AI workflows fundamentally depend on real-time data movement: ingesting training data streams, feeding live data to models for inference and distributing predictions back to applications. But strip ...

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs large-scale nonlinear ...

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs ...

UCLA researchers demonstrate diffractive optical processors as universal nonlinear function approximators using linear ...

This creates what you might call the AI workflow paradox: the faster we can generate code, the more critical it becomes to ...

Abstract: Distributed massive MIMO systems are expected to be part of the upcoming generation of wireless systems where joint communication and positioning opens the possibility of exploring new ...