Meta and Arm just unveiled a partnership to co-develop multiple generations of custom data center CPUs, starting with the new Arm AGI CPU. The chip is engineered to pack more compute into tight spaces while running alongside Meta's custom MTIA silicon. Meta will also release its board and rack designs through the Open Compute Project later this year.
ARM just unveiled Neural Super Sampling, a dedicated mobile AI upscaling tech designed to bring high-end PC-style gaming to smartphones. Running on trained AI models, it can boost a 540p render to 1080p without muddy textures while preserving battery life. The catch? You'll have to wait at least a year for next-gen silicon and game studios to support it.
Stability AI just teamed up with Arm to open-source Stable Audio Open Small, a 341M parameter text-to-audio model built to run on smartphone CPUs. Powered by Arm KleidiAI, it generates up to 11 seconds of stereo sound in under 8 seconds. Why it matters: generative audio is finally moving off the cloud and directly onto edge devices for real-time sound effects.
Stability AI just teamed up with Arm to run its text-to-audio model, Stable Audio Open, directly on smartphone CPUs without an internet connection. Powered by Arm's KleidiAI libraries, generating an 11-second audio clip dropped from 240 seconds to under 8 seconds—a 30x speedup for on-device creators.
Arm is reportedly preparing to launch its first in-house server CPU as soon as this summer, with Meta lined up as an early customer. Driven by SoftBank's Masayoshi Son, the move marks a dramatic shift away from Arm's pure-play licensing model and pits it squarely against Intel and AMD in the AI data center race.
Microsoft just unveiled its first in-house silicon at Ignite: the Azure Maia 100 AI accelerator and the 128-core Azure Cobalt 100 CPU. Designed to power Azure workloads, Copilot, and OpenAI’s models, Maia packs 105 billion transistors on a 5nm node. Why it matters: Microsoft is finally joining Google and AWS with custom chips, giving it tighter control over skyrocketing AI infrastructure costs.
