AI is rocketing ahead. It is the biggest industrial revolution of our age. AI adoption is growing, but still most are at ...

This is what the software-defined vehicle looks like in practice. Fewer chips, more consolidation, and far more dependence on ...

Ethernet auto-negotiation; multiphysics to avoid overdesign; PCB design reuse; mobile LLM quantization; modeling BSPDNs.

A new technical paper, Agentic Hardware Design as Repository-Level Code Evolution, was published by researchers at Nvidia ...

In next-generation silicon, AI can interpret system behavior at scale, but only if observability is designed into the fabric ...

DSP adoption demonstrated that technical innovation alone is not enough. Three lessons remain particularly relevant for edge ...

Expanding beyond traditional block-based SSD access with new command sets, broader media support, and improved transport ...

AI data centers need power from a range of sources, including batteries, to safeguard against blackouts, transient voltage spikes, and grid demand spikes. As with regenerative braking and ...

The intersection of AI and cybersecurity is the data itself. Trustworthy fusion depends on authenticated, integrity‑checked inputs and verifiable, attributable AI outputs. Defending against AI-enabled ...

Processing-using-DRAM interference; atomic-scale plasma processing; gallium oxide phase instability; event-driven reinforcement learning for fab control; microarchitectural timing leaks in embedded ...

Embedded systems are becoming more powerful, more connected, and more exposed. At the same time, attacks on hardware evolve rapidly, expanding beyond software exploits into physical techniques such as ...