The candy style mobile phones haven’t seen any upgrade in many years, and I don’t expect it to change substantially. Erstwhile Nokia used to innovate with different styles, hardware price points and some genuinely inspired designs that made it worthwhile. However, the price of failure is substantial. Mobile phone launches come a dime a dozen, and the hype cycle continues throughout the year.
I’d be expecting to see the innovations in cameras; especially post-processing algorithms. Most decent smartphones have a dedicated onboard GPU’s that makes it possible to improve image processing.
Hence, the influx of the Augmented Reality that would slowly percolate in the consumer space. It has a considerable import for the hospitals; especially to guide patients and improve efficiency. However, I doubt if the AR API’s (or anything equivalent) will be open for the developers. We will see exciting shifts in the ensuing year.
I am on the fence here. Despite the hoopla of the internet of things, I think it is yet another way to jack up prices at the cost of the inefficiency of transmission of data. Remote Surgery, for example, is an exciting concept, but if things go south, they would be scrambling for answers.
Graphical Processing Units (GPU):
I am excited about this one. GPU’s have different instruction sets compared to the main chip that makes it viable to do intensive computing. GPU’s gained prominence due to bitcoins and blockchains, but for general-purpose computing, it would now be more comfortable and faster to do the intensive physics calculations. I heard about the new Tomotherapy planning system that uses the GPU’s heavily. However, cloud computing will also slowly percolate in the departments. I had made an internal presentation in 2015 wherein, I had predicted about the likes of Amazon Web Services that would trump all other offerings. I am betting heavily on AWS, and it would help to familiarise with the enterprise offerings too!
Most of the commercial systems are bloated- phones, computers etc. Embedded systems with microkernels are required in “in-time” computing paradigms. I still remain a massive fan of microkernel architecture because it doesn’t require extensive maintenance at the OS level. However, after the demise of BlackBerry 10, the last mainstream kernel- QNX, also died a slow haemorrhaging death and away from the consciousness. Its the start of a new decade and we are carrying around the inefficiencies of the decade gone by.
This sums up the broad trends. Innovation happens “on the edges” instead of the “core”. Therefore, keep an eye on the outliers. If you’d notice, I haven’t mentioned anything about the AI/ML which, still requires a lot of real-life validation. I’ll keep a watch on it, for sure!
(All images are respective copyright of their owners. These popped up in the image searches and are for demonstration alone).