Hello Embedded Engineers and Developers Welcome to In Case You Missed it: Embedded Insights, the weekly news show all about Embedded technologies and solutions from Embedded Computing Design.

Often in electronics system design, the parameters of power and performance are traded off against each other: an improvement in one parameter weakens the other.

Bangalore, India. Ambient Scientific released its GPX10 Pro system-on-chip (SoC) utilizing advanced AI-native silicon technology to empower enhanced AI inference on battery-powered edge devices. Its AI engine allows various neural networking model types, including CNNs, RNNs, LSTMs and GRUs, locally at the edge. The GPX10 Pro is built on Ambient Scientific’s proprietary DigAn silicon architecture offering up to 100x improvements in power, performance and area compared to conventional 32-bit microcontrollers.

For decades, performance has been the holy grail of processor innovation. More gigahertz, more FLOPs, more cores, the race has largely revolved around speed and brute-force capabilities. But in today’s AI-driven world, especially at the edge, that narrative is shifting dramatically. We're entering an era where efficiency, not just performance, will determine the future of processing architectures.