CES 2026
who it's for
edge AI engineers, embedded engineers, autonomy engineers, wearable device designers, robotics engineers, mobile game developers, platform engineers, product managers
topics
on-device inference; always-on ML; ultra-low-power computing; safety-critical automotive design; automotive developer platforms; wearable neural sensors; mobile GPU for gaming; sensor fusion for AR/VR; humanoid robot manipulation; energy-first ML stacks; privacy-preserving edge AI
| title | author | length |
|---|---|---|
| AI-defined vehicles and autonomy | Drew Henry | 02m |
Claim: building AI-defined vehicles needs extremely high compute delivered with extreme efficiency; decades of safety-critical designs are being reused to meet… | ||
| The road ahead is AI-defined | Drew Henry | 02m |
AI-defined vehicles need high compute, high efficiency and Arm supplies safety-critical silicon already in production use with Tesla, Rivian and in Nvidia… | ||
| The impact of smart wearables | Chris Bergey | 01m |
Claims that edge AI and ultra-low-power computing let full AI inference run on tiny devices so smart glasses and next-generation health devices deliver… | ||
| AI that moves with you — Chris Bergey discusses the wearable future | Chris Bergey | 01m |
Claims that ARM is enabling wearable AI through always-on ML, ARM low-power cores, and glasses and skin-contact sensors with an emphasis on tiny, always-worn… | ||
| humanoid robots and the future of physical AI | Drew Henry | 01m |
Humanoid robots are evolving to do tasks beyond human limits, able to lift more and move faster and perform manipulation that humans cannot, not just mimic… | ||
| How gaming is evolving | Chris Bergey | 01m |
ARM reports it has shipped 10 billion GPUs into smartphones for gaming and describes ongoing console and VR growth while outlining a push to combine on‑device… | ||
| AI-powered mobile gaming | Chris Bergey | 01m |
ARM reports over 10 billion GPUs shipped into smartphones and shows a mobile-first platform that embeds on-device ML for AI agents and improved sensor fusion… | ||
| Why edge AI is becoming the default for devices | Chris Bergey | 01m |
Argues that putting models on-device becomes necessary because users expect always-on AI with low latency and local security and privacy guarantees rather than… | ||
| Why physical AI is being built | Drew Henry | 01m |
Claim: Arm supplies the compute building blocks and software platform that enable safe systems and highly efficient systems at scale. The talk points to Arm… | ||
| Why always-on, secure edge AI is scaling | Chris Bergey | 01m |
Argues that edge AI must be always-on low-latency and running on-device for security and privacy, not tethered to the cloud, and that this enables new hardware… | ||
| Physical AI is everywhere | Drew Henry | 01m |
Claims that Arm silicon and software stacks are the actual enabler of a wave of on-device AI by providing safe systems, highly efficient systems, and a mature… | ||
| nothing matches | ||