Yann LeCun on the future of deep learning hardware


LeCun says the demand for DL-specific hardware will likely only increase. New architectural concepts such as dynamic networks, associative-memory structures, and sparse activations will affect the type of hardware architecture that will be required in the future.
“This might require us to reinvent the way we do arithmetic in circuits,” LeCun says. Computer chips today are typically not optimized for deep learning, which can be effective even when using less precise calculations. “So, people are trying to design new ways of representing numbers that will be more efficient.”

The link is to a video; it's 6 minutes long. Worthwhile.


Want to receive more content like this in your inbox?