There is no single definition of artificial intelligence (AI). As a rule, AI is considered as a field of computer science, focused on the development of hardware and systems capable of performing tasks that are commonly associated with the human mind. or AI technologies are just tools that are tailored to solve specific (albeit very complex) problems.
It is a branch of AI that studies ways of increasing computer efficiency through their learned experience.
Deep learning is a separate class of machine learning algorithms that uses multiple layers to train neural networks. Deep learning has become very popular in recent years and has led to significant progress in solving problems such as speech and visual objects recognition.
People will always have something to think about.
One of the striking results in recent years is the realization of the fact that AI models can now be used for a very wide range of tasks that 20 years ago were believed to be unsolvable for computers, because the ability to solve them were attributed to higher nervous activity. For example, the AI now has the ability to draw pictures, keep up a conversation, drive a car, and much more. AI is already widely used in systems for recognizing printed and handwritten texts, speech recognition and synthesis, Internet search, and recommendation systems. One of the most notable latest achievements is the solution of the protein tertiary structure prediction problem, which was one of the most complex and important problems in biology and which was solved by DeepMind specialists in the fall of 2020.
It would be no exaggeration, if we say that the widespread introduction of AI technologies will entail major changes in lifestyle and living standards of people. Similar dramatic changes occurred with the widespread introduction of the steam engine, the development of the electric power industry and the spread of automobiles. The humanity will shift from mass production of identical goods and services to more personalized services, and many branches of the economy, which are currently impossible to imagine without human workforce will be fully or partially automated. Within a couple of decades, the jobs such as a call center operator, a driver, a simultaneous interpreter, an airplane pilot and many others will become obsolete. Most people will have virtual or robotic personal assistants who will help them in the household, monitor their health and plan their leisure time. Of course, some of the current professions will die out, but there is no need to be afraid of this. The humanity has repeatedly passed through periods of technological transformations. Other jobs in which people will be able to fulfil themselves better will replace the dying professions, for instance e-Sports, streaming, video blogging, etc.
The range of tasks in which machines are making noticeable progress is much wider than a few years ago. It includes playing board games including cards, answering simple questions, extracting facts from newspaper articles, assembling complex objects, translating text from one language to another, speech recognition, recognition of various objects depicted in images and driving cars in most common traffic situations. There are also many less obvious tasks performed by AI systems now, including detecting fraudulent credit card transactions, evaluating loan applications and bidding in complex electronic auctions. Simple forms of AI in fact perform many search engine functions.
Some studies such as Frey and Osborne (2013), suggest that automation may affect up to half of the jobs in the United States in the near future. Others, such as Brynjolfsson and McAfee (2011), indicate that the process has already begun: the slow return to full employment after the 2008 recession, as well as the discrepancy between increased productivity and stagnant wages, are the consequences of increased automation in professions that involve routine operations. Given that the progress of AI and robotics continues, it seems inevitable that most professions will be affected. This does not necessarily mean mass unemployment, however it may lead to a big shift in the structure of the economy and require new ideas on how to organize work and payment.