MACHINE LEARNING & IA
We teach a machine how to perform a certain action even if this action has never been programmed among the possible actions
By "artificial intelligence" we mean the ability of a hardware and software system to solve a problem just as if it were a human being, that is, using certain characteristics that are typically considered human such as, for example, visual, space-time and decision-making perceptions.
So not only calculation skills, but of all those different forms of intelligence that are recognized by Gardner's theory, and ranging from spatial to social intelligence, from kinesthetic to introspective.
Artificial intelligence, or AI, is already used in many fields and applications of daily life, from queue management to fast food, to weather models, from customer service management of contact centers to advanced traffic control tools, etc.
Thanks to neural networks, which by simulating the functioning of our brain are now able to solve problems by identifying solutions that are often inaccessible to the human mind, the "intelligent system" can learn from errors and then evolve to adapt and respond to more and more cases. This is the meaning of machine learning, which allows and will allow to entrust AI with more and more tasks, especially to be able to operate in contexts for which programmers cannot foresee all the development possibilities a priori.
Through machine learning, therefore, a machine is able to learn how to perform a certain action even if this action has never been programmed among the possible actions.
ByteInt and the artificial intelligence
ByteInt is at the forefront of the development of artificial intelligence systems, with the aim of improving the performance of companies and organizations by supporting them in identifying new assets and improving processes.