For this year's report, I took a stab at learning all the CSS/JS that I've always wanted to know, and then went after the task of making a fully responsive report. I've succeeded in doing so, and so this PDF version isn't as good as the real thing. In the next few days I will be sharing a link to the real digital experience. But for now -- enjoy this static version of the report which has a few parts that couldn't render to static form. Because ... this year's report is truly computationally designed and therefore needs to be expressed appropriately (smile). Expect a video version on my new YouTube channel "John Maeda is Learning." What can I do about it? As the marginal return on computing power (a la Moore's law) diminishes and technology is less of a differentiating factor, the value of design has entered the foreground. Five (20%) of the top cumulative-funded VC- backed ventures that have raised additional capital since 2013 are noted to have designer co-founders.

Imagine if the things around your house could respond to your voice even when you were shouting over a smoke alarm, keep track of each individual wandering through the house, unlock your front door just by identifying your voice, and even identify your emotions. Those are all capabilities that Microsoft is preparing to add to its Project Oxford, a set of cloud-based machine learning services introduced last May at Microsoft's Build conference. Ars took a deep dive on Project Oxford's first wave of machine learning-based services last year. Those services performed a number of image processing and recognition tasks, offered text-to-speech and speech recognition services, and even converted natural language into intent-based commands for applications. The services are the same technology used in Microsoft's Cortana personal assistant and the Skype Translator service, which translates voice calls in six languages (and text messages in 50 languages) in real-time.

That means future head-mounted displays (HMDs) based on Qualcomm's standalone headset kit will feature more efficient foveated rendering. Since they can tell where you're looking, they'll be able to dedicate most of their graphics power to make that part of the experience as sharp and clear as possible. They can even downgrade graphics on parts of the screen you're not looking at, which could lead to systems with lower specs and lower price tags. Eye tracking will also make experiences more personal and interactive. Avatars and in-game characters could look at you when you look at them, which could make interactions in VR social networks much more enjoyable.

Yeah, it's only March, but phone season has begun for 2018. Dozens of new handsets were unveiled at Mobile World Congress, the largest smartphone show on Earth, (here are the highlights) and Samsung's Galaxy S9 is already on its way to early birds. Also, Google is now circulating a developer preview of the next Android version, currently codenamed Android P. With all this action, we're beginning to get a picture of what smartphones in 2018 will look like. Here are some of the more interesting trends you may see on your next phone. It's been years since smartphones didn't all look mostly the same.

The British chip design firm ARM came up with the processors used in virtually all the world's smartphones. Now it plans to add the hardware that will let them run artificial-intelligence algorithms, too. ARM announced today that it has created its first dedicated machine-learning chips, which are meant for use in mobile and smart-home devices. The company says it's sharing the plans with its hardware partners, including smartphone chipmaker Qualcomm, and expects to see devices packing the hardware by early 2019. Currently, most small or portable devices that use machine learning lack the horsepower to run AI algorithms, so they enlist the help of big servers in the cloud.

Customer churn is a problem that all companies need to monitor, especially those that depend on subscription-based revenue streams. The simple fact is that most organizations have data that can be used to target these individuals and to understand the key drivers of churn, and we now have Keras for Deep Learning available in R (Yes, in R!!), which predicted customer churn with 82% accuracy. We're super excited for this article because we are using the new keras package to produce an Artificial Neural Network (ANN) model on the IBM Watson Telco Customer Churn Data Set! As for most business problems, it's equally important to explain what features drive the model, which is why we'll use the lime package for explainability. In addition, we use three new packages to assist with Machine Learning (ML): recipes for preprocessing, rsample for sampling data and yardstick for model metrics. These are relatively new additions to CRAN developed by Max Kuhn at RStudio (creator of the caret package). It seems that R is quickly developing ML tools that rival Python. Good news if you're interested in applying Deep Learning in R! We are so let's get going!! Customer churn refers to the situation when a customer ends their relationship with a company, and it's a costly problem. Customers are the fuel that powers a business. Further, it's much more difficult and costly to gain new customers than it is to retain existing customers. As a result, organizations need to focus on reducing customer churn. The good news is that machine learning can help. For many businesses that offer subscription based services, it's critical to both predict customer churn and explain what features relate to customer churn.

Every time there is a big wireless, telecom or technology trade show, the big question I am always asked by the media as a telecom and wireless analyst, is simple. What was the key message or take away from the show? Last week, at the world's largest wireless trade show, Mobile World Congress 2018 in Barcelona, Spain, the answer was clear. First it is about 5G, with plenty of AI and IoT mixed in. Yes, our world is rapidly changing. So, what will 5G, AI and IoT do for us?

Ed Baig reviews the Samsung Galaxy S9 (S9), from super slow-mo to AR Emojis. Samsung Galaxy S9 comes in three colors in the U.S. This one is lilac purple. When Samsung unleashed the Galaxy S4 smartphone in 2013, it piled on so many newfeatures, I joked that it was like Samsung was auditioning for a Las Vegas magic act. Fast-forward five years to the Galaxy S9 and S9 that I've been checking out for a week and a half, and it's comforting that Samsung no longer goes hog wild with parlor tricks, unless you want to count super slo-mo video or animated emojis.

Samsung's Galaxy S9 is a strange breed of smartphone. With a Snapdragon 845 processor, great camera, and 18:9 screen, it has all the trappings of a fantastic 2018 handset. Yet, at the same time, it's remarkably similar to the Galaxy S8 that it replaces. In fact, it's so much like its predecessor, issues we might normally overlook become all the more obvious this second time around. Samsung's hook with the Galaxy S9 is a "reimagined" camera, but the camera's new features--namely Dual Aperture, Super Slow-mo, and AR Emoji--are equal parts gimmick and catch-up to competing models. And because Samsung is limiting the dual camera and Live Portrait mode to the larger Plus model, the S9 (the phone I'm reviewing here) feels less like a new phone than a mid-cycle refresh.

Smart 5G systems will enable a range of emerging technologies that have the potential to improve lives at a pace and scale not seen before. And machine learning holds great promise to optimize 5G and future networks. This will affect ITU's standardization work in fields such as coding algorithms; data collection, storage and management; and network management and orchestration – raising a host of important questions such as: These questions will be central to ITU's 10th annual Kaleidoscope academic conference from 26-28 November in Sante Fe, Argentina. "Kaleidoscope 2018: Machine learning for a 5G future" is the tenth in a series of peer-reviewed academic conferences organized by ITU to bring together a wide range of views from universities, industry and research institutions. The aim of the Kaleidoscope conferences is to identify emerging developments in information and communication technologies (ICTs) and, in particular, areas in need of international standards to aid the healthy development of the Information Society.