Volare alto con l'Intelligenza Artificiale

Abstract

JOHN MCCARTHY, computer scientist at Stanford University, first
coined the term "artificial intelligence” in 1955, defining it as, "the science and engineering of making intelligent machines, especially intelligent computer programs.”
Machines are intelligent when they can replicate human cognitive skills such as forming categories, recognizing patterns, and solving problems. For machines to achieve artificial intelligence, computer programmers must create algorithms that can scan and organize input data to train and teach the machines to perform tasks. This method is called machine learning, the most basic of all AI techniques. Several other AI methods have since been developed, including neural network, a process that mimics how the human brain learns by using interconnected nodes to process data. Its more
sophisticated version is called deep learning, which uses multiple layers
of neural networks so that computers can analyze bigger datasets. With
the advent of big geospatial data, there are far more inputs for AI machines to train on and improve their accuracy. And due to AI's ability to handle big
datasets such as imagery, computer vision is currently one of the hottest
geospatial applications. With computer vision technology, machines
can be taught to "see” real-world objects from images, thus allowing
companies like Mapillary to identify roads from street photos, Ecopia to
extract built-up areas from satellite imagery, and VOXELGRID
to recognize construction materials from a point cloud.