Python Data Analytics with Pandas, NumPy and Matplotlib – Fabio Nelli

The term artificial intelligence was first used by John McCarthy in 1956, at a time full of great hopes and enthusiasm for the technology world. They were at the dawn of electronics and computers as large as whole rooms that could do a few simple calculations, but they did so efficiently and quickly compared to humans that they already glimpsed possible future developments of electronic intelligence. But without going into the world of science fiction, the current definition best suited to artificial intelligence, often referred to as AI, could be summarized briefly with the following sentence: Automatic processing on a computer capable of performing operations that would seem to be exclusively relevant to human intelligence. Hence the concept of artificial intelligence is a variable concept that varies with the progress of the machines themselves and with the concept of “exclusive human relevance”. While in the 60s and 70s we saw artificial intelligence as the ability of computers to perform calculations and find mathematical solutions of complex problems “of exclusive relevance of great scientists,” in the 80s and 90s it matured in the ability to assess risks, resources, and making decisions. In the year 2000, with the continuous growth of computer computing potential, the possibility of these systems to learn with machine learning was added to the definition. Finally, in the last few years, the concept of artificial intelligence has focused on visual and auditory recognition operations, which until recently were thought of as “exclusive human relevance”. These operations include:

  • Image recognition
  • Object detection
  • Object segmentation
  • Language translation
  • Natural language understanding
  • Speech recognition

These are the problems still under study thanks to the deep learning techniques.