Which is better for machine-learning applications: 2nd Generation Intel Xeon Scalable Processors or Nvidia’s T4? A head-to-head comparison helps explain whether a CPU or a GPU is best for your high-performance ML solution.

New GPGPU modules expand Curtiss-Wright’s family of high-performance embedded computing (HPEC) processors for artificial intelligence (AI) applications.

Newer on-vehicle integrated networks will be composed of heterogeneous networks in the form of software and equipment from multiple commercial vendors.

The use of artificial intelligence (AI) based machine learning technologies in autonomous vehicles is on the rise.

The fast growth of small satellites and their lower life cycle and launch costs has created a sizable market for low-cost electronic components that have radiation-resistant characteristics.

A combination of Curtiss-Wright’s CHAMP-XD1 processor module and General Dynamics Mission Systems’ SignalEye software uses machine learning to detect threats in the RF spectrum.

Curtiss-Wright is working with NASA and aerospace leaders to return Americans to the Moon and send astronauts to Mars in the early 2030s

SWaP-optimized COTS-based Digital Beachhead VICTORY-compliant network switch adds Complementary Assured Position, Navigation and Timing (A-PNT) services to ease modernization of ground vehicles.