Internet, the emergence of Microsoft, Google, Facebook, the birth of social networks, cell phones, and then smartphones - this was the second phase. But from 2008 to 2015, breakthroughs were much smaller, at least technologically. Someone who is thinking about the future today could have figured out the last 7 years and formulate a measure of progress - but he will lose sight of the whole picture. In fact, a new era of explosive growth is probably brewing right now.
3. Our experience makes us old obstinate ignoramuses when it comes to the future. We base our ideas on the world on our own experience, and this experience has firmly instilled in our minds the perception of the speed of progress in the recent past into patterns, such as "this is how it happens." We are also limited by our imagination, which uses our experience to shape fantasies about the future. However, what we know, as a rule, does not give us the right tools to predict the future. When we hear a prediction that contradicts our belief about how “it happens”, it is instinctively blocked by our consciousness. If I tell you, further in the text, that you may be living up to 150-250 years old, and maybe you will never die at all, you will instinctively object “Nonsense! If I have at least learned something from history, it is that we will all die! ” And this is true - no one in the past has lived forever. But no one flew on planes until they were invented!
Most likely, while the feeling of “yah, nonsense! ...” seems true to you from reading this article, but perhaps it will pass when you know everything I want to tell you. The facts say that if we just follow the logic and expect that the previous development models will continue to exist, we should expect that much, much more will change in the near future than we can imagine. Logic also suggests that if the greatest minds on Earth continue to move progress at the same accelerating pace, after a while we will all make such a strong leap in development that it will completely change the life we ​​know it and the understanding of what is really developed civilization. If you take some time to learn about what is happening today in science and technology, you will see many signs that suggest that life in its current manifestation will change drastically.
--------------------–-----------------------------
The Path to Super Intellect
What is artificial intelligence?
Most likely, you perceived the concept of “Artificial Intelligence” as some kind of science fiction bike, but recently you heard a couple of times how quite reasonable people seriously mentioned this concept. And it does not fit.
There are three reasons why people misunderstand the concept of Artificial Intelligence:
1. We associate it with feature films. Star Warriors. Terminator. Matrix. This is fantastic, as well as stories about living robots. Movies are forced to perceive Artificial Intelligence as fiction.
2. Artificial intelligence is a very broad concept. It is in calculators and in self-driving cars. He is also Something that can change our world. Artificial intelligence applies to all these concepts and it is confusing.
3. We use Artificial Intelligence constantly in everyday life, unaware that this is He. John McCarthy, who introduced the concept of Artificial Intelligence in 1956, said: "as soon as it starts to work, we no longer call it that." Because of this phenomenon, “Artificial Intelligence” usually sounds more like a mystical prediction of the future than a reality. At the same time, this is perceived as a popular concept from the past that has not been realized in the present. Ray Kurzweil says that hears people saying that the concept of AI has outlived itself in the 80s, and compares this approach with the statement that the Internet died after the dotcom crash in 2000.
Let's see. First, let's stop imagining robots. A robot is a container for Artificial Intelligence, which may or may not have a human-like shape. Artificial intelligence is a computer inside a robot. Artificial intelligence is the mind, the robot is the body. For example, Apple's Siri software is Artificial Intelligence, and the female voice to which he “speaks” is the personification of this Intellect, there is no robot in the physical sense at all.
Secondly, you may have heard the term "singularity" or "technological singularity." This term is used in mathematics to describe a graph in the form of an assymptote, where the normal rules no longer work. In physics, it is used to describe an infinitely small dense black hole or a point into which the entire Universe shrank at the moment before the Big Bang. Once again, this is a situation in which the usual rules no longer work. In 1993, Vernor Vinh wrote a popular essay in which he defined the singularity as a moment in the future when the intelligence of our technologies exceeds our own — the moment when the life we ​​know changes completely and the normal rules stop working. Later, Ray Kurzweil confused everything a bit, defining the singularity, as the moment of time when the Law of Self-Accelerating Development reaches so fast speed that technological progress will occur at infinitely fast speed, the moment after which we will live in a completely new world. I found that today's AI thinkers have stopped using the term “singularity”, since its meaning is, of course, somewhat confused. Therefore, I will not use it too much here (although the concept runs through this article).
And last, since there are many types of AI (since AI is such a broad topic), it is worthwhile to single out several types of Artificial Intelligence, differing in scale.
There are three categories of Artificial Intelligence scale:
1. Specialized Artificial Intelligence (FIC). Sometimes referred to as weak AI. This is the artificial intelligence that specializes in one area. There is an AI who will beat the world chess champion, but this is the only thing he can do. If you ask him how best to save the data on the hard disk, the answer is silence.
2. General Artificial Intelligence (OII). Sometimes referred to as a strong AI or human-level Intellect. This is the kind of intelligence that can compete with a person in all areas. Creating an AIS is a much more difficult task than creating an AII, and we still have to do it. Professor Linda Gottfredson describes rationality as "broad mental abilities that include, among other things, the ability to reason, plan, solve problems, think abstractly, understand complex ideas, learn quickly and learn from mistakes." OII will be able to do these things as easily as you do.
3. Super intelligence. Oxford professor and leading expert in AI, Nick Bostrom, defines Super-intelligence as “intelligence that transcends the best human minds in all areas, including scientific creativity,“ universal human wisdom and social intelligence ”. «-» , , , . . - — , . , , .
, — . — , , , . — -. , , , , , , .
, , :
, :
— , . A few examples:
: , , ABS, , . , , , .
— . , , , — .
- — , . , .
« », , ? Facebook ? -, , , . «, , ...». - , , , , .
- — -, . — , , , , .
, , . ,
, — .
— , , . Facebook.
— . , , ( - ). , , — . — .
- , , . , , - , ( , 2010, - , 1 . . , .
, , - , . - -. , « » — , , , .
, , — , . , , — , , . — , .
, (, , , ) — , . , . , , , , — . , ? — ! , 6- , ? , . «» , , , — . «» , , , — . , , , , « , «», , , ».
, , , , , . , ( ) . , , , , . , , « » . , - - — , , , .
, — , , . — — , , , «» , ?
— , , — :
— . , :
… , , . , : 7 , . , , . , , , , :
, , . , , , «», «», «» «». « » — , «» — .
.
The first key to creating Artificial Intelligence: increasing speed and computing power.
The first thing that must happen in order for OII to become possible is an increase in the power of computer hardware. In order for the AI ​​to be as intelligent as the human brain, it will have to catch up with the brain in computing power. One way to express this characteristic is the total number of operations per second (cps) that the brain is able to implement. This value can be calculated by adding up the speed of each part of the brain.
Ray Kurzweil developed a methodology that uses expert estimates of the speed of operations in one of the brain sections, and then compares the weight of this section with the weight of the whole brain and multiplies proportionally to estimate the total figure. It sounds rather clumsy, but he did it many, many times with different professional assessments of different parts of the brain, and the total figure almost always aimed for 10 ^ 16 or 10 quadrillion operations per second.
To date, the fastest supercomputer, the Chinese Tianhe-2 has surpassed this figure with its 34 quadrillion operations per second. But Tianhe-2 essentially loses to the brain in other parameters with its 720-meter building and even consumption of 24 MW of electrical power (the brain works at 20 W) at a price of 390 million dollars. Such a supercomputer is completely unsuitable for widespread use, and is also not suitable for most industrial or commercial tasks.
Kurzweil suggests that we evaluate computers based on how much speed (cps) we acquire for $ 1,000. And when we can get for $ 1000 "human" 10 ^ 16 cps, then we can assume that the General Artificial Intelligence can become a part of our life.
Moore's Law, a historically confirmed rule, states that the World Maximum Computing Power doubles in about 2 years, meaning that the development of computer hardware, as well as the general development of human civilization, occurs exponentially. According to Kurzweil's classification (in the context of “cps for $ 1000”), we are now at the level of 10 trillion (10 ^ 13) cps for $ 1000 and are moving along such a trajectory:
Those. today's computers for $ 1000 surpass the mouse brain, but their performance is only about a thousandth of a human one. It seems a little, but only until you remember that in 1985 the speed of a computer was one trillionth of human, billionth of 1995th and millionth of 2005. Being in the thousandth in 2015, we’ll reach parity by 2025 at this rate.
Thus, in terms of iron, the computational power required for the implementation of OII is technically available now in China. And we can expect that affordable and widely distributed iron of the OII level will appear in the next 10 years. However, computing power alone will not make a computer reasonable — the next question: how do we combine human intelligence and this computing power?
The second key to making CSI: Make it reasonable
Here is the problem. The fact is that no one knows for sure how to make a computer sensible - scientists are still arguing about how to bring the computer's “intelligence” closer to the human level, that is, for example, explain how to distinguish a dog from any other animal; or the letter "B", written in an unusual handwriting; or distinguish mediocre from excellent movie. There are several theories about this, and one day one of them will work. Here are the three most advanced ones:
1. Copy the human brain.
The closest analogy - as if scientists carefully studied the student at the next desk, who did an excellent job with his studies, and carefully tried to figure out how he does it. But with all the efforts they couldn’t even come close to his results, so in the end they gave up: “to hell with him - just write off his words!” This strategy makes sense - we are at a dead end, developing super-complex computers, and here - a perfect prototype in every (almost!)) Human head.
The scientific world is working intensively on reverse engineering of the human brain to figure out how Evolution managed to create such a cool thing - and optimistic forecasts suggest that we can do it by 2030. As soon as this happens, we will learn all the secrets of the highest efficiency and productivity of the brain and will be able to copy these mechanisms to implement Super Intelligence. One example of computer architecture that uses the principles of the brain is an artificial neural network. It is a network of transistors - neurons connected to each other with their "inputs" and "outputs", and at the initial stage "does not know" anything - absolutely pure lit. The system starts learning, trying to accomplish a task, for example - to recognize handwritten text. And at first, her attempts to guess the letters will be completely messy. But as soon as she was informed that she had done something right, the order of connecting the transistors, which led to the correct answer, gets a higher priority. When the system is wrong, the corresponding connections are lowered in priority. As a result of a large number of iterations according to the trial and error method, the system is self-optimized for the performance of a specific task. The brain works in a similar way, but in a more complex variation. And, studying the brain, we discover elegant and very effective techniques for creating and using neutron networks.
More sophisticated plagiarism involves a strategy called emulation of the whole brain. The task of the strategy is to study the brain layers by scanning and developing its three-dimensional model for its subsequent integration into a powerful computer. Then we would have a computer with the capabilities of the human brain - it only needs to learn and gather information. If the engineers succeed in their plans, they will be able to recreate the brain so precisely that the person’s personality and all the memories can be downloaded to the computer. If, prior to the experiment, the brain belonged to Jim, the computer will “wake up” to Jim (read more about what constitutes a person’s personality here), and it will be the system of General Artificial Intelligence. And after that, we can start working on turning Jim into an unimaginably intelligent Super Intelligence. He will definitely like it.
How far are we from complete imitation of the human brain? To date, it has been possible to imitate the work of the brain of a 1mm worm, consisting of 302 neurons. The human brain contains 100 billion neurons. It may seem like a senseless struggle, but think of the power of exponential progress: now we have defeated the little worm, soon, perhaps, we will catch up with the ant, and then the mouse. And suddenly the ultimate goal will be very real.
2. Try to force Evolution to do for the computer what it has already done for us.
If we decide that copying the success of that student is too difficult, then we can try to figure out how he is preparing for new exams.
Here is something we know: it is possible to build a computer equal in performance to the human brain. But if the brain itself is too complicated to copy, we could copy the Evolution methods instead. In fact, even if we could copy the brain, it could still be something like an attempt to build a plane, trying to copy the flap of a butterfly's wings. It often turns out that it is more efficient to create machines from scratch using a modern, mathematically optimized approach, instead of direct copying of biological processes.
But how can we simulate Evolution to create an OII? The method called “genetic algorithms” should work this way: it is necessary to start the process of performing operations and then evaluating its effectiveness (exactly the same that occurs in the biological world when living creatures live life and are “evaluated” as a result of successful (or not successful a) breeding). A group of computers would reproduce some work, and the most successful of them “mated” among themselves, combining half of their program code into a new computer. Less successful would be destroyed. As a result of a large, very large number of such iterations, this selection would produce more and more sophisticated computers. The challenge is to create an automatic process of assessment and reproduction so that this process can develop on its own.
The disadvantage of this method is that evolutionary processes last a billion years, and we would like to meet a couple of decades.
But we also have advantages over evolution. First, evolution occurs haphazardly, producing much more unnecessary mutations than useful ones. And we could control and direct the process, so that he would move in the direction of really necessary improvements. Secondly, Evolution has no goal, including the achievement of reason. Sometimes Evolution works even against the intellect (since the brain uses a large amount of energy). We, on the contrary, could direct this process in the direction of increasing intelligence. And thirdly, if Evolution had chosen for itself the path of development of the intellect, it would have had to optimize additionally a bunch of additional things - like reconsidering the process of energy production in the cell. While we could just get rid of the solution to this problem, using external electricity. No doubt, we would have coped with this task better than Evolution. However, it is still not clear whether we can evolutionally develop Artificial Intelligence sufficiently.
3. Make it all a computer problem, not ours.
This option comes up when desperate scientists begin to try to force the task to solve itself. Interesting, but perhaps this is the most promising method.
The idea is to build a computer, whose main task would be to do research in the field of Artificial Intelligence and reprogram itself, allowing it not only to learn, but to improve its own architecture. We would teach computers to be computer scientists, so that they can manage the process of their own improvement themselves. And that would be their only task: to figure out how to make themselves more reasonable. Further - more about this.
All this can happen very soon.
Intensive improvements in computer hardware and innovative software experiments are constantly occurring and General Artificial Intelligence can come to life very quickly and unexpectedly for two main reasons:
1. Exponential growth happens very quickly and what looks like a subtle improvement can quickly become an all-encompassing avalanche. Look at the picture:
The volume of Lake Michigan in ounces is approximately equal to the capabilities of our brain (in operations per second). The calculation speed doubles every 18 months. At this speed, progress is barely noticeable for a long time, and ... suddenly, everything is over
2. When it comes to software, progress may be slow, but then some kind of unexpected discovery instantly changes the speed of development (for example, for a long time mankind had great difficulty understanding the structure of the Solar System, and then discovering that all the planets move around the Sun , suddenly made everything much easier). Or if the question concerns a computer that improves itself: it may seem to us that the system is at the very beginning of the path, but after a moment of time it turns out that it is already 1000 times more efficient and approaches the level of human intelligence.
Road from General Artificial Intelligence and Super Intellect
One day we will reach General Artificial Intelligence - computers with a “human level of intelligence”. It turns out such a commune of people and computers living in equality.
Actually, not quite ...
The thing is that OII with an identical human level of intelligence and computing power will still have undeniable advantages over a person:
Iron:
Speed. The maximum "rate of fire" of neurons is around 200 Hz, while today's microprocessors (which are much slower today than they will be when we get to the OII) operate at 2 GHz, or 10 million times faster than our neurons. And the speed of data transmission in the brain, reaching 120 m / s, hopelessly lags behind the computer speed of communication over optical fiber, flying at the speed of light.
Size and volume. The brain is locked into the skull, and its size is limited. Another limitation is again a speed of 120 m / s, which will not allow producing communications on a network created from several human heads at an acceptable speed. Computers can be expanded to an unlimited size, and add an unlimited amount of new capacity, RAM, and hard disk space. All these computer parameters have much greater capacity and accuracy than the human brain.
Reliability and endurance. Not only computer memory is more human. Transistors are more reliable than human neurons, they are less prone to damage with time (and if some go bad, you can simply replace them with new ones). The human brain is also subject to fatigue, while computers can operate at full capacity around the clock for a very long time.
Software:
Editing, enhancements and great features. Unlike the human brain, computer software can receive updates and fixes, allowing you to experiment with it. Improvements can be implemented in areas where the capabilities of the human brain are limited. The algorithms of human vision are phenomenally perfect, while the technical capabilities of the vision system are rather mediocre. Computers will be able to compete with the person in the field of algorithms of view, and in addition receive significant improvements in the field of hardware.
Teamwork. People have surpassed all living things in the field of accumulation and dissemination of knowledge. Starting from the creation of language and association into large and complex social associations, moving forward with the invention of writing and printing, and now even more accelerated using the Internet, Collective Human Knowledge is the main reason for such superiority of man over the rest of the animal world. And computers will be much cooler than us in this: a worldwide network of artificial intelligence, working on one program, could regularly synchronize the accumulated knowledge in all individual computers, and thus, everything that became known to one of them would immediately be replicated on all others. . Such a network could also unite efforts, working on one task, and most importantly - this network would be unknown to dissent or selfishness, which often hamper the development of human civilization.
Artificial Intelligence, which is likely to approach the level of OII through a self-optimization program, will not consider the “human level of intelligence” as an important milestone (this is important only for us) and is unlikely to stop at what has been achieved. And an understanding of the advantages that any OII system of the “human level of rationality” will have makes it obvious that it will overcome the human level and “fly away” in the realm of true Super Intelligence in an instant.
And when this happens, it will most likely be a serious shock for us. The reason is that from our point of view: a) our intelligence exceeds the intelligence of all that surrounds us; b) we believe that smart people are much smarter than stupid ones. Something like this:
Our narrow understanding of rationality: the average person, being in the interval between Einstein (orange line) and some rural fool (green line), looks down on AI: “Ha, how funny this robot tries to repeat monkey tricks!”
As long as the AI ​​moves upward in the degree of rationality, we consider it just becoming smarter compared to an animal. After the AI ​​reaches the lower bar of human rationality (Nick Bolstrom uses the concept of “village idiot”), we will be touched by “Oh, how cute! He's just like that little fool! ” The only trick is that the range of human capabilities (from the idiot to Einstein) is in a relatively short interval, so IMMEDIATELY after overcoming the level of “idiot” and proclaiming the OII system, the system will be smarter than Einstein and we will suddenly find ourselves
and what happens after that?
Explosion of intelligence
I hope you enjoyed the “normal” story, because now this topic will become completely unusual and even scary, and the further the story is, the more serious. I want to pause and remind you that absolutely everything you read and read in this article is real: real science, real predictions of the future from the most famous and respected scientists and thinkers. Just remember this.
, , . , , , , , .
, : , — , . , — , . , . , -. .
: , , , , 2040 . — , 25 . , , ( -) . :
, , , — , 4- . , , - , , — , . -, 170'000 .
- — , , . — IQ=130, — IQ=85. IQ=12'952.
, , : . , - . .
wi-fi, 100, 1000 1 , , — , . , , , — . , , , , — — . , . , , , . :
?
This is a translation of an article written by Tim Urban, the author of the blog www.waitbutwhy.com . After reading my hair began to stir from the desire to discuss this article with someone, but there is no place to read it in Russian, so I tirelessly told all my friends. Read - this is cool!
Note: the reason why it took three weeks to write this post is because, while understanding the topic, I just could not believe what I was reading. Pretty quickly, I realized that what is happening in the world of Artificial Intelligence is not just important, but EXTREMELY important to our future. I wanted to learn about it as much as possible, and upon learning, I decided to write a post that could explain WHY this is all so important. In order not to scare you with the length of this text, I broke it into two parts. This is part 1.
')
We are on the verge of change, comparable to the emergence of human life on Earth. Vernor Vinge
What is it like to stand here?
It seems that standing on this place should be quite exciting, but the trick is that being on this line, you do not know what will happen next. So, in fact, it feels like this:
Therefore, we do not feel anything supernatural.
Far future. It will come soon
Imagine that you managed to transfer yourself to a time machine in 1750, where there was no electricity in the world, long-distance communication meant one thing - to yell louder, and all vehicles were fueled with hay. And then imagine that you chose a person there and brought him to our 2015, and then took him outside to see how he reacts to everything. It is difficult to imagine what it would be like to see brilliant streamlined cars flying along the highway at a tremendous (for him) speed; talk to people who were on the other side of the ocean a few hours ago; watch competitions running for 1000 miles; hear a musical concert played 50 years ago and play around with your magic thing that can take pictures of real life, or record a living moment of life, or draw a map and show it yourself in the form of a blue dot that shows where it is. See the face of a man and even talk to him, although he is on the other side of the world. And a bunch of other indescribable wonders. And this is all before you show him the Internet and try to explain what the International Space Station, the Large Hadron Collider, nuclear weapons or the Theory of Relativity are.
These discoveries for him will not be a surprise or surprise - these words are not sufficient to describe the depth of his shocks. He may just die from such a shock.
But what is interesting is that if he returns to his 1750 and tries to crank the same thing with his predecessors and goes back for the same 250 years - in 1500, a person from the 1500th will, of course, be surprised by some things - but not fatally. This journey on the degree of madness will be much weaker, since, although the difference between the world 1500 and 1750 exists, they differ much less than 1750 and 2015. This man of 1500, of course, learns something outlandish about space or physics, about the new attitude towards imperialism in Europe and will reconsider its ideas about the geopolitical map of the world. But observing the everyday life of the 1750th — transport, communications — he will definitely not die.
In fact, in order for a person from 1750 to have fun just like us, he will have to go much further into the past - perhaps before 12000 BC, before the First Agricultural Revolution gave impetus to the development of the first cities and set a new concept for the development of civilization. If those people from the world of hunting-gathering, who were to some extent just one of the animal species, saw the huge empires of 1750 with their churches-towers, ships crossing the ocean, would know that knowledge is accumulated and passed on from generation to generation - then he would just probably die.
But what if, after he died, he became jealous and he decided to do the same trick with his predecessor? Even if he rewinds back another 12,000 years and turns out to be in 24000 BC and takes a man there with him back to 12000 BC That old man will most likely say: “So what? What the hell is that? ”To a man from the 12000s BC will have to reel back more than 100'000 years to find someone who can be surprised by fire and the ability to speak.
In order for someone to be transferred to the future in order to die there from shock, he must be transferred for a sufficient number of years to get a “lethal dose of progress,” PSD. Thus, the SDP was more than 100'000 years in the era of hunting and gathering, but in the post-agricultural revolutionary period fit into 12000 years. The post-industrial world began to evolve so quickly that a 1750-person needs only 250 years to get the CDS.
This model is the acceleration of the speed of development with time - Ray Kurzweil calls the Law of Self-accelerating Development. It is possible, since more developed civilizations are able to progress with greater speed than less developed ones, precisely because they are more developed. In the 19th century, humanity knew more and had more technology than in the 15th, so it is not surprising, and the speed of progress was higher.
It works with simpler examples. The film “Back to the Future” was released in 1985, and the “past” took place in 1955. In the film, Michael J. Fox returned in 1955, and was amazed that the TV sets were new, surprised at the prices for soda, the unpopularity of the electric guitar and the old-fashioned language. It was a different world - for sure, but if the film was made today, and the past happened in 1985, it would be a film about much, much more striking differences. The hero would have appeared at a time when personal computers, the Internet, cell phones did not exist - today's Marty McFly, a teenager born in the late 90s would feel much more differences than Marty in 1955.
This is how the Law of Self-Accelerating Development works. The average rate of progress between 1985 and 2015 was significantly higher than in the period 1955 - 1985 and much more new appeared in the last 30 years.
Thus, moving forward is becoming more significant and faster. This should lead us to the idea of ​​something significant, approaching us from the near future. So?
Kurzweil suggests that the degree of progress realized in the entire 20th century would have been realized in just 20 years, if we take the 2000 progress rate as a reference. In other words, the speed of progress in 2000 is 5 times faster than the average speed of progress in the 20th century. He believes that the same degree of progress as in the 20th century was already implemented between 2000 and 2014, and the next “20th century” stage of progress will be completed by 2021, after some 7 years. In a couple of decades after that, according to his calculations, the “XX-century-old” stage of progress will be implemented several times in a single year, and then - and in general - within a month. In short, as a result of the implementation of the Law of Self-accelerating Development, according to the theory of Kurzweil, in the XI century, the degree of human development will be 1000 times higher than the degree of human development in the twentieth century.
If Kurzweil and many others who agree with him are right, then perhaps we will carry the head off from 2030 to the same extent as the guy from 1750 who happened to be in 2015. In other words, the next "lethal dose of progress" require only a couple of decades, and in 2050 the world can change so much that we may not even be able to fully realize it.
This is not science fiction. This is something that many scientists, much smarter than you or me, firmly believe. And if you delve into history, you will understand that this is completely logical from it.
So why, when you hear, when I say something like "the world in 35 years can be absolutely incomprehensible," you think "Cool, of course, but .... I do not know ...". Here are 3 reasons why we are skeptical about the amazing predictions of the future:
1. When it comes to history, we think linearly. When we imagine progress for the next 30 years, we look back at the previous 30 years and use them as an indicator of how much should happen. When we think about the degree of progress in the XI century, we simply take everything that was collected in the twentieth century, and add it to the year 2000. Exactly the same mistake was made by the dude from the 1750th, when he brought someone from the 1500th and expected that Kondraty would suffice from what he had seen, just like he himself had enough in 2015. It is very natural to think linearly, at a time when we must think exponentially. Anyone who is smarter could predict development for the next 30 years, not looking at the previous 30 years, but taking the current rate of progress and relying on it in his reasoning. Of course, he would have gotten closer to the goal, but he would have missed anyway. To think about the future correctly, it is necessary to understand that events in the future will develop much faster than they develop now.
Red - the trajectory of progress, based on past speed of development
Orange - the trajectory of progress, based on the current speed of development
Green - the trajectory of progress, taking into account the exponential growth
2. The trajectory of the recent past can give a distorted picture. First, even a steep exponential curve looks like a straight line, if you consider only a small segment of it, just as if you look at a small segment of a huge circle - it seems like a straight line. Secondly, the exponential growth does not have to be smooth. Kurtsevale says progress is S-curves:
The S-shaped curve is characterized by periodic explosive growth, and subsequent stabilization.
This development curve passes through 3 phases:
1. Slow growth (initial stage)
2. Rapid growth (next, explosive growth stage)
3. Stabilization (formation and existence of the world in the new development paradigm)
If you look at the near past and look at the current part of the S-curve, you can incorrectly assess how fast progress is moving. For the period 1995-2007, there was an explosive growth of the Internet, the emergence of Microsoft, Google, Facebook, the birth of social networks, cell phones, and then smartphones - this was the second phase. But from 2008 to 2015, breakthroughs were much smaller, at least technologically. Someone who is thinking about the future today could have figured out the last 7 years and formulate a measure of progress - but he will lose sight of the whole picture. In fact, a new era of explosive growth is probably brewing right now.
3. Our experience makes us old obstinate ignoramuses when it comes to the future. We base our ideas on the world on our own experience, and this experience has firmly instilled in our minds the perception of the speed of progress in the recent past into patterns, such as "this is how it happens." We are also limited by our imagination, which uses our experience to shape fantasies about the future. However, what we know, as a rule, does not give us the right tools to predict the future. When we hear a prediction that contradicts our belief about how “it happens”, it is instinctively blocked by our consciousness. If I tell you, further in the text, that you may be living up to 150-250 years old, and maybe you will never die at all, you will instinctively object “Nonsense! If I have at least learned something from history, it is that we will all die! ” And this is true - no one in the past has lived forever. But no one flew on planes until they were invented!
Most likely, while the feeling of “yah, nonsense! ...” seems true to you from reading this article, but perhaps it will pass when you know everything I want to tell you. The facts say that if we just follow the logic and expect that the previous development models will continue to exist, we should expect that much, much more will change in the near future than we can imagine. Logic also suggests that if the greatest minds on Earth continue to move progress at the same accelerating pace, after a while we will all make such a strong leap in development that it will completely change the life we ​​know it and the understanding of what is really developed civilization. If you take some time to learn about what is happening today in science and technology, you will see many signs that suggest that life in its current manifestation will change drastically.
--------------------–-----------------------------
The Path to Super Intellect
What is artificial intelligence?
Most likely, you perceived the concept of “Artificial Intelligence” as some kind of science fiction bike, but recently you heard a couple of times how quite reasonable people seriously mentioned this concept. And it does not fit.
There are three reasons why people misunderstand the concept of Artificial Intelligence:
1. We associate it with feature films. Star Warriors. Terminator. Matrix. This is fantastic, as well as stories about living robots. Movies are forced to perceive Artificial Intelligence as fiction.
2. Artificial intelligence is a very broad concept. It is in calculators and in self-driving cars. He is also Something that can change our world. Artificial intelligence applies to all these concepts and it is confusing.
3. We use Artificial Intelligence constantly in everyday life, unaware that this is He. John McCarthy, who introduced the concept of Artificial Intelligence in 1956, said: "as soon as it starts to work, we no longer call it that." Because of this phenomenon, “Artificial Intelligence” usually sounds more like a mystical prediction of the future than a reality. At the same time, this is perceived as a popular concept from the past that has not been realized in the present. Ray Kurzweil says that hears people saying that the concept of AI has outlived itself in the 80s, and compares this approach with the statement that the Internet died after the dotcom crash in 2000.
Let's see. First, let's stop imagining robots. A robot is a container for Artificial Intelligence, which may or may not have a human-like shape. Artificial intelligence is a computer inside a robot. Artificial intelligence is the mind, the robot is the body. For example, Apple's Siri software is Artificial Intelligence, and the female voice to which he “speaks” is the personification of this Intellect, there is no robot in the physical sense at all.
Secondly, you may have heard the term "singularity" or "technological singularity." This term is used in mathematics to describe a graph in the form of an assymptote, where the normal rules no longer work. In physics, it is used to describe an infinitely small dense black hole or a point into which the entire Universe shrank at the moment before the Big Bang. Once again, this is a situation in which the usual rules no longer work. In 1993, Vernor Vinh wrote a popular essay in which he defined the singularity as a moment in the future when the intelligence of our technologies exceeds our own — the moment when the life we ​​know changes completely and the normal rules stop working. Later, Ray Kurzweil confused everything a bit, defining the singularity, as the moment of time when the Law of Self-Accelerating Development reaches so fast speed that technological progress will occur at infinitely fast speed, the moment after which we will live in a completely new world. I found that today's AI thinkers have stopped using the term “singularity”, since its meaning is, of course, somewhat confused. Therefore, I will not use it too much here (although the concept runs through this article).
And last, since there are many types of AI (since AI is such a broad topic), it is worthwhile to single out several types of Artificial Intelligence, differing in scale.
There are three categories of Artificial Intelligence scale:
1. Specialized Artificial Intelligence (FIC). Sometimes referred to as weak AI. This is the artificial intelligence that specializes in one area. There is an AI who will beat the world chess champion, but this is the only thing he can do. If you ask him how best to save the data on the hard disk, the answer is silence.
2. General Artificial Intelligence (OII). Sometimes referred to as a strong AI or human-level Intellect. This is the kind of intelligence that can compete with a person in all areas. Creating an AIS is a much more difficult task than creating an AII, and we still have to do it. Professor Linda Gottfredson describes rationality as "broad mental abilities that include, among other things, the ability to reason, plan, solve problems, think abstractly, understand complex ideas, learn quickly and learn from mistakes." OII will be able to do these things as easily as you do.
3. Super intelligence. Oxford professor and leading expert in AI, Nick Bostrom, defines Super-intelligence as “intelligence that transcends the best human minds in all areas, including scientific creativity,“ universal human wisdom and social intelligence ”. «-» , , , . . - — , . , , .
, — . — , , , . — -. , , , , , , .
, , :
, :
— , . A few examples:
: , , ABS, , . , , , .
— . , , , — .
- — , . , .
« », , ? Facebook ? -, , , . «, , ...». - , , , , .
- — -, . — , , , , .
, , . ,
, — .
— , , . Facebook.
— . , , ( - ). , , — . — .
- , , . , , - , ( , 2010, - , 1 . . , .
, , - , . - -. , « » — , , , .
, , — , . , , — , , . — , .
, (, , , ) — , . , . , , , , — . , ? — ! , 6- , ? , . «» , , , — . «» , , , — . , , , , « , «», , , ».
, , , , , . , ( ) . , , , , . , , « » . , - - — , , , .
, — , , . — — , , , «» , ?
— , , — :
— . , :
… , , . , : 7 , . , , . , , , , :
, , . , , , «», «», «» «». « » — , «» — .
.
?
The first key to creating Artificial Intelligence: increasing speed and computing power.
The first thing that must happen in order for OII to become possible is an increase in the power of computer hardware. In order for the AI ​​to be as intelligent as the human brain, it will have to catch up with the brain in computing power. One way to express this characteristic is the total number of operations per second (cps) that the brain is able to implement. This value can be calculated by adding up the speed of each part of the brain.
Ray Kurzweil developed a methodology that uses expert estimates of the speed of operations in one of the brain sections, and then compares the weight of this section with the weight of the whole brain and multiplies proportionally to estimate the total figure. It sounds rather clumsy, but he did it many, many times with different professional assessments of different parts of the brain, and the total figure almost always aimed for 10 ^ 16 or 10 quadrillion operations per second.
To date, the fastest supercomputer, the Chinese Tianhe-2 has surpassed this figure with its 34 quadrillion operations per second. But Tianhe-2 essentially loses to the brain in other parameters with its 720-meter building and even consumption of 24 MW of electrical power (the brain works at 20 W) at a price of 390 million dollars. Such a supercomputer is completely unsuitable for widespread use, and is also not suitable for most industrial or commercial tasks.
Kurzweil suggests that we evaluate computers based on how much speed (cps) we acquire for $ 1,000. And when we can get for $ 1000 "human" 10 ^ 16 cps, then we can assume that the General Artificial Intelligence can become a part of our life.
Moore's Law, a historically confirmed rule, states that the World Maximum Computing Power doubles in about 2 years, meaning that the development of computer hardware, as well as the general development of human civilization, occurs exponentially. According to Kurzweil's classification (in the context of “cps for $ 1000”), we are now at the level of 10 trillion (10 ^ 13) cps for $ 1000 and are moving along such a trajectory:
Those. today's computers for $ 1000 surpass the mouse brain, but their performance is only about a thousandth of a human one. It seems a little, but only until you remember that in 1985 the speed of a computer was one trillionth of human, billionth of 1995th and millionth of 2005. Being in the thousandth in 2015, we’ll reach parity by 2025 at this rate.
Thus, in terms of iron, the computational power required for the implementation of OII is technically available now in China. And we can expect that affordable and widely distributed iron of the OII level will appear in the next 10 years. However, computing power alone will not make a computer reasonable — the next question: how do we combine human intelligence and this computing power?
The second key to making CSI: Make it reasonable
Here is the problem. The fact is that no one knows for sure how to make a computer sensible - scientists are still arguing about how to bring the computer's “intelligence” closer to the human level, that is, for example, explain how to distinguish a dog from any other animal; or the letter "B", written in an unusual handwriting; or distinguish mediocre from excellent movie. There are several theories about this, and one day one of them will work. Here are the three most advanced ones:
1. Copy the human brain.
The closest analogy - as if scientists carefully studied the student at the next desk, who did an excellent job with his studies, and carefully tried to figure out how he does it. But with all the efforts they couldn’t even come close to his results, so in the end they gave up: “to hell with him - just write off his words!” This strategy makes sense - we are at a dead end, developing super-complex computers, and here - a perfect prototype in every (almost!)) Human head.
The scientific world is working intensively on reverse engineering of the human brain to figure out how Evolution managed to create such a cool thing - and optimistic forecasts suggest that we can do it by 2030. As soon as this happens, we will learn all the secrets of the highest efficiency and productivity of the brain and will be able to copy these mechanisms to implement Super Intelligence. One example of computer architecture that uses the principles of the brain is an artificial neural network. It is a network of transistors - neurons connected to each other with their "inputs" and "outputs", and at the initial stage "does not know" anything - absolutely pure lit. The system starts learning, trying to accomplish a task, for example - to recognize handwritten text. And at first, her attempts to guess the letters will be completely messy. But as soon as she was informed that she had done something right, the order of connecting the transistors, which led to the correct answer, gets a higher priority. When the system is wrong, the corresponding connections are lowered in priority. As a result of a large number of iterations according to the trial and error method, the system is self-optimized for the performance of a specific task. The brain works in a similar way, but in a more complex variation. And, studying the brain, we discover elegant and very effective techniques for creating and using neutron networks.
More sophisticated plagiarism involves a strategy called emulation of the whole brain. The task of the strategy is to study the brain layers by scanning and developing its three-dimensional model for its subsequent integration into a powerful computer. Then we would have a computer with the capabilities of the human brain - it only needs to learn and gather information. If the engineers succeed in their plans, they will be able to recreate the brain so precisely that the person’s personality and all the memories can be downloaded to the computer. If, prior to the experiment, the brain belonged to Jim, the computer will “wake up” to Jim (read more about what constitutes a person’s personality here), and it will be the system of General Artificial Intelligence. And after that, we can start working on turning Jim into an unimaginably intelligent Super Intelligence. He will definitely like it.
How far are we from complete imitation of the human brain? To date, it has been possible to imitate the work of the brain of a 1mm worm, consisting of 302 neurons. The human brain contains 100 billion neurons. It may seem like a senseless struggle, but think of the power of exponential progress: now we have defeated the little worm, soon, perhaps, we will catch up with the ant, and then the mouse. And suddenly the ultimate goal will be very real.
2. Try to force Evolution to do for the computer what it has already done for us.
If we decide that copying the success of that student is too difficult, then we can try to figure out how he is preparing for new exams.
Here is something we know: it is possible to build a computer equal in performance to the human brain. But if the brain itself is too complicated to copy, we could copy the Evolution methods instead. In fact, even if we could copy the brain, it could still be something like an attempt to build a plane, trying to copy the flap of a butterfly's wings. It often turns out that it is more efficient to create machines from scratch using a modern, mathematically optimized approach, instead of direct copying of biological processes.
But how can we simulate Evolution to create an OII? The method called “genetic algorithms” should work this way: it is necessary to start the process of performing operations and then evaluating its effectiveness (exactly the same that occurs in the biological world when living creatures live life and are “evaluated” as a result of successful (or not successful a) breeding). A group of computers would reproduce some work, and the most successful of them “mated” among themselves, combining half of their program code into a new computer. Less successful would be destroyed. As a result of a large, very large number of such iterations, this selection would produce more and more sophisticated computers. The challenge is to create an automatic process of assessment and reproduction so that this process can develop on its own.
The disadvantage of this method is that evolutionary processes last a billion years, and we would like to meet a couple of decades.
But we also have advantages over evolution. First, evolution occurs haphazardly, producing much more unnecessary mutations than useful ones. And we could control and direct the process, so that he would move in the direction of really necessary improvements. Secondly, Evolution has no goal, including the achievement of reason. Sometimes Evolution works even against the intellect (since the brain uses a large amount of energy). We, on the contrary, could direct this process in the direction of increasing intelligence. And thirdly, if Evolution had chosen for itself the path of development of the intellect, it would have had to optimize additionally a bunch of additional things - like reconsidering the process of energy production in the cell. While we could just get rid of the solution to this problem, using external electricity. No doubt, we would have coped with this task better than Evolution. However, it is still not clear whether we can evolutionally develop Artificial Intelligence sufficiently.
3. Make it all a computer problem, not ours.
This option comes up when desperate scientists begin to try to force the task to solve itself. Interesting, but perhaps this is the most promising method.
The idea is to build a computer, whose main task would be to do research in the field of Artificial Intelligence and reprogram itself, allowing it not only to learn, but to improve its own architecture. We would teach computers to be computer scientists, so that they can manage the process of their own improvement themselves. And that would be their only task: to figure out how to make themselves more reasonable. Further - more about this.
All this can happen very soon.
Intensive improvements in computer hardware and innovative software experiments are constantly occurring and General Artificial Intelligence can come to life very quickly and unexpectedly for two main reasons:
1. Exponential growth happens very quickly and what looks like a subtle improvement can quickly become an all-encompassing avalanche. Look at the picture:
The volume of Lake Michigan in ounces is approximately equal to the capabilities of our brain (in operations per second). The calculation speed doubles every 18 months. At this speed, progress is barely noticeable for a long time, and ... suddenly, everything is over
2. When it comes to software, progress may be slow, but then some kind of unexpected discovery instantly changes the speed of development (for example, for a long time mankind had great difficulty understanding the structure of the Solar System, and then discovering that all the planets move around the Sun , suddenly made everything much easier). Or if the question concerns a computer that improves itself: it may seem to us that the system is at the very beginning of the path, but after a moment of time it turns out that it is already 1000 times more efficient and approaches the level of human intelligence.
Road from General Artificial Intelligence and Super Intellect
One day we will reach General Artificial Intelligence - computers with a “human level of intelligence”. It turns out such a commune of people and computers living in equality.
Actually, not quite ...
The thing is that OII with an identical human level of intelligence and computing power will still have undeniable advantages over a person:
Iron:
Speed. The maximum "rate of fire" of neurons is around 200 Hz, while today's microprocessors (which are much slower today than they will be when we get to the OII) operate at 2 GHz, or 10 million times faster than our neurons. And the speed of data transmission in the brain, reaching 120 m / s, hopelessly lags behind the computer speed of communication over optical fiber, flying at the speed of light.
Size and volume. The brain is locked into the skull, and its size is limited. Another limitation is again a speed of 120 m / s, which will not allow producing communications on a network created from several human heads at an acceptable speed. Computers can be expanded to an unlimited size, and add an unlimited amount of new capacity, RAM, and hard disk space. All these computer parameters have much greater capacity and accuracy than the human brain.
Reliability and endurance. Not only computer memory is more human. Transistors are more reliable than human neurons, they are less prone to damage with time (and if some go bad, you can simply replace them with new ones). The human brain is also subject to fatigue, while computers can operate at full capacity around the clock for a very long time.
Software:
Editing, enhancements and great features. Unlike the human brain, computer software can receive updates and fixes, allowing you to experiment with it. Improvements can be implemented in areas where the capabilities of the human brain are limited. The algorithms of human vision are phenomenally perfect, while the technical capabilities of the vision system are rather mediocre. Computers will be able to compete with the person in the field of algorithms of view, and in addition receive significant improvements in the field of hardware.
Teamwork. People have surpassed all living things in the field of accumulation and dissemination of knowledge. Starting from the creation of language and association into large and complex social associations, moving forward with the invention of writing and printing, and now even more accelerated using the Internet, Collective Human Knowledge is the main reason for such superiority of man over the rest of the animal world. And computers will be much cooler than us in this: a worldwide network of artificial intelligence, working on one program, could regularly synchronize the accumulated knowledge in all individual computers, and thus, everything that became known to one of them would immediately be replicated on all others. . Such a network could also unite efforts, working on one task, and most importantly - this network would be unknown to dissent or selfishness, which often hamper the development of human civilization.
Artificial Intelligence, which is likely to approach the level of OII through a self-optimization program, will not consider the “human level of intelligence” as an important milestone (this is important only for us) and is unlikely to stop at what has been achieved. And an understanding of the advantages that any OII system of the “human level of rationality” will have makes it obvious that it will overcome the human level and “fly away” in the realm of true Super Intelligence in an instant.
And when this happens, it will most likely be a serious shock for us. The reason is that from our point of view: a) our intelligence exceeds the intelligence of all that surrounds us; b) we believe that smart people are much smarter than stupid ones. Something like this:
Our narrow understanding of rationality: the average person, being in the interval between Einstein (orange line) and some rural fool (green line), looks down on AI: “Ha, how funny this robot tries to repeat monkey tricks!”
As long as the AI ​​moves upward in the degree of rationality, we consider it just becoming smarter compared to an animal. After the AI ​​reaches the lower bar of human rationality (Nick Bolstrom uses the concept of “village idiot”), we will be touched by “Oh, how cute! He's just like that little fool! ” The only trick is that the range of human capabilities (from the idiot to Einstein) is in a relatively short interval, so IMMEDIATELY after overcoming the level of “idiot” and proclaiming the OII system, the system will be smarter than Einstein and we will suddenly find ourselves
and what happens after that?
Explosion of intelligence
I hope you enjoyed the “normal” story, because now this topic will become completely unusual and even scary, and the further the story is, the more serious. I want to pause and remind you that absolutely everything you read and read in this article is real: real science, real predictions of the future from the most famous and respected scientists and thinkers. Just remember this.
, , . , , , , , .
, : , — , . , — , . , . , -. .
: , , , , 2040 . — , 25 . , , ( -) . :
, , , — , 4- . , , - , , — , . -, 170'000 .
- — , , . — IQ=130, — IQ=85. IQ=12'952.
, , : . , - . .
wi-fi, 100, 1000 1 , , — , . , , , — . , , , , — — . , . , , , . :
?
Source: https://habr.com/ru/post/293156/
All Articles