Artificial intelligence, usually in the form of machine learning (ML), is infosecurity’s current buzz. Many consider it will be the savior of the internet, able to defeat hackers and malware by learning and responding to their behavior in all-but real time. But others counsel caution: it is a great aid; but not a silver bullet.

The basic problem is that if machine learning can learn to detect malware, machine learning can learn to avoid detection by machine learning. This is a problem that exercises Hyrum Anderson, technical director of data science at Endgame.

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