Virtual reality and reality of Virtual devices.
Sitting in front of a flat-screen TV and watching video is going to feel like writing on a typewriter. And while virtual reality has peaked the interest of tech trailblazers, 2016 is the year it is expected to take measurable steps in targeting mainstream consumers.
New virtual-reality headsets are expected from major tech companies Sony, HTC and Oculus. (Facebook acquired the company for $2 billion)
Prices of the immersive headsets are already falling and are expected to fall further, while the device’s usage is broadening beyond the gaming industry.
So far, wearable technology hasn’t received a ton of love from everyday people, but it is expected to become increasingly more common in the workplace.
In 2016, wearable technology could increasingly become part of what your boss issues when you join a new company, particularly for jobs where employees aren’t sitting at desks. For instance, shipping-logistics company DHL reported productivity increased 25 percent when it put smart glasses on its shipping handlers in a pilot program.
the first wearable technology to be adopted in the work environment but other varieties would follow. For example, paramedics, surgeons and other medical professionals who work in a sterile environment could benefit by a device attached to the arm, allowing hands-free communication.
Cell phone is going to get a whole faster.
Most smartphones these days are operating on the 3G or 4G network. But all eyes are on the next generation of cell service, unsurprisingly, called 5G. Once 5G cellphone networks become standard, the network will be 100 times faster than current 4G networks, says Nitin Bhas, the Head of Research at Juniper, in an email to Entrepreneur. Various wireless carriers have begun the process of testing the new 5G network. For exampleHuawei and the research institute TNO announced in August 2015 that they will be testing a 5G network in the Netherlands, while Ericsson and Softbank began field trials and testing of 5G technologies in July 2015 in Tokyo. Even as tech companies set their focus on the 5G network, consumers won’t likely have access to it next year. Verizon has said it is aiming to have 5G commercial services available in 2017.
While the digital cryptocurrency Bitcoin has had its ups and downs in the consumer market, financial institutions are still invested in the the technology behind it — and are looking to use it with different transactions.
“It’s much quicker and potentially much more secure, hence you have a lot of banks thinking, ‘Could we in some way use distributed network, like blockchain, in this way?’” says Holden. What are these new innovations need to state. The next year will see significant momentum in this space.
Called blockchain technology, the innovation is a digital ledger or record of events. The instant, transparent nature of block chain technology makes it ideal for transfer of money across international borders — and this is what has peaked financial institutions’ interest.
Video gaming with cloud-based services.
The most powerful games of 2016 will rely on a combination of console and cloud-based power, says Steffen Sorrell, senior analyst at Juniper Research. Very immersive and powerful games still need the data center provided by a console, and Sorrell doesn’t expect that to change in 2016.
The new hot ticket in town
As if in a final coup de gras in some great revenge of the nerds take down, the newest hot form of entertainment is watching video-game stars play video games. No joke. Crowds of fans could be packed into arenas big enough to rival the largest sports teams or concerts and watch from a super-sized screens videogame professionals play games. And there’s real money on the line for the winners.
Data protection will emerge.
Every time a new home appliance becomes connected to the Internet, a new wearable device starts tracking more of our movements or a social network encourages us to put more of our feelings and vacation pictures online, more data is created. A lot more data. And that also means that parallel security measures will need to expand both in size and sophistication. New software security technologies will depend on identifying abnormalities in network behavior instead of identifying destructive code in software.
‘Cloud native’ shapes the future
Applications built from microservices running in containers have all sorts of advantages over monolithic applications. First and foremost, instead of dealing with obscure internal dependencies that make troubleshooting and updating painful, you can work with decoupled services that are individually monitored and managed.
But micro services architecture adds complications — mainly, swarms of containers to keep track of. And who manages literally billions of containers in production every day? Google, the company that in 2007 contributed the Linux kernel’s c groups container feature on which Docker was later built.
Last year Google introduced the open source Kubernetes project, which distills Google’s container management system into open source bits so mere mortals can wrangle clusters of containers at scale. This summer the project’s founder, Craig McLuckie, announced the formation of the CNCF (Cloud Native Computing Foundation), which will take Kubernetes as a starting point to build out an ecosystem for container scheduling, management, and orchestration. Watch this space carefully.
Spark ‘streaming’ accelerates
A funny thing happened to big data in 2015: Spark elbowed Hadoop out of the spotlight. Why? Because rather than processing data in big batches across many disks, as Hadoop does, Spark works its magic with small batches in big memory — close enough to real time to be indistinguishable from streaming. (Storm, a true streaming solution, has already fallen out of favor.)
Cloudera and IBM have gone all-in with Spark, while Amazon, Google, and Microsoft offer Spark as a service in their public clouds. But Spark still has major annoyances relating to memory management and resiliency, among other drawbacks. With this kind of momentum, though, you can expect many such problems to be addressed in the coming year.
Developers tap into machine learning
Not only do all the major clouds now offer analytics as a service, but they also provide machine learning APIs in the cloud; plus, open source machine learning tools abound. Ubiquitous machine learning capability enables developers to build applications that recognize patterns in gobs of data — for fraud detection, face recognition, medical diagnoses, infrastructure optimization, Web ad-serving, you name it.
Of course, some commercial software and websites have had machine learning features for years (for anticipating user actions, recommending related products, and so on). The difference today is that machine learning is broken out as a separate capability any developer can exploit, and we now have tons of data and cloud computing capacity to throw at it, including fancy new servers equipped with GPU accelerators to run machine learning algorithms.