Tag Archives: MobileXPRT

Gearing up for a busy year ahead

on January 4, 2018

We hope everyone’s 2018 kicked off on a happy note, and you’re starting the year rested, refreshed, and inspired. Here at the XPRTs, we already have a busy slate of activity lined up, and we want to share a quick preview of what community members can expect in the coming months.

Next week, I’ll be travelling to CES 2018 in Las Vegas. CES provides us with a great opportunity to survey emerging tech and industry trends, and I look forward to sharing my thoughts and impressions from the show. If you’re attending this year, and would like to meet and discuss any aspect of the XPRTs, let me know.

There’s also more WebXPRT news to come. We’re working on several new features for the WebXPRT Processor Comparison Chart that we think will prove to be useful, and we hope to take the updated chart live very soon. We’re also getting closer to the much-anticipated WebXPRT 3 general release! If you’ve been testing the WebXPRT 3 Community Preview, be sure to send in your feedback soon.

Work on the next version of HDXPRT is progressing as well, and we’ll share more details about UI and workload updates as we get closer to a community preview build.

Last but not least, we’re considering the prospect of updating TouchXPRT and MobileXPRT later in the year. We look forward to working with the community on improved versions of each of those benchmarks.

Justin

Posted in Uncategorized | Also tagged CES, HDXPRT, TouchXPRT, WebXPRT

Keeping up with the latest Android news

By Justin Greene

on September 7, 2017

Ars Technica recently published a deep-dive review of Android 8.0 (Oreo) that contains several interesting tidbits about what the author called “Android’s biggest re-architecture, ever.” After reading the details, it’s hard to argue with that assessment.

The article’s thorough analysis includes a list of the changes Oreo is bringing to the UI, notification settings, locations service settings, and more. In addition to the types of updates that we usually see, a few key points stand out.

Project Treble, a complete reworking of Android’s foundational structure intended to increase the speed and efficiency of update delivery
A serious commitment to eliminating silent background services, giving users more control over their phone’s resources, and potentially enabling significant gains in battery life
Increased machine learning/neural network integration for text selection and recognition
A potential neural network API that allows third-party plugins
Android Go, a scaled-down version of Android tuned for budget phones in developing markets

There’s too much information about each of the points to discuss here, but I encourage anyone interested in Android development to check out the article. Just be warned that when they say “thorough,” they mean it, so it’s not exactly a quick read.

Right now, Oreo is available on only the Google Pixel and Pixel XL phones, and will not likely be available to most users until sometime next year. Even though widespread adoption is a way off, the sheer scale of the expected changes requires us to adopt a long-term development perspective.

We’ll continue to track developments in the Android world and keep the community informed about any impact that those changes may have on MobileXPRT and BatteryXPRT. If you have any questions or suggestions for future XPRT/Android applications, let us know!

Justin

Posted in Android, Android O, Battery life, Google, Machine learning, Mobile devices, MobileXPRT, Open Source, Phones | Also tagged Android, BatteryXPRT, Oreo

Machine learning everywhere!

By Bill Catchings

on August 10, 2017

I usually think of machine learning as an emerging technology that will have a big impact on our lives in the not too distant future through applications like autonomous driving. Everywhere I look, however, I see areas where machine learning will affect our lives much sooner in a myriad of smaller ways.

A recent article in Wired described one such example. It told about the work some MIT and Google researchers have done using machine learning to retouch photos. I would do this by using a photo editing program to do something like adjust the color saturation of a whole photo. Instead, their algorithm applies different filters to different parts of a photo. So, faces in the foreground might get different treatment than the sunset in the background.

The researchers train the neural network using professionally retouched photos. I love the idea of a program that automatically improves the look of my less-than-professional personal photos.

What I found more exciting, however, is that the researchers could make their software efficient enough to run on a smartphone in a fraction of a second. That makes it significantly more useful.

This technology is not yet available, but it seems like something that could show up in existing photo or camera apps before long. I hope to see it soon on a smartphone in my hand!

All of that made me think about how we might incorporate such an algorithm in the XPRTs. When I started reading the article, I was thinking it might fit well in our upcoming machine-learning XPRT. By the time I finished it, however, I realized it might belong in a future version of one of the other XPRTs, like MobileXPRT. What do you think?

Bill

Posted in Google, Machine learning, MobileXPRT | Also tagged Google, machine learning, MLXPRT

Tag Archives: MobileXPRT

Gearing up for a busy year ahead

Keeping up with the latest Android news

Machine learning everywhere!

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