Demand for high-performance compute and storage for AI training and inference continues to climb. Phison has partnered with AI infrastructure management software provider Infinitix to integrate its aiDAPTIV+ intelligent storage technology with Infinitix's AI-Stack platform, delivering an enterprise-grade AI training and inference solution that unifies hardware and software.

If the main stage at CES 2026 still tried to preserve a sense of future possibility for software-defined vehicles, conversations away from the spotlight told a different story. In private discussions among supply-chain executives and engineers, the tone was noticeably cooler; it is pragmatic, cautious, and marked by hard-earned restraint.

At CES 2026, the global auto industry's conversation has shifted. The focus is no longer confined to the aspirational language of software-defined vehicles (SDVs), but increasingly to the physical limits those ambitions must confront. Battery-electric vehicles are often cast as the most natural embodiment of this future. Yet quietly, and perhaps more consequentially, vehicles powered by internal combustion engines are running up against a harsh and largely irreversible constraint of their own: the physics of computing.

At a media briefing on January 6, Nvidia's chief executive, Jensen Huang, offered further details on the safety design and real-world operating conditions of the company's newly unveiled autonomous-driving platform, Nvidia Alpamayo, as questions mount over how quickly such systems can move from demonstration to daily use.