Chris Dixon wrote a great post discussing what’s next in the computing industry. Historically, there’s been a major new tech cycle every 10 to 15 years that brings along a new era of computing: we saw this with personal computers in the 80s, the Internet in the 90s, and now with the smartphone era.
If this 10-15 year pattern continues, it means we should be entering the growth phase of the next big era in just a few years. It also means that we should already be in the early stages of that next big era. The question is: what is it? What’s the next big computing platform?
In my opinion, there are five key trends shaping the computing industry today (and Chris touched on the first three):
1. Computing everywhere:
In the semiconductor industry, we’ve seen chips get progressively faster and cheaper (Moore’s law) for the past five decades. Plus, as Chris points out, we’re moving more toward systems-on-a-chip architectures which drop the price of a computing system from $100 to $10. You can buy a Raspberry Pi Zero for five dollars. The end result is that it’s now cost effective to put a computer in virtually anything. With smartphones, wearables, tablets, drones, kiosks, IoT, etc., computing is taking place, non-stop, all around us.
2. Cheaper data gathering & storage at scale:
Now that computing endpoints are everywhere and anywhere, it’s cheaper than ever to gather data. For example, there are sensors in your phone and smartwatch; sensors on industrial equipment in a manufacturing plant, on a warehouse shelf in a distribution center or your refrigerator at home. Drones can cheaply gather large amounts of data. All of this means that there’s widespread availability of large data sets that can be stored inexpensively through cloud storage providers.
3. Better insights through AI:
We have seen incredible progress in AI over the past years, especially through the application of deep learning algorithms. Those AI systems will get even better as more data is collected, so cheaper data gathering should lead to better, smarter, and more useful AI products.
4. Innovation in the user interface through voice:
Better interfaces drive more effortless experiences for users. We’re already seeing the rise of conversational design beyond messaging apps and into the products and apps we use every day. With conversational UI, we don’t just chat with other people, but with services as well.
Speech, like we’re beginning to see with Amazon Echo, is the ultimate conversational interface. Asking a question aloud requires much less cognitive load and lets you do something else at the same time (as opposed to typing on the computer). In addition, products with speech-based interfaces can be scaled down to much smaller and cheaper form factors than products that require displays and keypads. New user interfaces will dramatically reduce the friction to access data and insights.
5. Rise of connected services:
Microservices represent the next big leap in the API economy. Instead of dealing with a single API or technology stack, an app now is made up of many fine-grained services (each with its own tech stack), enabling dev teams to decouple services and update/deploy faster. In this way, computer services are performing more and more specialized roles, just as humans are too.
The big question is what does all this mean in terms of the next computing platform? In a follow up to Chris Dixon’s post, Fred Wilson wrote:
“…I wonder if there is something more fundamental in the combination of ubiquitous computing and artificial intelligence that would be the next big computing platform. We are due for one soon… What is the dos/windows, Netscape, and iOS of this coming era? If we can figure that out, then we are onto something.”
Over the past few months, I have grown to believe that one of the large cloud platforms – AWS, Google, MS Azure – can grow into this next computing platform. And, AWS is the most likely candidate given its scale and mindshare among developers.
AWS is still considered pretty low level, mainly offering on-demand computing capacity and storage. But, to its advantage, AWS (unknowingly) did the right thing by first building an infrastructure as a service business and not starting with a platform-style set of services like Google’s App Engine. It’s much easier to build on AWS’ fundamentals rather than having to do it the other way around: Compute Engine was pretty late to the party.
AWS has been adding more and more intelligent building blocks over time, climbing up the stack with services that abstract the underlying infrastructure and help with specific tasks in the value chain. Lambda, API Gateway, and Amazon Machine Learning are great examples of this.
But, for AWS to become THE computing platform of the AI age, two things will need to happen:
- AWS will need to keep moving up the stack towards the intelligence layer (ML, AI)
- AWS needs to spawn an even broader ecosystem of apps on top of it (beyond the current AWS marketplace)
If AWS can do these two things, it might be in the best position to become the OS of the next big computing cycle.