Sources Contact Advanced Search Tutorials

An Interest In:

Web News this Week

Search Archive

Some of Our Sources

View All Sources

Help Webnuz

Referal links:

October 10, 2019 04:01 pm

An AI Pioneer Wants His Algorithms To Understand the 'Why'

Deep learning is good at finding patterns in reams of data, but can't explain how they're connected. Turing Award winner Yoshua Bengio wants to change that. From a report: In March, Yoshua Bengio received a share of the Turing Award, the highest accolade in computer science, for contributions to the development of deep learning -- the technique that triggered a renaissance in artificial intelligence, leading to advances in self-driving cars, real-time speech translation, and facial recognition. Now, Bengio says deep learning needs to be fixed. He believes it won't realize its full potential, and won't deliver a true AI revolution, until it can go beyond pattern recognition and learn more about cause and effect. In other words, he says, deep learning needs to start asking why things happen. The 55-year-old professor at the University of Montreal, who sports bushy gray hair and eyebrows, says deep learning works well in idealized situations but won't come close to replicating human intelligence without being able to reason about causal relationships. "It's a big thing to integrate [causality] into AI," Bengio says. "Current approaches to machine learning assume that the trained AI system will be applied on the same kind of data as the training data. In real life it is often not the case."

Slashdot

Slashdot was originally created in September of 1997 by Rob "CmdrTaco" Malda. Today it is owned by Geeknet, Inc..

More About this Source Visit Slashdot