AI with AI
Episode 1.14: Meta AI
Andy and Dave cover a series of topics that evoke broader to connect with the "meta" questions about the role and nature of AI. They begin with Google's Cloud AutoML announcement, which offers ways to more easily build your own AI. They discuss the announcement of AIs that "defeated" humans on a Standard University reading comprehension text, and the misrepresentation of that achievement. They discuss deep image reconstruction, with a neural net that "read minds" by piecing together images from a human's visual cortex. And they close with discussions about Gary Marcus's recent article, which offers a critical appraisal of Deep Learning, and a recent paper that suggests that convolutional neural nets may not be as good at "grasping" higher-level abstract concepts as is typically believed.