7.12. ARTIFICIAL INTELLIGENCE - (AI)

It is in human nature to read books (perhaps through school reading material), newspapers and magazines with stories, and enjoy watching events on the movie screen. I doubt that every grown man has not read a book or watched a movie on the subject of science fiction in his life. I also doubt that he did not dream something that does not belong to reality - some brain fantasy. Regarding fantasizing, two writers of stories and novels should be especially highlighted because even silent films were made based on their works. Further a little about them, because they deserved it.

The writer Jules Gabriel Verne, known for his science fiction novels, published a novel in 1865 about an astronaut's journey to the moon using a cannon as a launch pad. He is considered one of the pioneers of science fiction and his imagination influenced many later authors. But closer to today's events were the novels published by the writer Isaac Asimov. He wrote in a variety of fields, but is best known for his work in the science fiction genre. His most famous works include the 'Foundation' series of novels, the 'Robot' series and the 'Galactic Empire' series. Isaac Asimov formulated the 'Three Laws of Robotics' in his science fiction story 'Runaround' published in 1942. These laws became a key element of Asimov's robot universe and are known among science fiction fans around the world. Here's how they're usually worded:

1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.
2. A robot must obey the orders given to it by human beings, except where such orders would conflict with the First Law.
3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

Figure 7.12.1. Title page of one of Isaac Asimov's novels.

These laws were designed to provide ethical guidelines for robot behavior, and were often used in Asimov's stories to explore the dynamics of human-robot interaction. It is important to note that these laws only apply to a fictional world and that they themselves have opened up many ethical questions and dilemmas.

Not only the writers of stories and novels were engaged in science fiction. Painters have also created many paintings, but it is precisely on this topic of robots with a shell shape that the author of these pages likes the works of the painter Hajime Sorayama, a Japanese artist known for his work in the genre of futuristic realism. Sorayama is best known for his paintings and illustrations depicting robotic and cyborg figures, often in provocative and sensual poses. His works are characterized by exceptional detail and great technique, and he often uses a combination of traditional media and digital technology. Sorayama's work is widely popular and influential, and his works are exhibited in galleries around the world.

Figure 7.12.2. Some of the works of the painter Hajima Sorayama.

From the looks of the pictures, the author prefers the robot as envisioned by Sorayama, rather than the robot shown on the title page of Asim's book. So punch cards didn't even exist yet, and painters, especially writers of science fiction novels, were dealing with artificial intelligence. But the real first appearances of artificial intelligence (AI) go back to the history of computer science. Here are some key time periods that matter:

Year 1956: The Dartmouth Conference and the 'birth' of the term 'artificial intelligence'. At this conference, organized by John McCarthy, Marvin Minsky, Nathaniel Rochester and Claude Shannon, the term 'artificial intelligence' was used publicly for the first time.
1950s and 1960s: A logical and symbolic approach. During this period, researchers focused on logical and symbolic methods for programming computers to simulate human intelligence. An example is 'Logic Theorist', a software developed by Allen Newell to prove mathematical theorems.
1980s and 1990s: Experimental systems. During this period, researchers developed systems to solve limited problems, such as the medical condition diagnosis system MYCIN (developed at Stanford University) or the chess playing system Deep Blue (developed by IBM).
2000s and beyond: Machine learning and deep learning. The development of increasingly powerful computing resources and large amounts of data has enabled progress in the field of AI. Machine learning and deep learning have become the main methods for training computer systems to do tasks such as image recognition, natural language processing, autonomous driving and other complex tasks.

These are just a few of the many events that have shaped the development of artificial intelligence over the years. Progress in this area continues to accelerate, and AI is increasingly entering our everyday lives.

Terminator Artificial Intelligence (AI) is a branch of computer science that deals with the development of computer systems capable of performing tasks that require human intelligence. AI is based on algorithms and models that enable computers to learn from data, recognize patterns, make decisions and solve problems much like humans. An algorithm is a mathematical procedure that enables computers to perform various tasks and is designed to enable a computer to learn, understand and reason. Models perform various tasks, such as recognizing shapes, understanding language, making decisions, predicting or generating content, and the like. The application of UI covers areas such as computer vision, natural language, robotic automation, autonomous vehicles and others. UI has the potential to transform many industries and improve our daily lives. The above should not cause alarm, we are still far from 'Terminator'. Or are we not? Maybe the 'Matrix' awaits us in the future or are we already in the matrix? Or have we as humans polluted the planet Earth, with or without the application of any intelligence, and we are awaiting relocation to another planet? And maybe there will be a new 'Arka'? But let's go back to today. For a long time in this millennium, 'robots' have been doing jobs instead of man, in a better and more accurate way than him, and how they will work depends on the program support that controls their 'arms' according to an algorithm designed by man and which cannot be changed by robots.

Today is not the era that was at the time of the founding of the 'Ford' factory (or any other). Now on the conveyor belt, a 'robot arm' in the form of a flexible tube, which can be pulled anywhere, on the end of which is a mechanism for electric arc welding, welds the car bodywork more precisely and accurately than a human. The human is there to monitor the robot in terms of whether its position sensor or electrode wear has gone wrong. If it is, it will perform a 'repair' and forward a report on the lack of robot operation, which will be corrected by someone in charge. That robot doesn't even look like a human. It is similar with the painting of the vehicle bodywork; the computer will record the best work of the human, and repeat it as many questions as the human is satisfied with the result. A human's activity can be, for example, monitoring the dirtiness of the injector, about which the robot should inform him based on the readings of its sensors. If the injector becomes dirty and the sensor does not respond, the human will intervene. There are many examples similar to those described.

The above does not mean only the progress of software design for robots, but also the progress of all actuators, sensors and other electronic mechanisms that the robot uses. And a 3D printer is a kind of robot connected to a computer. Human-shaped robots are mainly 'advertising constructions', but based on their appearance and way of walking, comparing robots made in different time periods, it is possible to see how much electronic devices of various types have advanced in their functionality in order to improve the effect of work and behavior humanoid robot. Can a robot sweep the trash in the apartment? It can, but the 'broom' looks like the next Figure.

Figure*** 7.12.3. Floor cleaning robot. ( + / - )

The 'broom' shown will not get stuck due to the sensors in the 'whiskers', but it certainly cannot clean the corners of the room. True, there is less walking there, but that means that the occasional human has to do it himself. Some of these brooms know how to find their own place to charge the batteries with energy, and some do not. Some can unload the collected garbage into the container to the charger and some cannot. Despite a lot of help in the household, some things remain up to the man to do, such as cleaning the tank. The popular proverb says: 'How much money - so much music'. This robotic cleaner is just one example of household appliances available today. And even if they have WI-FI to let you know what's up with robot on a mobile - great!

None of the mentioned 'robotic devices' have the ability to learn independently and are not part of the UI. And where is the UI that is rapidly developing in the third decade of this millennium? Somewhere on a powerful server using a powerful data center, in one or more buildings connected by a fast communication infrastructure. Untouchable, impalpable and has no form like a man. At the end of this introduction to this chapter, I will citing a paragraph from one of the introductory pages of this e-book.

.... When scientists finally after making PC turn its power, the computer is running. They put him a question - ''Is there a God?'. After a few seconds of silence, suddenly melted switch to turn on the computer and its power is redirected to the computer only known source and the subsequent response - 'Now there is!'.

SUMMARY:

There are two essential prerequisites in order to realize a computer system capable of independent learning.

1.) Miniaturization of the elementary transistor element. Today, a multitude of processor cores can be integrated on one small silicon chip, which will process the available database at enormous speed, which was unimaginable at the time of ENIAC. In addition, accompanying devices, such as actuators, are smaller and more efficient.
2.) The creation of an algorithm by a human, which enables the software based on that algorithm to independently supplement it as well as supplement the initial database.

The text on this page was generated by the computer system 'ChatGPT', version of GPT-4, based on individual queries of the author. GPT stands for 'Generative Pre-trained Transformer', which is the name for the deep learning architecture used in its implementation. ChatGPT has been in public use since October 2020. The company 'OpenAI' then publicly presented the GPT-3 version, to provide access to users worldwide. It is available for use in various applications and platforms. It is a product of the development team at OpenAI. The exact number of people on that team is not known to the public, but OpenAI brings together multiple experts from different fields, including researchers, engineers, scientists and designers. These experts work together to improve and develop AI models like this one.

But there is competition. There are other language models and virtual assistants developed by other companies on the market. Some of the better known alternatives are Google's BERT, Microsoft's Transformer, Amazon's Alexa and IBM Watson. Each of these models has its own specifics and applications, so users can choose the one that best suits their needs.