Updated: Oct 21, 2019
Artificial intelligence is derived from information technology. It is often used interchangeably with the concepts of automation or robotization. It is also mistaken for machine learning or the use of algorithms. According to the dictionary, A.I. is "the theory and development of computer systems capable of performing tasks requiring human intelligence, such as visual perception, speech recognition, decision making and translation between languages. The word ‘intelligence’ is defined as the ability to understand, learn, and use knowledge and skills in new situations. The roles and tasks of AI are to process and recognize the data acquired and then to perform specific tasks.
3 Technologies of Artificial Intelligence
Today's AI potential and the implementation of tasks is possible thanks to the development of 3 technologies: machine learning, deep learning, & natural language processing.
Machine learning (M.L.) has taken AI to a higher level above the implementation of pre-assigned rules. Thus, the ML changed the role of the algorithms that have been used so far in the framework of AI. ML enables computers to learn from their data by creating links between them. Thanks to these possibilities, ML allows to draw conclusions and create generalizations based on the analysis. ML is based on a network of artificial neurons, which reflects the human nerve cell system, groups data on several layers: entry level, hidden levels and exit layers. The neuron network uses so-called learning algorithms, which by processing the input data themselves learn the rules and relationships between them, and based on correlation analyzes look for optimal solutions. ML comes in many forms and can be represented as: pattern recognition, statistical modeling, data mining, knowledge discovery, predictive analytics, data analytics, adaptive systems, self-organizing systems and many more.
Deep learning (DL) is a higher level of ML. It is based on learning algorithms that do not require manual management. DL using sets of available data (Big Data) and computing power of computers (server farms, processor power, computing in the cloud), allows almost immediately decoding and providing the result for new emerging information.
Natural language processing (NLP) is one of the applications of ML and DL, which aims to recognize speech. Many years of research in this area have enabled us to work with large data sets (text samples) that provide context, lexical, syntactic and semantic meanings.
These three technologies - ML, DL and NLP, enabled the development of AI tools in the area of voice, text, image recognition, decision-making and autonomous robots and vehicles. They become everyday life, finding application in even medicine, law, motorization and education.