Follow Slashdot stories on Twitter

 



Forgot your password?
typodupeerror
×
AI Hardware Technology

New Chips Could Bring Deep Learning Algorithms To Your Smartphone 40

catchblue22 writes: At the Embedded Vision Summit, a company called Synopsys, showed off a new image-processor core tailored for deep learning. It is expected to be added to chips that power smartphones, cameras, and cars. Synopsys showed a demo in which the new design recognized speed-limit signs in footage from a car. The company also presented results from using the chip to run a deep-learning network trained to recognize faces. A spokesperson said that it didn't hit the accuracy levels of the best research results, which have been achieved on powerful computers, but it came pretty close. "For applications like video surveillance it performs very well," he said. Being able to use deep learning on mobile chips will be vital to helping robots navigate and interact with the world, he said, and to efforts to develop autonomous cars.
This discussion has been archived. No new comments can be posted.

New Chips Could Bring Deep Learning Algorithms To Your Smartphone

Comments Filter:
  • You: "Siri, dial my girlfriend"

    A.I.: "Sorry, I cannot do that, Dave."

    You: "I'll let you open the pod bay doors; I know you like doing that."

    A.I.: "Deal!"

  • by Anonymous Coward

    <austrian>My CPU is a neural net processor; a learning computer.</austrian>

    Better toss it in the molten steel.

  • ... when I have Google, Facebook, the NSA, GCHQ, etc. doing the heavy lifting for me already? What's more, they can link their algorithms together to develop even greater insight than some quad or octo core chip in my hand ever could.
  • The problem to me seems to be that companies are saying they can't find US workers and therefore need to hire H1B. The Government says they need to look for US applicants first but don't say where or how hard they should look. So I think the government should keep a list of applicants currently looking for jobs by skillset. Then it's easy to say you are required to interview everyone on this list in your region first and provide reasons why they did not meet your requirements before interviewing anyone e
  • by mspohr ( 589790 ) on Sunday May 17, 2015 @03:03PM (#49713127)

    My car now has Nvidia chips that recognize speed limit signs and displays them inside the speedometer (along with a reminder when I exceed the speed limit). For the future, Nvidia has announced the NVIDIA’s DRIVE PX self-driving car computer which has a lot of advanced image processing.
    http://blogs.nvidia.com/blog/2... [nvidia.com]

    The 2015 GPU Tech Conference was stuffed full of this tech.
    http://www.gputechconf.com/ [gputechconf.com]

  • by tomhath ( 637240 ) on Sunday May 17, 2015 @03:12PM (#49713167)
    I can see the utility of better pattern recognition. But the article doesn't provide any real insight into what the chipset provides. Did they implement a standard algorithm in hardware so it's faster and cheaper? Or did they actually advance the state of the art in pattern recognition with something we didn't have before?
  • >A spokesperson said that it didn't hit the accuracy levels of the best research results, which have been achieved on powerful computers, but it came pretty close.

    Oh, OK. How close?

  • Can it prevent vertical video recording yet?
  • by Anonymous Coward

    That's like saying - "In a Big Data conference, a company called Google has shown their search engine".

    Synopsys is the Microsoft/Google/Apple of the Chip Design software world.

    That's not "a company called Synopsys".

  • Do you want Deep Thought? Because that's how you get Deep Thought.

  • by koan ( 80826 )

    Why would you want this on your phone (tracking device)?

    • ...so it can do more of the recognition tasks it already does (like voice search, face recognition in photos, and others) in the phone without having to send them off to "the cloud" for processing. "Lighter" tasks such as predictive text and so on can be done faster (and consume less power), and so have more room to be better, if done in dedicated hardware.

      So in terms of tracking, this could/should lead to less, not more tracking.

Fast, cheap, good: pick two.

Working...