The 'Nobel technology' award is awarded to AI-teaching software as human

This year, the ACM Computer Science Association awarded the Turing Prize to three scientists named "Godfather of Machine Learning" who laid the foundation for modern artificial intelligence.

The Turing Award, such as the Nobel Prize for computer science, is an annual award given to individuals or groups with important contributions to the Computer Science Association. The name of the prize is based on Mathison Turing, an English scientist and considered the father of computer science theory and artificial intelligence.

Three winners this year are Yann LeCun, a professor at New York University and Facebook's chief curator; Geoff Hinton, emeritus professor at the University of Toronto and senior Google researcher at Google Brain; Yoshua Bengio, professor at the University of Montreal and also the co-founder of the AI ​​company named Element AI.

The three scientists are collectively referred to as "machine learning gods (Deep Learning)" because they study the neural network, a type of software that teaches AI to function like the human brain.

Turing prize value is up to 1 million USD, divided equally for all 3 scientists. In addition, the winners also received Google's own awards, Turing Award sponsors.

The 'Nobel technology' award is awarded to AI-teaching software as human Picture 1
Yoshua Bengio, Yann LeCun and Geoff Hinton (turn left to right).

From the late 1970s and early 1980s, Hinton began working with neural networks. At that time, most computer scientists believed that this technique was a dead end. In 1983, he co-invented one of the first neural network devices to use statistical probabilities, Boltzmann. Currently, big technology companies like Facebook and Amazon all use this technology after it has been improved.

LeCun has made important contributions to the development of technology that gives the power to modern computer vision systems today.

Bengio has researched a new method to create a wide-ranging, contradictory network that can create original images from basic strokes.

All three scientists are optimistic about the future of machine learning and neural networks, but also express their vigilance about the practical applications they can bring, one of which is their use. to develop weapons systems.