From automobiles, drones, and manufacturing robots to solar inverters and wind turbines, the number of endpoints is quickly increasing — and the data-intensity of these assets is growing exponentially². While this trend is not new, recent advances in computing are augmenting how that data can be turned to valuable insights and actions.
1. Accelerated improvements in computing power, power usage effectiveness³ and data center energy consumption, both in hyper-scale and micro-scale closer to the source
2. Novel communication technologies that provide low latency, high bandwidth & secure networks for real-time & computationally intensive operation of distributed assets
3. Increase in computing and analytics performed at the “edge”; that is, on the asset / sensor itself
Together, these developments can be particularly important for energy & industrial companies digitizing their operations.
A few seconds can mean a world of difference when managing power equipment or controlling autonomous vehicles.
We believe this transition to “edge computing” is necessary to enable use cases that demand real-time action, especially in industries requiring constant up-time.
energy, manufacturing, telecommunication,& transportation companies.
These sectors require low latency, high security & control, and often manage remote assets with limited bandwidth. The windiest areas in the United States are in remote areas of the Midwest, where wind farms grapple with poor network access (forget 5G, even 3G access can be a challenge).
Processing critical operational analyses at the edge effectively makes big data smaller, lowering a network’s storage and bandwidth requirements. A more distributed & networked system residing close to or on operational assets also limits single point of failure risks. Some assets may even analyze and operationalize data, while limiting cloud communications to critical information. As autonomous vehicle technology evolves, analytical processing and decision-making will likely reside in the AV itself — with remote telemetry limited to failure-mode data and periodic backhaul of historical operations.
Importantly, corporations are investing to digitize and secure a large and growing number of distributed assets. Nearly 80 million or more than half of all utility customers in the U.S. have smart meters, and nearly 20 million homes have smart thermostats⁴.
how will companies collect, analyze, and operationalize that distributed intelligence?
The transition from central to decentralized (echoing the journey from mainframe to personal computers, to client-server, to cloud) is clearly cyclical, and we believe it will be gradual. On this journey, we are most excited about companies building digital solutions in the Computation layer, the Communications layer, and the Control layer.
 Source: Statista, using estimates as of 2016
 Source: IDC predicts a 10x increase in annual data generation by 2025, to 163 zettabytes per year
 Power usage effectiveness (PUE) is a ratio that describes how efficiently a computer data center uses energy
 Source: EIA