This is the second in a series of three posts on technologies that are having a profound impact on our mobile future. The first focused on the growth, benefits and challenges of 5G cellular networks. This post looks at the impact of artificial intelligence (AI) on mobile communications and computing.

As with 5G, AI may seem like old news. But the movement of AI from the cloud, where it has traditionally been deployed, to smart devices at the edge of the network will enable critical, time-sensitive decisions to be made faster and more reliably.

A January 27, 2020 article in Forbes, “Why Apple and Microsoft Are Moving AI to the Edge,” states that the computation power of AI algorithms has increased 300,000 times between 2012 and 2019—doubling every three-and-a-half months. The cloud has been a logical place for AI because it provides massively scaled computational power and very cheap memory and storage. But cloud-based AI has its issues, including latency—the delay as data moves to the cloud for processing and the results are transmitted back over the network to a mobile device. The movement of critical, often confidential data back and forth between the cloud and edge devices also poses security issues.

Conversely, on-device AI results in faster performance and response time, lower latency and improved security by retaining data on the device. Shifting AI from the cloud is being enabled by the rapid growth of smart devices at the edge of the network—smartphones, smart watches and sensors placed on machines and infrastructure. Gartner predicts that by 2022, 80 percent of smartphones shipped will have on-device AI capabilities, up from 10 percent in 2017. According to SAR Insight & Consulting, the global number of AI-enabled devices with edge computing will grow at a CAGR of 64.2% from 2019 to 2024.

The previously mentioned Forbes article makes the case that the migration of AI from the cloud to the network edge is a continuation of centralized to decentralized computing that began about 40 years ago with the shift from mainframe to personal computers. The article notes that, as with PCs, not all will be easy at the edge. “There is a limit to the amount of computation power that can be put into a camera, sensor or a smartphone. In addition, many of the devices at the edge of the network are not connected to a power source, which raises issues of battery life.”

In smartphones and smart watches, AI will compete with the CPU/GPU, display and memory storage for battery life. In my previous post, I noted that we’ve benchmarked our Enovix 3D Silicon™ Lithium-ion Battery against the same size conventional lithium-ion battery in a new 5G smartphone, and that our battery increases energy capacity by 51% (6,770 mAh versus 4,200 mAh). We’ve also benchmarked our silicon-anode battery against the same size conventional lithium-ion battery used in a major brand smart watch, where it increases energy capacity by 106% (925 mAh versus 450 mAh).

5G and AI will provide improved performance for mobile communications and computing devices, and we’ll provide batteries with significantly increased energy capacity that will enable users to fully realize the improved performance.