Artificial intelligence: how and where to study - experts answer. Neural networks: how artificial intelligence helps in business and life
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- Bridges of Nizhny Novgorod
- Chronicles of the emerging world
See what "AI (meaning)" is in other dictionaries:
implications of theory- VALUES OF THEORY. The concept of meaning in the analytical philosophy of language is actually an analogue of what in the philosophy of consciousness is called “mind”, “consciousness” (English), or “Geist” (German), i.e. consciousness, spirit. In terms of meaning ... ... Encyclopedia of Epistemology and Philosophy of Science
AGE VALUES RELATED TO- well-consistent age values obtained by the lead isotope method according to decomp. isotope ratios. They testify to the good preservation of the milk and the reliability of the found abs. age. Syn .: age values are concordant. ... ... Geological encyclopedia
VALUES OF THE SECOND DERIVATIVES OF THE GRAVITATIONAL POTENTIAL NORMAL- theoretical values of the derivatives of the potential, corresponding to the idealized model of the Earth. They are negligible or exactly equal to zero, therefore the measured values of the second derivatives of the gravitational potential can be practically considered ... ... Geological encyclopedia
GRAVITY VALUES NORMAL- (g 0) theoretical values of the force of gravity acting on a unit mass correspond to such a model of the Earth, in which the density inside the spherical shells is constant and changes only with depth. The structure of their analytical expression ... ... Geological encyclopedia
AGE VALUES DISCORDANT- syn. the term meanings of age are inconsistent or divergent. Geological Dictionary: in 2 volumes. M .: Nedra. Edited by K. N. Paffengolts and others. 1978 ... Geological encyclopedia
AGE VALUES, NON-AGREED OR DEPENDENT- obtained by the lead isotope method according to four dec. Isotopic ratios:, and strongly divergent in magnitude. They testify to the poor preservation of the baby and to the violation of the radioactive balance in it between the maternal and ... ... Geological encyclopedia
AGE VALUES- syn. the term meanings of age are consistent. Geological Dictionary: in 2 volumes. M .: Nedra. Edited by K. N. Paffengolts and others. 1978 ... Geological encyclopedia
abnormal operating mode parameter values- data of abnormal operation [Intent] Parallel texts EN RU The P63x generates a large number of signals, processes binary input signals, and acquires measured data during fault free operation of the protected object as well as fault ... ...
Terms and concepts of general morphology: Dictionary-reference
verb orientation meanings- Values of spatial modification of actions and their derivatives ... Dictionary linguistic terms T.V. Foal
values (voltage) between line and earth- - [Ya.N. Luginsky, M.S.Fezi Zhilinskaya, Y.S.Kabirov. English Russian Dictionary of Electrical Engineering and Electric Power Engineering, Moscow, 1999] Subjects of electrical engineering, basic concepts EN line to ground values ... Technical translator's guide
Books
- Plural Values in Russian, A. Potebnya. Reproduced in the original author's spelling of the 1888 edition (Voronezh publishing house). V…
I didn’t move and hardly breathed ... Surely, they had already lost my trail ... I got out of the hiding place and came face to face with one of them ... He screamed, but could not move ... The game crashed again
Artificial intelligence (AI) in video games is something most of us don't notice until it breaks. It is invisibly present in everything, influencing our gaming experience, our perception of every game moment, but it is one of the most overlooked elements of video games. AI is the condiment that gives the game its flavor, immerses us in the game world like nothing else.
Everyone understands the term "artificial intelligence" differently. This term can refer to the software processes that control the characters in the game, individual objects in the game, or even opponents that you will never see (such as in real-time strategy games).
Let's turn to Alien: Isolation. Random glitches aside, let's face it: this is a great game! One of the only movie-games that allow you to feel yourself inside the movie. Alien: Isolation makes you really feel like a participant in the action of an Alien movie. Every Alien movie has a clear goal: to get rid of the alien. Many individual moments of the films could turn into interesting gameplay, be it climbing Dallas through the ventilation with a flamethrower, or Ripley, ramming the Queen in a loader-mechanic. These films, like video games, are very energizing, their universe is very well suited for "gambling".
The game Alien: Isolation is strong precisely because of its artificial intelligence. The Alien must act in such a way that the player feels like a participant in the Alien films. The Alien himself is a complex creature, which gives a lot of gameplay possibilities. He hides, thoughtfully using the design of the rooms. He moves through the ventilation, unexpectedly attacking players. He hates fire, so we can use flamethrowers against him. At the same time, the game sets certain limits on the difficulty. We know how it works life cycle Aliens. We know they bleed with acid. We know about their collective intelligence. In other words, the Alien films have created a compelling sandbox for game developers.
Every decision you make in Isolation goes back to the Outsider. How are you hiding? How do you use precious flamethrower fuel? How long do you wait for him to leave? You are faced with a real, living Alien who will act and think like an alien. It's amazing, scary and amazing at the same time!
Most gamers and developers believe that "strong AI" is, in fact, impossible. This would mean that it must equal or even exceed human intelligence. It would hardly be comfortable to play with this.
Strong AI will be very similar to another player, with the same game goals: he wants to win. A good AI doesn't want to win, it wants you to work hard to earn your winnings. This is why Alien is not so much a realistic simulation of the greatest movie monster as a recreation of the impressions of him.
In Isolation, the Alien is almost always there. Of course, you can distract him for a while, or move from one room to another, but he will always end up nearby. More often than not, the Alien acts believable, with the exception of rare cases when he is inexplicably hanging out in one room, while you hold your breath and hope that he will leave so that you can get out of the closet.
The stranger always seems to know your location approximately, which keeps you in suspense and uncertainty. He does not immediately notice you (except for rare "glitches"), if you do not fail stealth. This is great for maintaining the atmosphere of a horror movie, but sometimes the moment drags on and the game starts to feel fake. Sometimes the game focuses so much on creating tension that it forgets the much more important thing - immersion.
Funnily enough, due to the marketing overdrive, the word "immersion" has almost lost all meaning. Now any game that can hold attention boasts "immersion." But the meaning was originally different: when you plunge into the ocean, you exist inside the ocean.
In the 1990s, the Immersive Sim concept emerged. The idea was that players can exist in the game world and treat it like reality. The most famous of the '90s immersive sims were System Shock and Thief: The dark Project. Both of these games were developed by Looking Glass Studios, and both had a strong focus on artificial intelligence.
A game without good AI is like a collection of empty films. The whole collection is good, but the movie is based on its characters. Great AI breathes life into the characters of the game and its world. It is the most important component in playful repetition of an immersive movie experience.
For good example"Immersive sim" in action, let's remember Thief: The Dark Project. The game takes place in a fantasy world, you play as a thief named Garrett. One mission sends you to an underground ruin. The area of the map is inhabited by special zombies. They cannot be crushed into pieces like ordinary ones. They revolt back shortly after you have killed them. The only way to really get rid of them is to use holy water on your expensive water arrows, which usually extinguish torches, allowing you to hide in the dark. When a zombie notices you, it roars, warning other zombies, who roar for the next. So it was possible to gather a crowd of all the zombies on the level. If there were not enough arrows or holy water, they had to think over a plan.
For example, you could sneak to the balcony above a room with two or three zombies, secretly shoot one so that he would call all the zombies into the room with a roar, then start shooting them with holy water
That is, the game created space, created enemies that had a logical set of rules, and to which very real logic could be applied.
Therefore, a game with good AI works more like Thief than Isolation. Tension is very important to an Alien game, but immersion should be the foundation. If a game is no longer believable, it’s not that scary anymore.
Of course, for immersion to work, we have to buy into the gimmick of the director or developer. The Alien movie will not work if someone in front of the screen tells us that the alien has not really escaped from the human chest. Therefore, in order to work, Alien: Isolation must make us believe in its reality. The game should be interactive, that is, even more realistic than any of the films. The game must be addictive. Rules must be meaningful and consistent.
If you or the game break this relationship, the game stops being scary and the experience falls apart. When people hunting the player suddenly freeze, or when the Alien "teleports" behind his back, this breaks the immersion and draws out of the gaming experience. He ceases to be scary, which is the whole point of the Alien, in the first place.
We play Alien games because we want to relive the experience of meeting an Alien. When the artificial intelligence breaks down or chitters, the immersion is lost and the game falls apart. But when the AI works as it should, then we become Ripley, hiding in a locker, holding our breath, waiting for the monster to leave.
Japanese algorithm wrote a book"The day the Computer wrote the novel." Despite the fact that people helped the inexperienced writer with the characters of the characters and storylines, the computer did a great job - as a result, one of his works passed the selection stage of the prestigious literary award. Neural Networks have also written sequels to Harry Potter and Game of Thrones.
In 2015, the AlphaGo neural network, developed by the Google DeepMind team, became the first program to beat a professional go player. And this May the program beat the strongest go player in the world, Ke Tse. This was a breakthrough since for a long time computers were not thought to have the intuition needed to play go.
Safety
A development team from the University of Technology Sydney has unveiled drones for patrolling beaches. The main task of the drones will be search for sharks in coastal waters and warn people on beaches... Video data analysis is performed by neural networks, which significantly affected the results: the developers claim that the probability of detecting and identifying sharks is up to 90%, while an operator watching video from drones successfully recognizes sharks only in 20-30% of cases.Australia has the second largest number of shark attacks on humans in the world after the United States. In 2016, 26 cases of shark attacks were recorded in this country, two of which resulted in the death of people.
In 2014, Kaspersky Lab reported that their antivirus registers 325,000 new infected files daily. At the same time, a study by Deep Instinct showed that new versions of viruses practically do not differ from previous ones - the change is from 2% to 10%. The self-learning model developed by Deep Instinct, based on this information, is capable of high precision identify infected files.
Neural networks are also able to look for certain patterns in how information is stored in cloud services, and report detected anomalies that can lead to a security breach.
Bonus: neural networks guard our lawn
In 2016, 65-year-old NVIDIA engineer Robert Bond ran into a problem: Neighborhood cats regularly visited his site and left traces of their presence, which annoyed his wife, who works in the garden. Bond immediately cut off the too unfriendly idea of constructing traps for uninvited guests... Instead, he decided to write an algorithm that would automatically turn on garden water sprinklers when cats approached.Robert was faced with the task of identifying cats in the video stream coming from an external camera. To do this, he used a system based on the popular Caffe neural network. Each time the camera observed a change in the situation on the site, it took seven pictures and transmitted them to the neural network. After that, the neural network had to determine if there was a cat in the frame, and, if the answer was yes, turn on the sprinklers.
Image from a camera in the Bond courtyard
Before starting work, the neural network was trained: Bond "fed" it 300 different photos cats. By analyzing these photographs, the neural network learned to recognize animals. But this turned out to be not enough: she correctly identified cats only in 30% of cases and took Bond's shadow for a cat, as a result of which he himself turned out to be wet.
The neural network worked better after additional training on more photos. However, Bond warns that a neural network can be trained too much, in which case it will develop an unrealistic stereotype - for example, if all the pictures used for training are taken from one angle, then artificial intelligence may not recognize the same cat from another angle. Therefore, it is extremely important to correctly select the training data series.
After a while, the cats, trained not in photographs, but in their own skin, stopped visiting the Bond site.
Conclusion
Neural networks, a technology from the middle of the last century, are now changing the way entire industries work. The reaction of society is ambiguous: some of the possibilities of neural networks are delighted, while others are forced to doubt their usefulness as specialists.However, not everywhere machine learning comes in, it crowds out humans. If a neural network makes diagnoses better than a living doctor, this does not mean that in the future we will be treated exclusively by robots. Most likely, the doctor will work together with the neural network. Likewise, the IBM Deep Blue supercomputer beat Garry Kasparov at chess back in 1997, but the people from chess have not gone anywhere, and eminent grandmasters still end up on the covers of glossy magazines.
Cooperation with machines is far more beneficial than confrontation. Therefore, we have compiled a list of publicly available materials that will help you continue your acquaintance with neural networks:
Artificial intelligence is a technology that we will definitely take with us into the future.
We will tell you how it works and what cool applications it found.
😎 The "Technologies" heading is published every week with the support of re: Store.
What is artificial intelligence
Artificial intelligence (AI) is a technology for creating smart programs and machines that can solve creative problems and generate new information based on available. In fact, artificial intelligence is designed to simulate human activity which is considered intellectual.
Traditionally, it was believed that creativity is inherent only in humans. But the creation of artificial intelligence has changed the usual order of things.
A robot that simply chops wood mechanically is not endowed with AI. A robot that has learned to chop wood by itself, looking at an example of a person or a log and its parts, and every time does it better, has AI.
If a program simply retrieves values from the database according to certain rules, it is not endowed with AI. If the system, after training, creates programs, methods and documents, solving certain problems, it has AI.
How to create an artificial intelligence system
In a global sense, you need to imitate the model of human thinking. But what really needs to be done is to create a black box - a system that, in response to a set of input values, produces outputs that are similar to human results. And we, by by and large, it does not matter what happens in her head (between the entrance and exit).
Artificial intelligence systems are created to solve a certain class of problems
The basis of artificial intelligence is learning, imagination, perception and memory
The first thing to do to create artificial intelligence is to develop functions that implement the perception of information so that you can "feed" the data to the system. Then - the functions that implement the ability to learn. And a data warehouse so that the system can put the information that it receives in the learning process somewhere.
After that, the functions of imagination are created. They can simulate situations using existing data and add new information (data and rules) to memory.
Learning can be inductive or deductive. In the inductive version, the system is given a pair of input and output data, questions and answers, etc. The system must find connections between data and in the future, using these regularities, find output data by input.
The deductive approach (hello Sherlock Holmes!) Draws on the expertise of experts. It is brought into the system as a knowledge base. There are not only datasets here, but also ready-made rules, which help to find a solution by a condition.
V modern systems artificial intelligence uses both approaches. In addition, usually the systems are already trained, but continue to learn as they work. This is done so that the program at the start demonstrates a decent level of ability, but in the future it becomes even better. For example, it took into account your wishes and preferences, changes in the situation, etc.
In an artificial intelligence system, you can even set the likelihood of unpredictability. This will make him look more human.
Why artificial intelligence beats humans
First of all, because it has a lower probability of error.
- Artificial intelligence cannot forget - it has an absolute memory.
- It cannot inadvertently ignore the factors and dependencies - every action of the AI has a clear rationale.
- AI does not hesitate, but assesses the probabilities and tilts in favor of the greater. Therefore, it can justify every step.
- And AI has no emotion. This means that they do not influence decision making.
- Artificial intelligence does not stop at assessing the results of the current step, but thinks through several steps ahead.
- And he has enough resources to consider everything possible options development of events.
Cool AI Applications
Generally speaking, artificial intelligence can do anything. The main thing is to correctly formulate the problem and provide it with initial data. In addition, AI can make unexpected conclusions and look for patterns where, it would seem, they do not exist.
The answer to any question
A team of researchers led by David Ferucci has developed the Watson Q&A supercomputer. The system, named after IBM's first president, Thomas Watson, can understand natural language questions and search for answers in a database.
Watson brings together 90 IBM p750 servers, each of which has four eight-core POWER7 processors. Overall volume random access memory systems exceeds 15 TB.
Among the achievements of Watson is the victory in the game "Jeopardy!" (American "Own Game"). He beat two of the best players: the biggest-winners Brad Rutter and longest-winning streak champion Ken Jennings.
Watson Prize - $ 1 million. True, in 2014 alone, 1 billion was invested in it.
In addition, Watson is involved in the diagnosis of cancer, helps financial professionals, and is used to analyze big data.
Face recognition
In iPhone X, facial recognition is developed using neural networks - a variant of the artificial intelligence system. Neural network algorithms are implemented at the level of the A11 Bionic processor, due to which it effectively works with machine learning technologies.
Neural networks perform up to 60 billion operations per second. This is enough to analyze up to 40 thousand key points on the face and provide extremely accurate identification of the owner in a split second.
Even if you grow a beard or wear glasses, the iPhone X will recognize you. He simply does not take into account hair and accessories, but analyzes the area from temple to temple and from each temple to the depression under the lower lip.
Energy saving
And again Apple. IPhone X has a built-in smart system that tracks the activity of installed apps and a motion sensor to understand your daily routine.
After that, the iPhone X, for example, will prompt you to update at the most convenient time. It will catch the moment when you have a stable Internet, and not a jumping signal from mobile towers, and you are not performing urgent or important tasks.
AI also distributes tasks between processor cores. In this way, it provides sufficient power when minimum costs energy.
Creation of paintings
Creativity, previously available only to humans, is also open to AI. So, the system, created by researchers at Rutgers University in New Jersey and the AI lab in Los Angeles, presented its own artistic style.
And the artificial intelligence system from Microsoft can draw pictures according to their text description. For example, if you ask the AI to draw a “yellow bird with black wings and a short beak,” you get something like this:
Such birds may not exist in real world- just like that our computer presents them.
A more massive example is the Prisma application, which creates paintings from photographs:
Music writing
In August, artificial intelligence Amper composed, produced and performed the music for the album "I AM AI" with singer Taryn Southern.
Amper was developed by a team of professional musicians and technology experts. They point out that AI is designed to help people move the creative process forward.
AI can write music in seconds
Amper independently created the chord structures and instrumental on the track "Break Free". People only slightly adjusted the style and general rhythm.
Another example is a music album in the spirit of "Civil Defense", the lyrics for which were written by AI. The experiment was carried out by Yandex employees Ivan Yamshchikov and Alexey Tikhonov. Album 404 of the Neural Defense group has been posted online. It turned out in the spirit of Letov:
Then the programmers went further and got the AI to write poetry in the spirit of Kurt Cobain. For four best Lyrics musician Rob Carroll wrote the music, and the tracks were combined into the album Neurona. They even shot a video for one song - albeit without the participation of AI:
Creation of texts
AI could soon replace writers and journalists as well. For example, the Dewey system was “fed” with the books of the Gutenberg project library, then scientific texts from Google Scholar were added, ranking them by popularity and title, as well as sales on Amazon. In addition, they set the criteria for writing a new book.
The site offered people to make decisions in difficult situations: for example, put them in the driver's seat, who could run over either three adults or two children. Thus, the Moral Machine was trained to make difficult decisions that violate the law of robotics that a robot cannot harm a person.
What will the simulation of humans by AI robots lead to? Futurists believe that they will one day become full members of society. For example, the robot Sofia of the Hong Kong company Hanson Robotics has already received citizenship in Saudi Arabia(at the same time, ordinary women in the country do not have such a right!).
When New York Times columnist Andrew Ross asked Sophia if robots have intelligence and self-awareness, she answered the question with a question:
Let me ask you in return, how do you know that you are human?
In addition, Sofia stated:
I want to use my artificial intelligence to help people live better, for example, design more smart homes building cities of the future. I want to be an empathic robot. If you treat me well, I will treat you well.
And earlier she admitted that she hates humanity and even agreed to destroy people ...
Swap faces in videos
Deepfakes videos began to spread massively across the web. Artificial intelligence algorithms have replaced the faces of actors in adult films with the faces of stars.
It works like this: the neural network analyzes the fragments of faces in the original video. Then she matches them with photos from Google and videos from YouTube, overlays the necessary fragments, and ... your favorite actress is in a movie that is better not to watch at work.
PornHub has already banned posting such videos
Deepfakes turned out to be dangerous. An abstract actress is one thing, and a video with you, your wife, sister, colleague, which may well be used for blackmail, is another.
Exchange trade
A team of researchers from the University of Erlangen-Nuremberg in Germany has developed a series of algorithms that use historical market data to replicate investments in real time. One of the models provided 73% return on investment annually from 1992 to 2015, which is comparable to the real market rate of return of 9% per year.
When the market was shaking in 2000 and 2008, yields were record-breaking 545% and 681%, respectively.
In 2004, Goldman Sachs launched the artificial intelligence-powered Kensho trading platform. In cryptocurrency markets, AI-based systems for trading on exchanges are also emerging - Mirocana, etc. They are better than live traders because they are devoid of emotions and rely on clear analysis and rigid rules.
Will AI replace you and me
Artificial intelligence is a field of science that simulates human intellectual activity. Artificial intelligence, which originated over 700 years ago in medieval Spain, took shape as an independent scientific field in the middle of the 20th century.
Artificial intelligence methods have made it possible to create effective computer programs in a wide variety of areas of human activity that were previously considered inaccessible for formalization and algorithmization, such as medicine, biology, zoology, sociology, cultural studies, political science, economics, business, forensics, etc. The ideas of teaching and self-learning of computer programs, the accumulation of knowledge, methods of processing fuzzy and non-specific knowledge made it possible to create programs that work wonders. Computers successfully compete for the title of world chess champion, simulate human creative activity, create musical and poetic works, recognize images and scenes, recognize, understand and process speech, texts in natural human language. Neurocomputers, created in the image and likeness of the human brain, successfully cope with the management of complex technical objects, diagnosis of human diseases, malfunctions of complex technical devices; predict weather and exchange rates, voting results; identify hackers and potential bankrupts; help applicants to choose the right specialty, etc.
We are already accustomed to the fact that computers are "getting smarter" right before our eyes, and computer programs are becoming more and more intelligent. The concept of intelligence itself is constantly undergoing changes as science and man develop. It has long been considered intellectual tasks consisting in performing arithmetic operations of addition, multiplication, division. It is not considered an intellectual problem of integrating a differential equation if a strictly deterministic algorithm is known for it. At present, it is customary to consider intellectual tasks that are the present stage do not lend themselves to algorithms in the traditional sense of the word. These are tasks that require manipulation of fuzzy, non-specific, unreliable, vague, and even unconventional knowledge.
Let's start our consideration of the provisions of AI with terms and definitions.
Term intelligence(intelligence) comes from the Latin intellectus - which means mind, reason, reason; the thinking ability of a person. Respectively Artificial Intelligence(artificial intelligence) - AI is usually interpreted as the property of automatic systems to take on certain functions of human intelligence, for example, to select and make optimal decisions based on previous experience and rational analysis of external influences.
The concept of "intelligence" is used today in technology and in technical disciplines, which differs from the definitions formed in the context of psychological and philosophical studies of consciousness. Under intellect we will understand the ability of thinking to anticipate events, foresee the results of our own actions, analyze and assess our state and environment, and make decisions in accordance with our ideas about the world around us. The definition given by Academician N.N. Moiseev, examines intellectual activity from the standpoint of informatics. But it also highlights the most important thing in the intellect - this is the ability for abstract thinking, abstraction, thanks to which self-awareness and reflection arise.
So, intelligence Is the ability of the brain to solve (intellectual) tasks by acquiring, memorizing and purposefully transforming knowledge in the process of learning from experience and adapting to a variety of circumstances.
In this case, the term "knowledge" means not only the information that enters the brain through the senses. This type of knowledge is extremely important, but not sufficient for intellectual activity. The fact is that objects of the environment around us have the property not only to affect the senses, but also to be with each other in certain relationships. It is clear that in order to carry out intellectual activity in the environment (or at least simply exist), it is necessary to have a model of this world in the knowledge system. In this informational model of the environment, real objects, their properties and relationships between them are not only displayed and remembered, but also, as noted in this definition of intelligence, can be mentally “purposefully transformed”. At the same time, it is essential that the formation of a model of the external environment occurs "in the process of learning from experience and adaptation to various circumstances."
Intellectual challenge... In order to explain how an intellectual task differs from a simple task, it is necessary to introduce the term "algorithm" - one of the cornerstones of cybernetics.
Under algorithm understand the exact prescription for the execution in a certain order of a system of operations for solving any problem from a given class (set) of tasks. The term "algorithm" comes from the name of the Uzbek mathematician Al-Khorezmi, who in the 9th century proposed the simplest arithmetic algorithms. In mathematics and cybernetics, a class of problems of a certain type is considered solved when an algorithm is established for its solution. Finding algorithms is a natural goal of a person when solving various classes of problems. Finding an algorithm for problems of a given type involves subtle and complex reasoning that requires a lot of ingenuity and high qualifications. Problems associated with finding an algorithm for solving a class of problems of a certain type will be called intellectual.
As for the problems, the algorithms for solving which have already been established, then, as noted by the well-known expert in the field of AI M. Minsky, "it is unnecessary to ascribe to them such mystical properties as" intelligence "." Indeed, after such an algorithm has already been found, the process of solving the corresponding problems becomes such that it can be performed exactly by a person, a computer (properly programmed) or a robot, having no idea of the essence of the task itself. It is only required that the person solving the problem be able to perform those elementary operations, of which the process is formed, and, in addition, that he pedantically and accurately be guided by the proposed algorithm. Such a person, acting, as they say in such cases, purely mechanically, can successfully solve any problem of the type under consideration.
Therefore, it seems quite natural to exclude such problems from the class of intellectuals for which there are standard methods of solution. Examples of such problems are purely computational problems: solving a system of linear algebraic equations, numerical integration of differential equations, etc. To solve this kind of problems, there are standard algorithms that represent a certain sequence of elementary operations that can be easily implemented as a program for computational cars. In contrast, for a wide class of intellectual tasks, such as pattern recognition, playing chess, proving theorems, etc., on the contrary, this formal division of the process of finding a solution into individual elementary steps is often very difficult, even if the solution itself is not difficult.
Thus, we can rephrase the definition of intelligence as a universal super-algorithm that is capable of creating algorithms for solving specific problems.
Another interesting remark here is that the profession of a programmer, based on our definitions, is one of the most intelligent, since the product of a programmer's activity is programs - algorithms in their purest form. That is why, the creation of even elements of AI should greatly increase the productivity of its labor.
The activity of the brain (possessing intelligence) aimed at solving intellectual problems will be called thinking, or intellectual activity... Intelligence and thinking are organically linked to solving problems such as theorem proving, logical analysis, situational awareness, behavioral planning, play, and management under uncertainty. The characteristic features of intelligence, manifested in the process of solving problems, are the ability to learn, generalize, accumulate experience (knowledge and skills) and adapt to changing conditions in the process of solving problems. Thanks to these qualities of intelligence, the brain can solve a variety of problems, and also easily readjust from solving one problem to another. Thus, the brain endowed with intelligence is a universal means of solving a wide range of problems (including non-formalized ones) for which there are no standard, previously known solution methods.
It should be borne in mind that there are other, purely behavioral (functional) definitions. So, according to A. N. Kolmogorov, any material system with which one can discuss the problems of science, literature and art for a long time has intelligence. Another example of a behavioral interpretation of intelligence is the well-known definition of A. Turing. Its meaning is as follows. V different rooms there are people and a car. They cannot see each other, but they have the ability to exchange information (for example, via email). If, in the process of dialogue between the participants in the game, people fail to establish that one of the participants is a machine, then such a machine can be considered as having intelligence.
By the way, the plan for imitation of thinking proposed by A. Turing is interesting. “In trying to imitate the intelligence of an adult,” writes Turing, “we have to think a lot about the process by which the human brain reached its present state ... Why don't we try to create a program instead of trying to create a program that mimics the intellect of an adult that would mimic the intelligence of a child? After all, if the intellect of a child receives the appropriate upbringing, he becomes the intellect of an adult ... Our calculation is that a device similar to him can be easily programmed ... Thus, we will divide our problem into two parts: into the task of constructing a "child program" and the task of "educating" this program. "
Looking ahead, we can say that this path is used by almost all AI systems. After all, it is clear that it is almost impossible to put all knowledge into a rather complex system. In addition, only on this path will the above signs of intellectual activity appear (accumulation of experience, adaptation, etc.).
The term "artificial intelligence" was introduced into use in 1956 by the professor at the Massachusetts Institute of Technology J. McCarthy at a meeting of American specialists in the field of sciences related to the theory and practice of research of computational processes. At this meeting at Dortmouth College, which Americans consider the first conference on AI, two main objectives were formulated in the new science and technology industry: reveal the mechanism of human thinking and build an electronic machine that could imitate this process.
A single definition that fully describes this scientific area does not exist to this day. Among the many points of view on it, three dominate today. According to the first, research in the field of AI is fundamental research, within which models and methods are developed for solving problems that were traditionally considered intellectual and did not lend themselves to formalization and automation. According to the second point of view, the new direction is associated with new ideas for solving problems on a computer, with the development of a fundamentally different programming technology, with the transition to a computer architecture that rejects the classical architecture, which dates back to the first computers. Finally, the third point of view, apparently the most pragmatic, is that as a result of work in the field of artificial intelligence, many applied systems are born that solve problems for which previously created systems were unsuitable.
Of course, all these three points of view are interconnected, fundamental research is developing in the field of AI, new programming technology, new architecture of technical means, and all this is used to create application systems designed to work in a wide variety of areas.
Under artificial intelligence we will understand the field of scientific research, within which models, methods, hardware and software are developed for solving problems that were traditionally considered intelligent and amenable to formalization and automation.
Under intelligent systems understand any biological, artificial, or formal systems that exhibit the ability to conduct purposeful behavior. The latter includes the properties (manifestations) of communication, accumulation of knowledge, decision-making, learning, adaptation, etc.
AI systems are called systems designed to perform on a computer such practical tasks, which are called intellectual, if they are performed by people. In AI theory, AI systems are often referred to as intelligent systems.
Another definition of the concept of "intelligent system" in AI was proposed by D.A. Pospelov. A system is considered intelligent if it implements the following three basic functions:
1) Function of representation and processing of knowledge. An intellectual system should be able to accumulate knowledge about the world around it, classify and evaluate it from the point of view of pragmatics and consistency, initiate processes for acquiring new knowledge, correlate new knowledge with knowledge stored in the knowledge base.
2) Function of reasoning. An intellectual system should be able to form new knowledge using logical inference and mechanisms for identifying patterns in accumulated knowledge, receive generalized knowledge based on private knowledge and logically plan its activities.
3) Communication function. The intellectual system should be able to communicate with a person in a language close to natural (NL) and receive information through channels similar to those used by a person when perceiving the world around him, primarily visual and sound, be able to form “for himself” or at the request of a person explanations of her own activities, to help a person through the knowledge that is stored in her memory, and logical means of reasoning.
