Path: EDN Asia >> News Centre >> IC/Board/Systems Design >> Deep learning set to revolutionise computer, automotive vision
IC/Board/Systems Design Share print

Deep learning set to revolutionise computer, automotive vision

01 Apr 2015  | Junko Yoshida

Share this page with your friends

There is sufficient evidence to support chip vendors' growing enthusiasm for deep learning, and more specifically, convolutional neural networks (CNN), which are widely used models for image and video recognition. In fact, deep learning is now changing the way computers see, hear and identify objects in the real world.

However, the bigger, and perhaps more pertinent, issues for the semiconductor industry are: Will "deep learning" ever migrate into smartphones, wearable devices, or the tiny computer vision SoCs used in highly automated cars? Has anybody come up with SoC architecture optimised for neural networks? If so, what does it look like?

"There is no question that deep learning is a game-changer," said Jeff Bier, a founder of the Embedded Vision Alliance. In computer vision, for example, deep learning is very powerful. "The caveat is that it's still an empirical field. People are trying different things," he said.

Earlier this month, Qualcomm introduced its "Zeroth platform," a cognitive-capable platform that's said to "mimic the brain." It will be used for future mobile chips, including its forthcoming Snapdragon 820, according to Qualcomm.

Cognivue is another company vocal about deep learning. The company claims that its latest embedded vision SoC architecture, called Opus, will take advantage of deep learning advancements to increase detection rates dramatically. Cognivue is collaborating with the University of Ottawa.

If presentations at Nvidia's recent GPU Technology Conference (GTC) were any indication, you get the picture that Nvidia is banking on the all aspects of deep learning in which GPU holds the key.

China's Baidu, a giant in search technology, has been training deep neural network models to recognise general classes of objects at data centres. It plans to move such models into embedded systems.

Search results of cats that look like dogs

Search results of 'cats that look like dogs' (Source: Yahoo)

Zeroing in on this topic during a recent interview with EE Times, Ren Wu, a distinguished scientist at Baidu Research, said, "Consider the dramatic increase of smartphones' processing power. Super intelligent models, extracted from the deep learning at data centres, can be running inside our handset." A handset so equipped can run models in place without having to send and retrieve data from the cloud. Wu, however, added, "The biggest challenge is if we can do it at very low power.

AI to Deep learning

One thing is clear. Gone are the frustration and disillusion over artificial intelligence (AI) that marked the late 1980s and early '90s. In the new "big data" era, larger sets of massive data and powerful computing have combined to train neural networks to distinguish objects. Deep learning is now considered a new field moving toward AI.

1 • 2 • 3 • 4 Next Page Last Page


Want to more of this to be delivered to you for FREE?

Subscribe to EDN Asia alerts and receive the latest design ideas and product news in your inbox.

Got to make sure you're not a robot. Please enter the code displayed on the right.

Time to activate your subscription - it's easy!

We have sent an activate request to your registerd e-email. Simply click on the link to activate your subscription.

We're doing this to protect your privacy and ensure you successfully receive your e-mail alerts.


Add New Comment
Visitor (To avoid code verification, simply login or register with us. It is fast and free!)
*Verify code:
Tech Impact

Regional Roundup
Control this smart glass with the blink of an eye
K-Glass 2 detects users' eye movements to point the cursor to recognise computer icons or objects in the Internet, and uses winks for commands. The researchers call this interface the "i-Mouse."

GlobalFoundries extends grants to Singapore students
ARM, Tencent Games team up to improve mobile gaming


News | Products | Design Features | Regional Roundup | Tech Impact