Innovative Machine Learning Training Method Opens New Possibilities for Artificial Intelligence

From AZoRobotics:  As a result of a new machine learning algorithm formulated by engineering researchers Parham Aarabi (ECE) and Wenzhi Guo (ECE MASc 1T5) at University of Toronto, smartphones may soon be able to provide users with honest answers.

The researchers prepared an algorithm that was capable of learning directly from human instructions, instead of an existing set of examples, and surpassed conventional techniques of training neural networks by 160%.

But more astonishingly, their algorithm also surpassed its own training by 9% - it learned to identify hair in pictures with better reliability than that enabled by the training, signifying a major leap forward for artificial intelligence.  Cont'd...

Comments (0)

This post does not have any comments. Be the first to leave a comment below.


Post A Comment

You must be logged in before you can post a comment. Login now.

Featured Product

FAULHABER MICROMO - Game changer in logistics

FAULHABER MICROMO - Game changer in logistics

Faster, more efficient, more sustainable - due to global competition in industry combined with booming online trade, transport structures in intralogistics are facing new challenges. The industries' answer: Automation. From storage to shipping, key work steps are being taken over by intelligent logistics robots, such as automatic storage and retrieval machines and driverless transport systems. To work efficiently and reliably around the clock, these robots need flexible and particularly compact drive solutions.