Latest from Vellex

Modern EV and autonomous vehicle safety is limited by digital-first architectures that introduce latency, power, and signal-quality constraints. Analog intelligence enables continuous, ultra-low-power computation directly on raw sensor signals before digitization, improving response time, robustness, and always-on safety. By enhancing sensor quality and reducing front-end latency, analog computing complements digital AI and forms a hybrid, physics-aligned foundation for safer vehicles.

AI’s rapid growth, powered by energy-hungry GPUs, has sparked a sustainability crisis driven by the inefficiency of digital computing’s von Neumann architecture. To overcome this, innovators are reviving analog and neuromorphic computing, which process data directly in memory, eliminating energy-intensive data movement. Companies like Vellex Computing are leading this shift, enabling ultra-efficient, brain-inspired chips that bring powerful, sustainable AI to edge devices worldwide.

AI and high-performance computing are hitting an energy wall as digital architectures consume unsustainable power for data movement and training. Analog computing offers a breakthrough - processing information through continuous physical dynamics instead of binary logic, enabling up to 100× energy efficiency and real-time performance. By computing with physics itself, analog systems redefine performance metrics and pave the path toward sustainable, high-efficiency intelligence.