Moores Lab AI is betting that chip design AI will only work if it is built around deep semiconductor expertise, not generic ...

Researchers at Purdue University and the UCLA published a technical paper titled “Experimental Evidence for the Impact of ...

Aggressive prediction of $1T by 2030 was $700B too low. Here’s why.

The rise of agentic AI is shifting data centers from GPU-centric number crunching to CPU-driven orchestration, where managing long-running reasoning loops and context is just as important as raw ...

Larger packages, finer routing, and embedded functions are pushing advanced substrates toward application-specific designs.

A mixture of expert agentic AI systems can focus on their tasks with or without a commanding general, but challenges remain ...

AI may accelerate semiconductor design, but users still need formal proof, semantic continuity, and auditable workflows to trust automation.

A scalable LPDDR-based memory platform optimized for edge AI inferencing.

First-silicon success falls; engineering capacity; minimum clock period; optimizing PyTorch; counterfeit electronics.

Intel may be the marquee name, but materials suppliers, packaging hubs, and quantum startups will determine whether the region becomes a true semiconductor ecosystem.

Why design teams must organize before they optimize and how to utilize a purpose-built foundation for AI-ready data management across the chip design lifecycle.

Increasingly complex chip designs require more test data than those developed at older nodes and on single planar dies. The ...