Tag Archives: artificial intelligence

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“Neurogrid” circuit modeled on the human brain is the fastest, most energy efficient of its kind

Stanford Bioengineer Kwabena Boahen’s “Neurogrid” can simulate one million neurons and billions of synaptic connections. Neuromorphic systems realize the function of biological neural systems by emulating their structure. As I suggested in my own theory of consciousness, a successful artificial consciousness must have both structural and algorithmic components. The structural component must be involved in tuning and amplifying the fundamental awareness inherent in all physical matter for there to be true consciousness. In other words, consciousness can not be expressed purely through information manipulation using discrete rule-sets and algorithms.

The Neurogrid’s microchips are 9,000 times faster and uses significantly less power than those found in a typical PC. The inventors of the “Neurogrid” expect they should be able to bring the cost of a system board down to about $400 from the current cost of $40,000.

The abstract and technical paper can be found here: http://goo.gl/vwJPXn

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A New Approch to Artificial Intelligence

A New Approch to Artificial Intelligence

There are many things humans find easy to do that computers are currently unable to do. Tasks such as visual pattern recognition, understanding spoken language, recognizing and manipulating objects by touch, and navigating in a complex world are easy for humans. Yet despite decades of research, we have few viable algorithms for achieving human-like performance on a computer.

In humans, these capabilities are largely performed by the neocortex. The Cortical Learning Algorithm (CLA) is a technology modelled on how the neocortex performs these functions. It offers the groundwork for building machines that approach or exceed human level performance for many cognitive tasks. The CLA is implemented within the NuPIC open source project.