Movidius, Google Team Up To Leverage Deep Learning On Mobile Devices

[scolaner]

Movidius and Google are teaming up to get the benefits of Deep Learning onto mobile devices. You'll get the magic of Deep Learning on-device, without needing to be connected to the Internet.

Movidius, Google Team Up To Leverage Deep Learning On Mobile Devices : Read more

 

[bit_user]

El-Ouazzane did not elaborate on how the device may take its acquired data and send it back to Google so it could be added to the database, but it must, somehow. Without that exchange of information, neither the neural net at large nor the model on-device could grow.

The communication will probably follow the existing model of Android updates. Google will probably collect data, as an independent activity, then train their models & improve their algorithms on their servers. The resulting code & data would be pushed out to devices, periodically.

Maybe Google will surprise us withe some kind of distributed learning that harnesses the compute power and data from the devices to update their centralized model, but that's not how this sort of thing is usually done.

Of course, devices can learn things about their owner and the environment they inhabit, but I see that as a sort of user-specific customization and not something that would get propagated back to Google.

 

[bit_user]

What we’re seeing here, to me, is a certain parity between the importance of the device and the importance of the cloud. They need each other. Therefore, Google and Movidius need each other.

I'm not too sure about that. Qualcomm has the Zeroth engine in some of their new Snapdragon SoC's (the 820, possibly others). I'd bet they'll support Google's new deep learning APIs, just like how we're seeing both Intel and Lenovo support the Tango API, using different hardware. My guess is that Google is probably partnering with Movidius to foster an ecosystem, so that Qualcomm won't completely dominate the space.

As for complementing the cloud, I really don't see this as being any different than the GPU or many other built-in device functions. There are lots of things these devices need to do that just make more sense to be integrated into the device, if possible. Plus, doing this stuff in the cloud would eat bandwidth and require a substantial amount of processing power.

 

[hst101rox]

It's interesting you have this article on Deep Learning today, but also on this topic is that Google's Deep Mind (Deep Learning?) beat a human player at the ancient chinese board game called Go, previously thought impossible.

 

[bit_user]

It's interesting you have this article on Deep Learning today, but also on this topic is that Google's Deep Mind (Deep Learning?) beat a human player at the ancient chinese board game called Go, previously thought impossible.

The article was prompted by Google/Movidius' announcement. That they made it today might have been coincidence, or possibly they chose to announce it now to benefit from the buzz around that event.

Speaking of which, where's the article about that?

 

[hst101rox]

Speaking of which, where's the article about that?

https://www.washingtonpost.com/news/innovations/wp/2016/01/27/google-just-mastered-a-game-thats-vexed-scientists-for-decades/?tid=sm_fb

 

[bit_user]

Speaking of which, where's the article about that?

https://www.washingtonpost.com/news/innovations/wp/2016/01/27/google-just-mastered-a-game-thats-vexed-scientists-for-decades/?tid=sm_fb

Thanks, but that was meant as a nudge for Tom's to get with it!
😉