Deep Learning Pioneer On the Next Generation of Hardware For Neural Networks

An anonymous reader writes: While many recognize Yann LeCun as the father of convolutional neural networks, the momentum of which has ignited artificial intelligence at companies like Google, Facebook and beyond, LeCun has not been strictly rooted in algorithms. Like others who have developed completely new approaches to computing, he has an extensive background in hardware, specifically chip design and this recognition of specialization of hardware, movement of data around complex problems, and ultimately core performance, has proven handy. He talks in depth this week about why FPGAs are coming onto the scene as companies like Google and Facebook seek a move away from "proprietary hardware" and look to "programmable devices" to do things like, oh, say, pick out a single face of one's choosing from an 800,000 strong population in under five seconds.

Comments

Re:The problem with neural networks

[Sneeka2]

Sure, it's all extremely difficult. I'd think with neural networks you can use an evolutionary approach and eventually choose the program which has evolved and performed best over a series of X million of tests. The question "when is the program done" doesn't mean "when has the programmer thought of every last possibility" anymore, but rather "when are we satisfied enough with the statistics that we trust this program enough?"