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The system is based off human vision systems and will be applied to fully-autonomous vehicles

Researchers at Yale University and New York University have developed a new supercomputer that is capable of navigating a car more quickly and efficiently through the use of a human-based visual system. 

The supercomputer is called NeuFlow, and it was created by Eugenio Culurciello of Yale's School of Engineering & Applied Science along with Yann LeCun from New York University. Culurciello developed the human-inspired system while LeCun supplied the complex vision algorithms, which runs the neural networks for synthetic vision applications. NeuFlow's actions are based on the human visual system, acting as quickly and efficiently as a human when obeying traffic laws, distinguishing different objects from one another such as trees and buildings, and reacting to other drivers on the road. 

Culurciello and LeCun are looking to use this supercomputer as a way for cars to drive themselves. To do this, NeuFlow runs more than 100 billion operations per second only using a few watts of power, which is less than what's required to power a cell phone. NeuFlow exists on a single chip, making it no larger than a wallet, but it is more efficient and powerful than full-scale computers. Also, this system "processes tens of megapixel images in real time." 

"One of our first prototypes of this system is already capable of outperforming graphic processors on vision tasks," said Culurciello.

The development of fully-autonomous vehicle's will be a significant advancement in the world of human convenience and safety, and that's why NeuFlow isn't the only computer-driven system out there right now. 

In 2008, DailyTech went for a spin in the Chevrolet Tahoe DARPA Challenge vehicle, which is a fully-autonomous vehicle that won the DARPA 2007 Urban Challenge and is equipped with GPS, radar, video, laser and LIDAR sensors and inputs to recognize objects on the road. Its key sensor, velodyne, has 64 sensors in a wide array and is able to collect one million bits of data per second at 10 Hz. It's logic consists of over 350,000 lines of code, and is able to obtain a 3-D view of the surrounding terrain just like NeuFlow.

But unlike the Chevrolet Tahoe DARPA Challenge vehicle, NeuFlow is not quite ready for vehicle use yet. Culurciello and LeCun are looking to use NeuFlow in other applications as well, such as a tool for 360-degree synthetic vision for soldiers in combat and to help improve robot navigation in dangerous locations. 

NeuFlow was presented by Culurciello at the High Performance Embedded Computing (HPEC) workshop in Boston, Mass. on September 15. 



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RE: OK
By Smartless on 9/16/2010 2:29:42 PM , Rating: 2
Ah yes, pods, that's a transportation engineer's vision. There's even been research into computer brains taking over on the freeway so that you can literally tailgate another car to increase the road capacity. In any case, iRobot comes to mind especially since Will Smith still "drove" his car. We Americans love our cars for its freedom, its unique expression, and because not everyone lives where mass transit is practical. Will this AI driven vehicles see consumer use? Maybe, but how much you want to bet someone's going to root their AI to program it to race or swerve in and out of traffic lol.


RE: OK
By geddarkstorm on 9/16/2010 3:27:27 PM , Rating: 2
I could see Japan loving something like this. Not only because they enjoy, culturally, being on the cutting edge AI/Robot wise, but also because of the population densities in their major city areas (being an island and all). This could be a serious boon to commuting.

For the US, we have tons of open space and sprawl, so computer controlled freeway systems are necessary or practical for the vast majority of the country. That would make it much harder to roll out, even selectively.


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