A Real Test for Object Recognition

February 9, 2009

Dun dun dun

Humans are remarkably good at identifying the same face across illuminations, positions, deformations, and depths. The same face can even be identified through fences, glass, and water. The possible number of contexts for a face to appear in are infinite, yet we can identify it instantaneously. For whatever reason, we are really good at identifying objects, but researchers have struggled to make computers even semi-competent at it. One of the more valiant efforts is Yann LeCun’s use of convolutional nets, but its primary successes are in controlled situations. Any reasonable person in the field would agree that any human can wipe the floor with even the best algorithm running on the best supercomputer (programmed by the best programmer in the best department in the best state in the best country!). So what gives?

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IBM Seeks to Build the Computer of the Future Based on Insights from the Brain

February 4, 2009

In december 2008, a video post has been published on Abovetopsecret.com  with the title “DARPA & IBM building a “global brain” “cognitive computer” for “monitoring people”. In this video, the leader of the IBM SyNAPSE project, Dharmendra Modha, talks about SyNAPSE.

This is an excerpt from the video:
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“Hello World” on Memristive Nanodevices

February 3, 2009

SyNAPSE is not a project DARPA undertook lightly. Many attempts at large-scale neuromorphic engineering have been made in the past. None met their goals. As such, SyNAPSE owes its existence to a number of recent game-changing developments. From HP Labs, the discovery of the memristor was one such keystone innovation. It took Greg Snider’s 2007 work in Nanotechnology, however, to establish memristors as a viable platform for the implementation of self-organizing recurrent neural networks.

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