The only thing that flies faster than time is the progress of technology. Once after lunch, a chip-designing friend excused himself quickly with the deft explanation that Moore’s Law meant that he had to make his chip set 0.67 percent faster each week, even while on vacation. If he didn’t, the chips wouldn’t double in speed every two years.
Now that 2017 is here, it’s time to take stock of the technological changes ahead, if only to help you know where to place your bets in building programming skills for the future.
From the increasing security headache of the internet of things to machine learning everywhere, the future of programming keeps getting harder to predict.
The cloud will defeat Moore’s Law
There are naysayers who claim the chip companies have hit a wall. They’re no longer doubling chip speed every two years as they did during the halcyon years of the ’80s and ’90s. Perhaps -- but it doesn’t matter anymore because the boundaries between chips are less defined than ever.
In the past, the speed of the CPU in the box on your desk mattered because, well, you could only go as fast as the silicon hamster inside could spin its wheel. Buying a bigger, faster hamster every few years doubled your productivity, too.
But now the CPU on your desk barely displays information on the screen. Most of the work is done in the cloud where it’s not clear how many hamsters are working on your job. When you search Google, their massive cloud could devote 10, 20, even 1,000 hamsters to finding the right answer for you.
The challenge for programmers is finding clever ways to elastically deploy just enough computing power to each user’s problem so that the solution comes fast enough and the user doesn’t get bored and wander off to a competitor’s site. There’s plenty of power available. The cloud companies will let you handle the crush of users, but you have to find algorithms that work easily in parallel, then arrange for the servers to work in synchrony.
IoT security will only get scarier
The Mirai botnet that unfolded in this past fall was a wake-up call for programmers who are creating the next generation of the internet of things. These clever little devices can be infected like any other computer, and they can use their internet connection to wreak havoc and let slip the dogs of war. And as everyone knows, dogs can pretend to be anyone on the internet.
The trouble is that the current supply chain for gadgets doesn’t have any mechanism for fixing software. The lifecycle of a gadget usually begins with a long trip from a manufacturing plant to a warehouse and finally to the user. It’s not usual for up to 10 months to unfold between assembly and first use. The gadgets are shipped halfway around the world over those long, lingering months. They sit in boxes waiting in shipping containers. Then they sit on pallets at big box stores or in warehouses. By the time they’re unpacked, anything could have happened to them.
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