The need to train their deep neural networks as fast as possible led the Evolving Artificial Intelligence Laboratory at the University of Wyoming to harness the power of NVIDIA Tesla GPUs starting in 2012 to accelerate their research.
“The speedups GPUs provide for training deep neural networks are well-documented and allow us to train models in a week that would otherwise take months,” said Jeff Clune, Assistant Professor, Computer Science Department and Director of the Evolving Artificial Intelligence Laboratory. “And algorithms continuously improve. Recently, NVIDIA’s cuDNN technology allowed us to speed up our training time by an extra 20% or so.”
Clune’s Lab, which focuses on evolving artificial intelligence with a major focus on large-scale, structurally organized neural networks, has garnered press from some of the largest media outlets, including BBC, National Geographic, NBC News, The Atlantic and featured on the cover of Nature in May 2015.
[The following video shows off work from the Evolving AI Lab on visualizing deep neural networks. Keep reading to learn more about this work!]
For this Spotlight interview, I had the opportunity to talk with Jeff Clune and two of his collaborators, Anh Nguyen, a Ph.D. student at the Evolving AI Lab and Jason Yosinski, a Ph.D. candidate at Cornell University.
Brad: How are you using deep neural networks (DNNs)?
We have many research projects involving deep neural networks. Our Deep Learning publications to date involve better understanding DNNs. Our lab’s research covers: Continue reading