In the two previous articles in this series, I’ve taken a look at short-term trends regarding design tools, and explained how I look for what’s next in IT. In the third and final part, I want to share my current observations about the next big wave of innovation.
I use the ideas of “stacks” as my metaphor to understand how specific technologies interact to create new rounds of innovation. I see a new stack coming together that will drive innovative new applications in a variety of fields. The current innovation stack — CAMS — has four “big idea” technologies (cloud, analytics, mobile, social); this new one has five: real-time processing, operational trust, autonomy, distributed processing, and intelligence. The initials seems to be a good title (ROADI), since the poster child for this next wave of innovation is the self-driving car. ROADI will turn product and services into autonomous discrete agents.
Self-driving cars must possess intelligent and autonomous behavior. They must always respond in real-time to the environment. Their actions are based on a refined notion of trusted operational behavior. The necessary computation and connectivity can’t be centralized in a server or even a cloud; it must take place in each vehicle and in every other object on or near the road.
Assembling the ROADI Stack
There are several innovations behind the emerging ROADI Stack:
Graphics Processing Units
Graphics Processing Units (GPUs) are no longer just for graphics. Better known as GPGPUs (General Purpose GPUs), they are faster than CPUs at processing constant multiple data streams.
The Internet of Things
The Internet of Things and the Industrial IoT (IIoT) describe a variety of interconnected technologies, including distributed computation applications known as Edge Computing, Fog Computing, the more established Cloud Computing, and such emerging technologies as microscopic CPUs. As the tools mature, IoT/IIOT devices will exhibit autonomous and decentralized behavior, interacting with each other without the need for centralized control.
Deep Learning
Deep Learning has changed how we use so-called Big Data. It allows the emergence of behavior we describe as intelligent, providing millions of autonomous devices with the logic they need to operate in the real world in real time.
Blockchain
Blockchain technology will provide new elements crucial to autonomous distributed intelligence, the disintermediation of trust and an open ledger of transactions. An autonomous distributed technology needs the ability to be trusted without the intervention of an intermediary service or human. Blockchain tech uses a cryptographic ledger to bring immutable proof and automated smart contracts into the stack. For example: if a self-driving car is in an accident, a blockchain-based smart contract could be automatically triggered, relationally binding it to any other smart objects involved in the accident and the physical jurisdiction. The complete recent record of the car’s behavior will become part of the public record on the blockchain ledger, making it easier to assign responsibility for an accident.
Display Technologies
Immersive and Interactive display technologies such as augmented reality, machine vision, and heads-up displays will provide a conduit to human interaction with ROADI technologies.
Eleven years after the launch of the iPhone, we are still trying to understand smartphone influences on behavior. When smart connected products become ROADI products, there are new considerations. Can robots witness a crime? Can a smart factory order supplies without human intervention? Will immutable records stand up in court? How industry responds to these social meta-specifications will likely prove to be the biggest hurdle or the biggest asset in the development of ROADI products and services.
Randall S. Newton is Managing Director of Consilia Vektor, a technology analysis and marketing advisory service specializing in product development, construction technology, and distributed ledger (cryptocurrency) applications.
