Enabling intelligence for the next generation of technology demands an overhaul of existing IT infrastructures, with a balance of cloud and edge computing, and a renewed focused on hardware acceleration to deliver intelligence everywhere.
Companies are basing their future growth strategies on New IT systems--artificial intelligence, connected devices, robotics, extended reality (XR) and more. Yet today’s enterprise infrastructures cannot support the demand for immediate response times in physical-world applications, nor the instant insights and actions distributed systems need to create intelligent solutions at scale.
And when I say immediate, I mean it. Years ago, a friend of mine had a medical condition that caused seizures. They would come out of nowhere and without proper care, could be life-threatening. Today, the risks from seizures are much less, thanks to NeuroPace—a device implanted in a patient’s head that can detect the onset of a seizure and send electrical pulses to stop the seizure immediately. It doesn’t need to send data back to the cloud for analysis or even be connected to a mobile phone. The device, acting autonomously, has reduced seizures in patients by 44 percent after the first year.
As more objects and devices like the NeuroPace become “smart” (i.e., home appliances, driverless cars and sensor-based robots), this intelligence is creating vast swathes of data. Current predictions suggest that by 2020, smart sensors and other Internet of Things (IoT) architecture devices will generate at least 507.5 zettabytes of data.
To keep up with the crush of information, and allow devices to make decisions in real-time, businesses will have to focus making edge networks fast and powerful enough to process analytics on actual devices and deliver real-time actions. This is the premise of our Internet of Thinking chapter in the Accenture Technology Vision 2018, our annual tech trend report.
Using the “edge” as an asset
In most cases, current enterprise infrastructures are designed around a few basic assumptions: enough bandwidth to support any remote application, an abundance of compute in a remote cloud, and nearly infinite storage. These assumptions are no longer adequate.
Delivering intelligent environments in the physical world requires rethinking current IT infrastructures, leveraging an expanded network of devices and updated methodologies. To fully enable real-time intelligence, businesses must shift event-driven analysis and decision processing closer to points of interaction and data generation.
We call this the Internet of Thinking, and this distributed computing will power a range of future applications, including autonomous vehicles that make their own rapid decisions, automated fluid management in hospitals, self-maintaining industrial equipment, conscious surveillance cameras with on-board analytics and smart trains that allow for "real-time" seat booking.
Cloud technologies will still play a critical part, but will evolve into a coordination between the two. Companies will balance edge devices that take instant action with cloud to improve the algorithms that govern them, analyze information and deliver meta-insights.
As companies push enterprise endpoints further outside the controlled environments they’re used to managing, they will also need to deliver sufficient computing power where intelligent environments need it. This means a renewed focus on hardware accelerators to circumvent latency and compute limitations. Adding hardware acceleration
Special purpose graphics processing units (GPUs), field (re)programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs) are all options to deliver the power and energy efficiency for real-time decision-making at the point of interaction. Highly demanding environments may even require custom hardware.
Time to get started
To drive tomorrow’s revolutionary technologies to their full potential, companies must begin today: rethinking their approach to service design and technology ecosystems, balancing cloud-first with edge-smart, and adding the right combination of intelligent hardware to deliver specific use cases in the physical world.
Those that extend their intelligent infrastructures to the edge and effectively manage real-time decision-making will have unprecedented opportunities to deliver new products and services to people—in their cars, homes, workplaces and society overall.
Does your existing IT infrastructure support real-time action in dynamic environments? What kind of hardware do you need to deliver intelligence everywhere?
To learn more about this IT trend, I encourage you to:
Read the Accenture Technology Vision 2018 overview and trend highlights
View the essential slide shares, videos and infographics
Share your thoughts at #techvision2018
Reach out to us to put these innovation-led ideas to work in your enterprise.