Recent advances in machine learning make it tempting to believe that ML and, more broadly, AI will be a silver bullet, capable of making progress on any real-world problem it’s applied to. But is that really so?
Aleksander Madry discusses major roadblocks that prevent current AI frameworks from having a broad impact and outlines approaches to addressing these issues and making AI frameworks truly human-ready.
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