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 is applied to. But is that really so?
In this talk, Aleksander will discuss major roadblocks that prevent the current AI framework from having this kind of broad impact and will outline approaches to addressing these issues and making this framework truly “human-ready”.
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