Windows 10: 2nd version of HoloLens HPU will incorporate AI coprocessor for DNNs

Brink · Jul 23, 2017

It is not an exaggeration to say that deep learning has taken the world of computer vision, and many other recognition tasks, by storm. Many of the most difficult recognition problems have seen gains over the past few years that are astonishing.

Although we have seen large improvements in the accuracy of recognition as a result of Deep Neural Networks (DNNs), deep learning approaches have two well-known challenges: they require large amounts of labelled data for training, and they require a type of compute that is not amenable to current general purpose processor/memory architectures. Some companies have responded with architectures designed to address the particular type of massively parallel compute required for DNNs, including our own use of FPGAs, for example, but to date these approaches have primarily enhanced existing cloud computing fabrics.

But I work on HoloLens, and in HoloLens, we’re in the business of making untethered mixed reality devices. We put the battery on your head, in addition to the compute, the sensors, and the display. Any compute we want to run locally for low-latency, which you need for things like hand-tracking, has to run off the same battery that powers everything else. So what do you do?

You create custom silicon to do it.

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First, a bit of background. HoloLens contains a custom multiprocessor called the Holographic Processing Unit, or HPU. It is responsible for processing the information coming from all of the on-board sensors, including Microsoft’s custom time-of-flight depth sensor, head-tracking cameras, the inertial measurement unit (IMU), and the infrared camera. The HPU is part of what makes HoloLens the world’s first–and still only–fully self-contained holographic computer.

Today, Harry Shum, executive vice president of our Artificial Intelligence and Research Group, announced in a keynote speech at CVPR 2017, that the second version of the HPU, currently under development, will incorporate an AI coprocessor to natively and flexibly implement DNNs. The chip supports a wide variety of layer types, fully programmable by us. Harry showed an early spin of the second version of the HPU running live code implementing hand segmentation.

The AI coprocessor is designed to work in the next version of HoloLens, running continuously, off the HoloLens battery. This is just one example of the new capabilities we are developing for HoloLens, and is the kind of thing you can do when you have the willingness and capacity to invest for the long term, as Microsoft has done throughout its history. And this is the kind of thinking you need if you’re going to develop mixed reality devices that are themselves intelligent. Mixed reality and artificial intelligence represent the future of computing, and we’re excited to be advancing this frontier.

Marc Pollefeys,
Director of Science, HoloLens
Click to expand...

Source: Second version of HoloLens HPU will incorporate AI coprocessor for implementing DNNs - Microsoft Research

:)

LCRT · Jul 23, 2017

hololens powered by the 950 and 950xl

if you understood it, you wouldn't mention hololens at all. it has nothing to do with what you are talking about.

it is not an affordable version of hololens - because it is NOT the same type of tech. you clearly do not understand the difference.

HOLOLENS is not the same type of product. do not associate VR using a phone with an augmented reality headset. they're not related at all.

ACESsiggy · Jul 23, 2017

Missing coprocessor in Windows 10

Similar issue but this is under "Other devices" for what he's referring to this Coprocessor. My Nvidia Geforce GTX 560 is installed and updated to the latest driver version but it's under "display adapters". So I guess what he and I'm wondering is "other
devices" and coprocessor ....

Windows 10: 2nd version of HoloLens HPU will incorporate AI coprocessor for DNNs

2nd version of HoloLens HPU will incorporate AI coprocessor for DNNs

2nd version of HoloLens HPU will incorporate AI coprocessor for DNNs

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