Q.ANT Launches Second-Generation Photonic Processor for AI and High-Performance Computing

Q.ANT has announced the availability of its second-generation Native Processing Unit, the NPU 2, featuring enhanced nonlinear processing capabilities that deliver substantial gains in energy efficiency and performance for artificial intelligence and high-performance computing applications. The photonic processor performs nonlinear mathematics natively in light, enabling new classes of AI and scientific applications including physical AI, advanced robotics, next-generation computer vision, industrial intelligence, and physics-based simulation.

According to Dr. Michael Förtsch, CEO of Q.ANT, the company offers a new class of processors that enable performance gains beyond incremental improvements of digital counterparts, opening doors to superior algorithms that digital circuits cannot achieve. The NPU 2 demonstrates that performance and sustainability are not opposing forces but rather complementary aspects of advanced computing. The technology addresses the critical challenge of AI racing ahead of our ability to power it, with energy becoming the new frontier in computational advancement.

The acceleration of AI has reached the physical limits of silicon, where each new generation of GPUs consumes more power and water while producing more heat. Cooling systems now account for up to 40 percent of total data-center energy consumption. Photonic processing fundamentally changes this equation as light travels faster, generates minimal heat, and can execute complex functions in a single optical step that would require thousands of transistors in conventional CMOS chips. Q.ANT's architecture delivers up to 30 times lower energy use and 50 times higher performance for complex AI and HPC workloads by replacing transistor logic with native analog computation in light.

Q.ANT will debut its second-generation Native Processing Unit at Supercomputing 2025 in St. Louis from November 17-21. At the LRZ booth #535, the company will run a live image-based AI learning demonstration powered by the Q.ANT Photonic Algorithm Library on its photonic processors. The Q.PAL offers developers efficient, nonlinear algorithms and functions for complex workloads, continuously enhanced and optimized by Q.ANT for application-oriented photonic processing. The demonstration will show how photonic processors achieve more accurate results with fewer parameters and operations compared to conventional CPU-based systems.

Visitors can test how the NPU learns images within seconds using a nonlinear neural network, representing significant advancement from simple digit recognition to image classification and learning within just one year. Dr. Förtsch emphasized that photonic computing is scaling much faster than CMOS technology, achieving in one year what took ten years for digital computing. The rapid transition demonstrates why efficient, light-based computation will drive the next wave of AI and HPC development.

The second-generation NPU introduces an enhanced nonlinear processing core with optimized analog units for nonlinear network models that dramatically reduce parameter counts and training depth while improving accuracy for image learning, classification, and physics simulation. The system is delivered as a turnkey 19-inch rack-mountable server through the Native Processing Server NPS, which contains multiple NPU 2 processors and integrates seamlessly with existing CPUs and GPUs via PCIe and C/C++/Python APIs, making photonic acceleration immediately deployable in HPC and data-center environments.

In practical applications such as manufacturing, logistics, and inspection, photonic processors can execute nonlinear neural networks far more efficiently, allowing visual AI to recognize defects, track objects, and optimize inventories with fewer parameters. This dramatically reduces energy costs and makes computer vision systems economically viable for tasks previously considered too compute-intensive. The technology will accelerate next-generation AI architectures, including hybrid models that combine statistical reasoning with physical modeling, advancing domains such as drug discovery, materials design, and adaptive optimization where both nonlinear complexity and extreme energy efficiency are essential.

Q.ANT servers equipped with the latest NPU 2 processors are available for order now, with customer shipments scheduled for the first half of 2026. Each system ships as a turnkey, data-center-ready server that integrates seamlessly into existing HPC infrastructures. More information about the company and its photonic computing solutions can be found at https://www.qant.com.