Tirias Research believes that by 2025, 95 percent of all new devices or platforms will leverage artificial intelligence in the cloud or with some form of native machine learning. Arm is not the first IP or semiconductor vendor to offer an AI solution, but as the center of the industry’s largest processor architecture ecosystem, it may someday enable hundreds of billions of intelligent devices.

Today, cloud-based solutions are leveraging GPUs, FPGAs and custom chips for large deployments while most of the device-level solutions are using DSPs, dedicated IP blocks or custom accelerator chips. New solutions and companies are being announced almost weekly. Now Arm is stepping into the arena.

Project Trillium includes new processor cores designed specifically for the challenges of on-device machine learning. While targeting inference today, its goal also is to provide some level of model modification in the future.

Arm claims its cores will sport 3 TOPs/Watt, more than 4.6 TOPs in total (8-bit integer) performance and up to a 4x increases in performance with further optimizations. Initially, Project Trillium cores have a target power consumption of 1.5W on a 7nm fabrication process. The new cores can be integrated with existing Arm cores in a unified memory architecture that leverages open source software.

The new cores initially target smartphones and IP cameras, especially when paired with the Object Detection processor core Arm announced at CES and Arm’s neural network libraries. Long term, the cores could find use in any mobile or embedded application. The Project Trillium IP will be available to partners in mid-2018 with products likely in 2019.

Unfortunately, there is no one-size fits all with machine learning. Each new task has its own requirements of neural networks. This is driving the need for new processing architectures that both change with the workloads and increase overall processor performance exponentially.

It’s early days, and Arm has yet to provide details of its first family of products. The company joins a game in progress with many players already on the field. That said, it’s a game that could take decades to play out in data centers and even longer in the challenging space of edge computing.

–Jim McGregor is principal analyst at Tirias Research