In 2007, we told you about Stanford's Neurocore chip which sported a 256x256 array of neurons, each designed to duplicate biological neurons down to the level of protein pores and ion channels. A new generation of neural network hardware is being developed by the Fast Analog Computing with Emergent Transient States (FACETS) Project. The FACETS hardware will have 200,000 neurons with 50 million synapses built on a single silicon wafer. Current prototypes are running 100,000 times faster than their biological couterparts, allowing a full day of neural activity to be simulated in less than a second. Physicist Karlheinz Meier, who coordinates the project, said,
We may then be able to make computing devices which are radically different and have amazing performance which, at some point, may approach the performance of the human brain – or even go beyond it!”
Aside from being much faster than computer simulations of neural networks, neural hardware is also much more power efficient, typically using only a tiny fraction of the power consumed by attempts to simulate large networks on super computers such as the Blue Brain Project. For more, see the Technology Review article, the Science Daily article, or check out the many technical papers available from FACET. (image courtesy of FACETS Project, Ruprecht-Karls Universität Heidelberg).