Have you ever thought about how influential artificial intelligence has become in recent years? We have, and our expert in modern technologies, Yevhen Kasyanenko, has already expressed his opinion on this topic:
“Artificial intelligence is an integral part of business, science, everyday life, and education, surrounding us every day. The competent implementation of innovation can lead to positive changes in every industry.”.
We would like to add that the development of machine technology has indeed come a long way, but many people are still unaware of the circumstances and research that led to the development of AI in the first place.
Our KISS Software team, led by Yevhen Kasyanenko, has prepared material for you that will help you understand all the stages of the history of the creation and development of artificial intelligence, as well as the effectiveness of its implementation in our lives.
In the 20th century, the first mechanical experiments began in conjunction with philosophical concepts, which created the first AI models.
“In essence, machine intelligence is nothing more than algorithms that mimic human thinking,” explains our expert.
From the middle of the century, scientists focused on “packaging” all the knowledge and experience known to humans into a single system. This is how the development of AI began.
Can machines think like humans? This was the main question that preoccupied every scientist in the 1930s.
British cryptographer and computer scientist Alan Turing developed a test to determine how possible this was. He wanted to answer this question with an experiment that would show whether computer algorithms were capable of imitating the thought process. His test consisted of simulating a dialogue between a human, a machine, and another human. During the correspondence, the tester had to decide whether he was communicating with a human or a machine. The persuasiveness of the tester’s answer indicated the ability of artificial intelligence to imitate humans.
In parallel with Turing’s research, mathematicians were actively working on cybernetic contributions. It was the development of Norbert Wiener’s systems that made an important contribution to AI models that are capable not only of imitating, but also of adapting, updating, and learning.
The Dartmouth Conference, held in 1956, is considered the official start of AI. It was there that the term “artificial intelligence” was first used.
After the presentation organized by John McCarthy, which showed experiments with machine “intelligence,” new developments began to actively develop. Innovations became significant not only in computational models, but also in learning and solving complex logical problems.
“Please note that there is a BASE in AI development that is unchanging. It is the foundation that sets the direction for development. It also works in any other system. A qualitatively laid foundation will bring more results. This is the rule I use when working with my KISS Software team for our clients,” – Yevhen Kasyanenko emphasizes.
Since the 1960s, the history of artificial intelligence has gained momentum. AI began to be actively studied at universities and government organizations. This period became crucial for the future development of the modern generation of neural networks.
Algorithms were improved, and keys were found that allowed computers not only to receive information but also to analyze it. In addition to automating complex mathematical calculation processes, machines were able to select and make logical decisions. AI was tested in medicine, engineering, finance…
The biggest problem and reason for the stagnation in the development of AI technology were:
The development of AI became a complete disappointment for people when they encountered a multitude of problems. Excessive expectations were not met due to the inability to create machines with complex thinking. Limited capabilities prevented scientists from realizing their most ambitious ideas.
Funding from investors declined in the 1960s, and for this reason, “winter came for AI.” Projects were frozen, interest declined significantly, and research was reduced.
By the 1990s, interest in the history of artificial intelligence was gaining momentum again, as technical inventions gradually improved. Powerful computer processors made it possible to conduct experiments with machine learning. One of the major achievements in 1997 was the creation of IBM Deep Blue. This supercomputer defeated chess champion Garry Kasparov. This success showed scientists that AI is capable of flexibly adapting to algorithms, predicting actions, and analyzing processes.
“The human brain is not capable of retaining and analyzing as much information as can be stored in a computer database. It is the unique features and prospects of using AI for the analysis of medicine, finance, and business that have become fundamental to modern neural networks. But every system needs training and modeling…,” notes Yevhen Kasyanenko.
It was at the beginning of the 21st century that artificial intelligence gained access to information. Data was systematically uploaded to computers via the Internet and could be easily transferred to various devices. This made it much easier to train AI based on human experience.
In 2010, modeling was actively developed, and complex patterns for analysis and algorithms were implemented. AI began to recognize speech, translate languages, correspond with humans, recognize faces, and generate creative ideas.
Deep learning scaled many projects and opened up access to modern approaches in engineering, finance, and medicine. This became a new milestone in the history of the creation and development of artificial intelligence.
“AlphaGo from DeepMind is a striking example of how a ‘machine’ can surpass humans in strategic thinking and logic,” our expert emphasized.
By 2020, AI had become part of the digital world, with chatbots, Siri, chatGPT, and various voice assistants actively entering everyday life. A multitude of coded functions made it possible to automate routine tasks.
In business, AI has become a tool for personalization, forecasting, and decision-making. Machine intelligence algorithms have enabled companies to reduce costs and significantly increase the efficiency of routine tasks.
Artificial intelligence is now allowed to control unmanned systems, automotive traffic, and video surveillance. Digital “vision” is capable of executing commands based on the visible field. AI analyzes the environment and is capable of finding risks both within systems and threats from outside.
“Humanity has not created something ‘above itself’; it has optimized knowledge in such a way as to facilitate its existence. Intelligent systems are largely capable of mastering many processes to simplify life and business development,”shares his thoughts Yevhen Kasyanenko.
Technology is developing at a rapid pace in an era when everything can be found on the Internet. People have access to only a small part of the technology where they interact with AI. Against this backdrop, conditional “challenges” to the system arise steadily through ethical, social, and technological processes.
The main goal of AI development is to combine general intelligence that can be adapted and trained. After that, the development of superintelligence would have the potential to diagnose diseases, prevent financial fraud, and control unmanned systems more accurately, correctly, and with analytics.
Regulating all processes is complicated by the fact that algorithms are becoming complex and must be controlled using increasingly powerful computers. This factor may force people to learn new professions in order to prevent the labor market from collapsing. In addition, information on the network is becoming vulnerable to cyberattacks.
“In the future, special attention must be paid to managing the development of AI so that technologies keep pace with systems and algorithms. After all, major risks can become a problem at the stage of missing ‘details’, as was the case before the first winter for artificial intelligence,” comments Yevhen Kasyanenko.
The history of artificial intelligence has gone through many ups and downs. It began with philosophical speculation and only over time was it realized in modern neural network technologies. Today, AI developments improve our daily lives and open up many avenues for business growth and experimentation in science, medicine, and engineering.
Nowadays, AI is no longer just hype, but a tool that really works. For it to benefit your business, it is important not just to “install a neural network,” but to competently integrate it into your processes. This is exactly what KISS Software, led by Yevhen Kasyanenko, helps with. We create smart solutions based on artificial intelligence that automate routine tasks, increase efficiency, and help launch truly innovative products.
Want AI to work for your business, not just sound good in a presentation? Write to KISS, and together we will create technologies that don’t look like the future. They are the future, where artificial intelligence is your reliable assistant.
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