Arm Holdings is positioning itself at the center of AI transformation. In a wide-ranging podcast interview, Vince Jesaitis, Arm’s head of global government affairs, challenged company decision-makers to consider the company’s international strategy, how the company sees the evolution of AI and the future of the industry.
From cloud to edge
Arm believes the AI market is entering a new phase, moving from cloud-based processing to edge computing. While much of the media attention has so far focused on large data centers where models are trained and accessed from the cloud, Jesaitis said most AI computing, especially inference tasks, is likely to become increasingly distributed.
“The next ‘aha’ moment in AI will be when local AI processing occurs on devices that were previously unimaginable,” Jesaitis said. These devices range from smartphones and earphones to automotive and industrial sensors. Arm’s IP is literally already embedded in these devices. Arm is the company that, in the past year alone, has been the IP behind more than 30 billion chips placed in every conceivable type of device around the world.
There are several benefits to bringing AI to the edge environment, and the team at Arm cites three main “advantages.” First, the inherent efficiency of low-power Arm chips means lower power bills to run and cool your compute. This minimizes the environmental footprint of the technology.
Second, placing the AI in a local setting results in significantly lower latency (latency is determined by the distance between the local operation and the site of the AI model). Arm points to applications such as features such as instant conversion, dynamic scheduling of control systems, and near-instant triggering of safety functions (for example, in IIoT configurations).
Third, “keep it local” means sensitive data is never sent outside the company. While the benefits are clear for any organization in a highly regulated industry, the increasing number of data breaches means that even companies operating with relatively secure data sets are looking to reduce their attack surface.
Arm silicon is optimized for power-constrained devices and suitable for the computing needs on the ground, the company said. In the future, AI may be embedded throughout the environment, rather than being concentrated in data centers operated by large providers.
military and world government
Arm sees this level of engagement as an important part of its role and actively engages with policymakers around the world. As governments continue to compete to attract semiconductor investment, issues of supply chains and centralized dependence are still fresh in the minds of many policymakers from the time of the COVID-19 outbreak.
It lobbies for workforce development and is currently working with White House policymakers on an education coalition to build an “AI-enabled workforce.” National independence in technology depends as much on the capabilities of the workforce as on the availability of hardware.
Mr Jesaitis pointed out the differences between the regulatory environments. The US is prioritizing what local governments call acceleration and innovation, while the EU is leading on safety, privacy, security, and legally enforced standards of practice. Arm aims to find a middle ground between these approaches and further advance the AI industry while building products that meet stringent global compliance needs.
The enterprise case for edge AI
The case for integrating Arm’s edge-focused AI architecture into enterprise transformation strategies is compelling. The company emphasizes its ability to deliver scalable AI without having to centralize it in the cloud, and is also pushing for investments in hardware-level security. This means you can avoid issues such as memory abuse (which is outside the control of users connected to a centralized AI model).
Of course, sectors that are already highly regulated in terms of data practices are unlikely to see relaxed governance in the future, and vice versa is almost inevitable. Over the next few years, we will see stricter regulations across all industries, as well as stiffer penalties for non-compliance. However, to balance that out, companies that can demonstrate the inherent safety and security of their systems will have a significant competitive advantage. It is in this regulatory landscape that Arm is considering adapting its own and local edge AI.
Additionally, ESG goals will become increasingly important in Europe and Scandinavia. This is where the power dissipation nature of the Arm chip provides a huge advantage. This is a trend that even US hyperscalers are responding to. AWS’ latest SHALAR series of low-cost, low-power Arm-based platforms exists to meet just that demand.
Arm is working with cloud hyperscalers like AWS and Microsoft to produce chips that combine efficiency with the horsepower needed for AI applications, the company said.
What’s next for Arm and the industry?
Jesaitis pointed to several trends that companies may see over the next 12 to 18 months. Global AI exports, particularly from the United States and the Middle East, ensure that large providers can meet local demand for AI. Arm is a company that can supply both major providers in these situations (as part of its product portfolio) and meet the growing demand for edge-based AI.
Jesaitis also sees edge AI as something of a sustainability hero in an industry increasingly criticized for its environmental impact. Arm technology’s biggest market is in low-power computing for mobile, making it inherently “green.” Businesses want to meet their energy goals without sacrificing compute, and Arm offers a way to combine performance and responsibility.
Redefining “smart”
Arm’s vision for edge AI means that computers and the software running on them are context-aware, cheap to run, secure by design, and highly responsive thanks to near-zero network latency. “We used to call things ‘smart’ because they were online, but now they’re going to be really intelligent,” Jesaitis said.
(Image source: “Factory Floor” by danielfoster437 is licensed under CC BY-NC-SA 2.0.)
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