The shift from software-defined to AI-defined vehicles raises questions about whether the hardware can keep up.

As models evolve faster than silicon cycles, chip architects must balance flexible compute, data movement, and ...

On-device AI can deliver faster insights, greater autonomy, and less cloud traffic — but only with the right infrastructure.

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

This eBook offers insights into what’s involved in photonics design, what’s changing (or at least what we know so far), and how those changes will affect semiconductor and electronic design in the ...

With the AI boom driving demand for faster semiconductor chip turnarounds, can AI help engineers meet those tighter deadlines? Startup Moores Lab AI hopes to provide a definitive answer with its ...

Quantum computing applications; monitoring shared memory; simulating solid state batteries; trusting ML in automotive; ...

Verification data is not enough without verification context Most verification environments are good at producing outputs. They generate logs, waveforms, assertions, coverage metrics, pass/fail status ...

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

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

EDA tools are helping design 3D-ICs and multi-die systems by co-optimizing across domains and speeding up design exploration. Customers face several pain points, including vendor interoperability, ...