Deep learning, the category of AI algorithms that kick-started the field’s most recent revolution, has made immense strides in giving machines perceptual abilities like vision. But it has fallen short in imbuing them with sophisticated reasoning… . In other words, machines don’t truly understand the world around them, which makes them fall short in their ability to engage with it.
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“Obviously we’re missing something,” [Facebook AI scientist Yann LeCunn] said. … A teen can learn to drive safely by practicing for 20 hours and manage to avoid crashes without first experiencing one, while reinforcement-learning algorithms (a subcategory of deep learning) must go through tens of millions of trials, including many egregious failures.
The answer, he thinks, is in the underrated deep-learning subcategory known as unsupervised learning.
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LeCun believes the emphasis should be flipped. “Everything we learn as humans—almost everything—is learned through self-supervised learning. There’s a thin layer we learn through supervised learning, and a tiny amount we learn through reinforcement learning,” he said.
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Ultimately, unsupervised learning will help machines develop a model of the world that can then predict future states of the world, he said.
Read full, original post: The AI technique that could imbue machines with the ability to reason
