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The problem of common-sense reasoning has plagued the field of artificial intelligence for over 50 years. Now a new approach, borrowing from two disparate lines of thinking, has made important progress.
By teaching machines to understand our true desires, one scientist hopes to avoid the potentially disastrous consequences of having them do what we command.
The laws of physics stay the same no matter one’s perspective. Now this idea is allowing computers to detect features in curved and higher-dimensional space.
By ignoring their goals, evolutionary algorithms have solved longstanding challenges in artificial intelligence.
Researchers have discovered a surprising mathematical relationship in the brain’s representations of sensory information, with possible applications to AI research.
A tool known as BERT can now beat humans on advanced reading-comprehension tests. But it’s also revealed how far AI has to go.
In some ways, machine vision is superior to human vision. In other ways, it may never catch up.
Mathematicians and neuroscientists have created the first anatomically accurate model that explains how vision is possible.
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