Category: AI

Thoughts from MWC Shanghai

on June 29, 2017

I’ve spent the last couple days walking the exhibition halls of MWC Shanghai. The Shanghai New International Expo Centre (SNIEC) is large, but smaller than the MWC exhibit space in Barcelona or the set of exhibit halls in Las Vegas for CES. (SNIEC is not even the biggest exhibition space in Shanghai!) Further, MWC here still only took up half the exhibition space, but there was plenty to see. And, I’m less exhausted than after CES or MWC in Barcelona!

If I had to pick one theme from the exhibition halls, it would be 5G. It seemed like half the booths had 5G displayed somewhere in their signage. The cloud was the other concept that seemed to be everywhere. While neither was surprising, it was interesting to see halfway around the world. In truth, it feels like 5G is much farther along here than it is back in the States.

I was also surprised to see how many phone vendors are here that I’d never heard of before such as Lephone and Gionee. I stopped by their booths with XPRT Spotlight information and hope they will send in some of their devices for inclusion in the future.

One thing I found of note was how much technology in general and IoT in particular is going to be everywhere. There was an interesting exhibit showing how stores of the future might operate. I was able to “buy” items without traditionally checking out. (I got a free water and some cookies out of the experience.) I just placed the items in a location on the checkout counter, which read their NFC labels and displayed them on the checkout screen. It seemed sort of like my understanding of the experiments that Amazon has been doing with brick-and-mortar grocery stores (prior to their purchase of Whole Foods). The whole experience felt a bit odd and still unpolished, but I’m sure it will improve and I’ll get used to it.

The next generation will find it not odd, but normal. There were exhibits with groups of children playing with creative technologies from handheld 3D printers to simplified programming languages. They will be the generation after digital natives, maybe the digital creatives? What impact will they have? The future is both exciting and daunting!

I came away from the conference thinking about how the XPRTs can help folks choose amongst the myriad devices and technologies that are just around the corner. What would you most like to see the XPRTs tackle in the next six months to a year?

Bill Catchings

Posted in 5G, AI, computer vision, Education, Future of performance evaluation, Internet of things, IoT, Mobile World Congress, Mobile World Congress, Trade Shows |

Learning about machine learning

By Bill Catchings

on April 27, 2017

Everywhere we look, machine learning is in the news. It’s driving cars and beating the world’s best Go players. Whether we are aware of it or not, it’s in our lives–understanding our voices and identifying our pictures.

Our goal of being able to measure the performance of hardware and software that does machine learning seems more relevant than ever. Our challenge is to scan the vast landscape that is machine learning, and identify which elements to measure first.

There is a natural temptation to see machine learning as being all about neural networks such as AlexNet and GoogLeNet. However, new innovations appear all the time and lots of important work with more classic machine learning techniques is also underway. (Classic machine learning being anything more than a few years old!) Recursive neural networks used for language translation, reinforcement learning used in robotics, and support vector machine (SVM) learning used in text recognition are just a few examples among the wide array of algorithms to consider.

Creating a benchmark or set of benchmarks to cover all those areas, however, is unlikely to be possible. Certainly, creating such an ambitious tool would take so long that it would be of limited usefulness.

Our current thinking is to begin with a small set of representative algorithms. The challenge, of course, is identifying them. That’s where you come in. What would you like to start with?

We anticipate that the benchmark will focus on the types of inference learning and light training that are likely to occur on edge devices. Extensive training with large datasets takes place in data centers or on systems with extraordinary computing capabilities. We’re interested in use cases that will stress the local processing power of everyday devices.

We are, of course, reaching out to folks in the machine learning field—including those in academia, those who create the underlying hardware and software, and those who make the products that rely on that hardware and software.

What do you think?

Bill

Posted in AI, AR, Augmented reality, Automated cars, Automation, computer vision, Future of performance evaluation, Machine learning, What makes a good benchmark? |

Mobile World Congress 2017 and the territories ahead

By Mark Van Name

on March 2, 2017

Walking the halls of this year’s Mobile World Congress (MWC)—and, once again, I walked by every booth in every one of them—it was clear that mobile technology is expanding faster than ever into more new tech territories than ever before.

On the device front, cameras and camera quality have become a pitched battleground, with mobile phone makers teaming with camera manufacturers to give us better and better images and video. This fight is far from over, too, because vendors are exploring many different ways to improve mobile phone camera quality. Quick charging is a hot new trend we can expect to hear more about in the days to come. Of course, apps and their performance continue to matter greatly, because if you can do it from any computer, you better be able to do at least some of it from your phone.

The Internet of Things (IoT) grabbed many headlines, with vendors still selling more dreams than reality, but some industries living this future now. The proliferation of IoT devices will result, of course, in massive increases in the amount of data flowing through the world’s networks, which in turn will require more and more computing power to analyze and use. That power will need to be everywhere, from massive datacenters to the device in your hand, because the more data you have, the more you’ll want to customize it to your particular needs.

Similarly, AI was a major theme of the show, and it’s also likely to suck up computing cycles everywhere. The vast majority of the work will, of course, end up in datacenters, but some processing is likely to be local, particularly in situations, such as real-time translation, where we can’t afford significant comm delays.

5G, the next big step in mobile data speeds, was everywhere, with most companies seeming to agree the new standard was still years away–but also excited about what will be possible. When you can stream 4K movies to your phone wirelessly while simultaneously receiving and customizing analyses of your company’s IoT network, you’re going to need a powerful, sophisticated device running equally powerful and sophisticated apps.

Everywhere I looked, the future was bright—and complicated, and likely to place increasing demands on all of our devices. We’ll need guides as we find our paths through these new territories and as we determine the right device tools for our jobs, so the need for the XPRTs will only increase. I look forward to seeing where we, the BenchmarkXPRT Development Community, take them next.

Mark

Posted in 4K, 5G, AI, Future of performance evaluation, Internet of things, IoT, Mobile data, Mobile devices, Mobile World Congress, Mobile World Congress, Phones, Trade Shows |

Category: AI

Thoughts from MWC Shanghai

Learning about machine learning

Mobile World Congress 2017 and the territories ahead

Check out the other XPRTs: