Artificial Intelligence (AI) allows computers to learn from their own experience, adapt to the parameters set and perform tasks that previously could only be performed by a human being. In most AI implementations – from computer chess players to unmanned cars – the ability to deeply learn and process the natural language is essential.
History of artificial intelligence development
The term “artificial intelligence” appeared in 1956, but AI technology has reached its true popularity only today against the background of increasing data volumes, improving algorithms, optimizing computing power and data storage facilities.
The first research in AI started in the 50s of the last century and was aimed at solving problems and developing symbolic computation systems. In the 60’s this direction attracted the interest of the U.S. Department of Defense: the U.S. military began to teach computers to simulate human thought activities.
These works became the basis for the principles of automation and formal logic of reasoning, which are used in modern computers, in particular, in systems to support decision-making and intelligent search engines designed to complement and enhance human capabilities.
Although AI is often portrayed in science-fiction films and novels as humanoid robots that take over the world, at this stage of technology development AI is not so scary and far from being as smart. On the contrary, the development of artificial intelligence allows these technologies to bring real benefit in all sectors of the economy.
What is the importance of artificial intelligence?
- AI automates repetitive learning and searching processes by using data. But AI differs from robotization, which is based on the use of hardware. The goal of AI is not to automate manual work, but to reliably and continuously perform numerous large-scale computerized tasks.
- AI makes existing products intellectual. As a rule, AI technology is not implemented as a separate application. AI functionality integrates into existing products, allowing them to be improved, just as Siri technology has been added to next-generation Apple devices. Automation, communication platforms, bots and smart computers, combined with large amounts of data, can improve the various technologies used in the home and office, from security data analysis systems to investment analysis tools.
- AI is adapted through progressive learning algorithms so that further programming can be data-driven. The AI reveals structures and patterns in the data that enable the algorithm to master a particular skill: the algorithm becomes a classifier or predictor. Thus, the same principle by which the algorithm learns the game of chess, he can learn to offer suitable products online.
- AI performs a deeper analysis of large volumes of data using neural networks with multiple hidden levels. A few years ago it was almost impossible to create a fraud detection system with five hidden levels. Everything changed with huge growth of computing power and appearance of “big data”. Deep learning models require a huge amount of data, because it is on this basis that they learn.
- Deep neural networks enable AI to achieve an unprecedented level of accuracy. In the field of healthcare, the diagnosis of cancerous tumors on MRI images using AI technologies (in-depth training, classification of images, recognition of objects) is as accurate as the conclusions of highly qualified radiologists.
- AI makes it possible to get the most out of the data. With the appearance of self-learning algorithms, the data themselves become the intellectual property object. The data contain the necessary answers – you just need to find them with the help of AI technologies. Because data are now more important than ever before, they can provide a competitive advantage.
How is artificial intelligence used?
AI functionality is in great demand in all industries, especially in question-and-answer systems that can be used in legal aid, patent search, risk communication and medical research.
Other applications of AI are described below:
AI technologies can be used in personalized medicine and in X-ray decoding. Personalized medical assistants can remind users to take medication, exercise or switch to a healthier diet.
AI helps to make purchases online with individually tailored recommendations, as well as allowing sellers to discuss purchases with customers. In addition, AI technology can optimize inventory management and product placement processes.
The AI can analyze IoT data from the production floor from the connected equipment and predict load and demand using recursive networks, a specific type of deep-learning network used for serial data handling.
Coaches receive reports with camera shots and sensor readings on how to better organize the game, including how to optimize the placement of players and strategy.
The principle of artificial intelligence
The AI’s principle of operation is to combine a large amount of data with fast, iterative processing capabilities and intelligent algorithms, allowing programs to automatically learn from the patterns and features contained in the data. AI is a complex discipline with many theories, techniques and technologies.
The goal of AI is to provide software products capable of analyzing input data and interpreting the results obtained. Artificial intelligence – means providing more intuitive process of interaction of the person with programs and the help at decision-making within the limits of certain tasks. AI is not a substitute for a person, and it will not become so in the foreseeable future.