See the recording here.

The Kraw Lecture Series in Silicon Valley is made possible by a generous gift from UC Santa Cruz alumnus George Kraw (Cowell ‘71, history and Russian literature) and Raphael Shannon Kraw. The lecture series features acclaimed UC Santa Cruz scientists and technologists who are grappling with some of the biggest questions of our time.

Abstract: The brain is the perfect place to look for inspiration to develop more efficient neural networks. Indeed, the inner workings of our synapses and neurons offer a glimpse at what the future of deep learning might look like. Our brains are constantly adapting, our neurons processing all that we know, mistakes we’ve made, failed predictions—all working to anticipate what will happen next with incredible speed. Our brains are also amazingly efficient. Training large-scale neural networks can cost more than $10 million in energy expense, yet the human brain does remarkably well on a power budget of 20 watts.

We can apply the computational principles that underpin the brain, and use them to engineer more efficient systems that adapt to ever changing environments. There is an interplay between neural inspired algorithms, how they can be deployed on low-power microelectronics, and how the brain provides a blueprint for this process.