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.

Keywords

• Intelligenza Artificiale
• machine learning
• deep learning
• computer vision
• mapping
• immagini satellitari