AI scalability will require full-stack co-optimization, not just bigger data centers. AI workloads require a 10X compute ...
This is what the software-defined vehicle looks like in practice. Fewer chips, more consolidation, and far more dependence on ...
ChipAgents has introduced Renoir, an agentic large language model (LLM) whose name means “renew.” In early chip design ...
We nod at it, we put it on slides, and we move on. But the goalposts keep moving. Things that used to live comfortably at the ...
Ethernet auto-negotiation; multiphysics to avoid overdesign; PCB design reuse; mobile LLM quantization; modeling BSPDNs.
Expanding beyond traditional block-based SSD access with new command sets, broader media support, and improved transport ...
At the recent Data Center World 2026 in Washington, D.C., one message came through louder than ever: AI infrastructure is ...
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 ...
A new technical paper, Agentic Hardware Design as Repository-Level Code Evolution, was published by researchers at Nvidia ...
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 ...
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 ...
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