My favorite podcast, by far, is the a16z Podcast. Every edition provides interesting insights on topics technologists and forward thinking executives should track.
The topic I just listed to featured Fei-Fei Li, associate professor at Stanford University, along with the brilliant star of tech trend context Sonal Chokshi and the famous a16z partner Frank Chen. The topic was “When Humanity Meets A.I.” and I could not think of a better team to examine the many facets of this interesting topic. From the podcast description:
Who has the advantage in artificial intelligence — big companies, startups, or academia? Perhaps all three, especially as they work together when it comes to fields like this. One thing is clear though: A.I. and deep learning is where it’s at. And that’s why this year’s newly anointed Andreessen Horowitz Distinguished Visiting Professor of Computer Science is Fei-Fei Li [who publishes under Li Fei-Fei], associate professor at Stanford University. Bridging entrepreneurs across academia and industry, we began the a16z Professor-in-Residence program just a couple years ago (most recently with Dan Boneh and beginning with Vijay Pande).
Li is the Director of the Stanford Vision Lab, which focuses on connecting computer vision and human vision; is the Director of the Stanford Artificial Intelligence Lab (SAIL), which was founded in the early 1960s; and directs the new SAIL-Toyota Center for AI Research, which brings together researchers in visual computing, machine learning, robotics, human-computer interactions, intelligent systems, decision making, natural language processing, dynamic modeling, and design to develop “human-centered artificial intelligence” for intelligent vehicles. Li also co-created ImageNet, which forms the basis of the Large Scale Visual Recognition Challenge (ILSVRC) that continually demonstrates drasticadvancesin machine vision accuracy.
So why now for A.I.? Is deep learning “it”… or what comes next? And what happens as A.I. moves from what Li calls its “in vitro phase” to its “in vivo phase”? Beyond ethical considerations — or celebrating only “geekiness” and “nerdiness” — Li argues we need to inject a stronger humanistic thinking element to design and develop algorithms and A.I. that can co-habitate with people and in social (including crowded) spaces.
Download this edition at: When Humanity Meets A.I
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