How Does AI Work? Researchers Reveal the Mechanism Underlying Successful Machine Learning

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Researchers from Bar-Ilan University have uncovered how machine learning successfully classifies images, revealing that each filter in a deep learning architecture recognizes and refines the recognition of image clusters through layers.

Current AI architectures can successfully perform image classification tasks, competing with human capabilities. Yet what is the mechanism that makes <span class="glossaryLink" aria-describedby="tt" data-cmtooltip="

machine learning

Machine learning is a subset of artificial intelligence (AI) that deals with the development of algorithms and statistical models that enable computers to learn from data and make predictions or decisions without being explicitly programmed to do so. Machine learning is used to identify patterns in data, classify data into different categories, or make predictions about future events. It can be categorized into three main types of learning: supervised, unsupervised and reinforcement learning.

” data-gt-translate-attributes=”[{"attribute":"data-cmtooltip", "format":"html"}]” tabindex=”0″ role=”link”>machine learning so successful?

Image classification is a complex task that deep learning architectures perform successfully. Those deep architectures are usually comprised of many layers, with each layer consisting of many filters. The common understanding is that as the image progresses through the layers more enhanced features, and features of features, of the image are revealed. Yet those features and features of features are not quantifiable, and thus how machine learning works remains a puzzle.

In an article recently published in <span class="glossaryLink" aria-describedby="tt" data-cmtooltip="

Scientific Reports

Established in 2011, <em>Scientific Report</em>s is a peer-reviewed open-access scientific mega journal published by Nature Portfolio, covering all areas of the natural sciences. In September 2016, it became the largest journal in the world by number of articles, overtaking <em>PLOS ON</em>E.

” data-gt-translate-attributes=”[{"attribute":"data-cmtooltip", "format":"html"}]” tabindex=”0″ role=”link”>Scientific Reports, researchers from Bar-Ilan University reveal the mechanism underlying successful machine learning, which enables it to perform classification tasks with resounding success. “Each filter essentially recognizes a small cluster of images and as the layers progress the recognition is sharpened. We found a way to quantitatively measure the performance of a single filter,” said Prof. Ido Kanter, of Bar-Ilan’s Department of Physics and Gonda (Goldschmied) Multidisciplinary Brain Research Center, who led the research.

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A video describing the research. Credit: Prof. Ido Kanter, Bar-Ilan University

“This discovery can pave the path to better understanding how AI works,” said PhD student Yuval Meir, one of the key contributors to the work, adding, “This can improve the latency, memory usage, and complexity of the architecture without reducing overall <span class="glossaryLink" aria-describedby="tt" data-cmtooltip="

accuracy

How close the measured value conforms to the correct value.

” data-gt-translate-attributes=”[{"attribute":"data-cmtooltip", "format":"html"}]” tabindex=”0″ role=”link”>accuracy.” While AI has been at the forefront of recent technological progress, comprehending how such machines actually work can open the way for even more advanced AI.

Reference: “Towards a universal mechanism for successful deep learning” by Yuval Meir, Yarden Tzach, Shiri Hodassman, Ofek Tevet and Ido Kanter, 11 March 2024, Scientific Reports.
DOI: 10.1038/s41598-024-56609-x