CES 2016: 2-in-1s, Virtual Reality and Machine Learning Among Key Trends
The Consumer Electronics Show under way in Las Vegas is monstrously large and will likely attract 150,000 to 170,000 attendees, according to The Wall Street Journal. Cavernous halls at the Las Vegas Convention Center are filled to the rafters with booths from major technology companies hawking everything from 4K TVs to new smartphones, drones and wearable devices.
Yet a few days into the conference, some clear themes are starting to appear amid the numerous announcements coming out of the confab. These could have far-reaching implications for the business technology market, though some may not be fully felt until the years ahead.
Here is a rundown of some of the key themes from CES 2016:
2-in-1s Are Evolving
OEMs including HP, Lenovo and Toshiba have announced new takes on the two-in-one device category. The new offerings represent evolutionary approaches to the devices, with glitzier and speedier specifications and new features. All serve as showcases for Microsoft’s Windows 10 platform.
For example, Lenovo’s new ultralight ThinkPad X1 tablet comes with an optional magnetic ThinkPad keyboard and comes with a superfast LTE Advanced modem that supports up to 300 megabit-per-second download speeds. HP upgraded its Spectre x360 convertible device to a 15.6-inch model that sports an optional 4K display. And Toshiba’s dynaPad 12-inch tablet comes with an optional magnetic full keyboard that transforms it into a clamshell notebook.
Some of the potential enterprise benefits of these gadgets are obvious. For example, the dynaPad also includes updated versions of Toshiba’s suite of business applications that let users collect, organize and share notes, images and files, and integrate them with Microsoft Office.
Analysts say that other advantages are less noticeable but could have long-term benefits. For example, the flexibility and mobility two-in-ones afford could appeal to millennial workers who expect that functionality. Additionally, devices with powerful, built-in wireless capabilities could enable mobile workforce deployments and applications. They also will give workers greater access to cloud-based servers and applications.
Virtual Reality Is Here, But Its Impact Will Be Limited
Virtual reality headsets have been on the radar for several years now. However, in 2016 several of the major vendors will finally release commercial products. While business applications for such platforms are likely far off, the potential for enterprise applications does exist.
Oculus, a division of Facebook, announced that its Rift VR headset is now available to pre-order for $599 and will ship to 20 countries starting March 28. According to Ars Technica, within an hour of pre-orders becoming available, the expected ship date was pushed back to May, suggesting “some combination of either limited initial supplies or very robust sales for the Rift.”
Meanwhile, HTC announced the Vive Pre, a new iteration of its VR headset that developers will be able to access ahead of the expected consumer launch of the Vive in April. As The Verge notes, the Vive Pre has one major hardware improvement, which is a front-facing camera that can bring VR headset users back into the real world if they venture beyond the headset’s virtual tracking field.
Most of the initial applications for VR headsets are expected to be for gaming and entertainment. However, several plausible business applications include training, computer-aided design in manufacturing, and enterprise communication, according to a report last year from the Tuck School of Business at Dartmouth College.
Don’t expect to see VR take off anytime soon though, at least according to graphics-chip maker Nvidia. According to Bloomberg, the company estimates that this year just 13 million PCs — less than 1 percent of the 1.43 billion PCs research firm Gartner expects to be in use globally in 2016 — will have the graphics capabilities needed to run VR.
Machine Learning Gets a Boost
Another topic that has come up quite a bit is machine learning, or the idea that an artificial intelligence can learn from and make predictions based upon data it accesses. Nvidia announced a new “supercomputer” for cars, the Drive PX2, that takes advantage of a “deep neural network” that trains cars to “detect objects, identify them, determine where the car is relative to the world around it, and then calculate its optimal path for safe travel.”
Silicon giant Qualcomm announced a similar initiative with its Snapdragon 820A chipset family, which takes advantage of “machine intelligence” for the same kind of advanced driver assistance systems, as well as in-vehicle infotainment scenarios. And Toyota is launching a five-year $1 billion research institute that will study machine learning as part of an effort to create a car that is incapable of crashing.
As TechCrunch pointed out last year, the potential uses for machine learning in enterprise software are seemingly limitless. Companies may one day use the technology to mine internal and external databases to find patterns and provide insights and predictions. Machine learning could have a large impact on sales, marketing, human resources and finance departments, the report notes.
