Signaloid announces preview of new ASIC targeting physical AI and robotics applications

Applications of AI


  • Signaloid previews new ASIC built specifically for physical AI and robotics workloads.

  • The chip is being taped out with TSMC in partnership with imec and Cadence’s IC-Link, and is expected to deliver up to 1000x better performance per watt for key physical AI workloads.

Cambridge, UK, June 2, 2026–(BUSINESS WIRE)–Signaloid (https://signaloid.com), a computing platform company providing hardware and binary translation-based acceleration of AI, robotics, aerospace, and quantitative finance workloads, today announced tapeout and preliminary specifications for its C0-ASIC. Delivery of the first customer engineering samples is scheduled for Q3 2026, and additional FPGA-based systems implementing the ASIC design are being discussed for deployment in the UK and Switzerland in late 2026.

C0-ASIC specifically targets energy-efficient physical AI workloads. The UK Advanced Research and Inventions Agency (ARIA) will accept deliveries of ASIC-based systems for use in next-generation AI workloads such as quadratic methods.

“ARIA’s Scaling Compute program has commissioned several innovative technology prototypes that explore unconventional ideas to design new AI accelerators.” ARIA Program Director Suraj Bramkhaval said: ”We commissioned Signaloid’s C0-ASIC to evaluate randomized numerical linear algebra and stochastic computing workloads. We believe that randomized linear algebra is a fundamentally new and powerful technique that underpins many applications in computer science, including AI, and leveraging these principles in hardware has the potential to provide entirely new vectors for improving performance. We are excited to partner with Signaloid to invest behind this theme and explore its full potential. ”

Different types of AI computing accelerators

The C0-ASIC is Signaloid’s distribution-enhanced computing hardware (UxHw®) Technology.

Unlike traditional CPUs and GPUs, which use vast amounts of computational power across thousands of computational cores to solve problems that require iterative randomized variations, Signaloid’s UxHw dynamically restructures computations based on new mathematical techniques to achieve the same results while often using 1000 times (or more) less energy.

UxHw technology and its implementation is covered by a growing portfolio of over 90 intellectual property applications in the US, China, Taiwan, Japan and the EU.

international partnership

The design and implementation is the result of a collaboration between Signaloid and world-leading design partners IC-Link by imec and US-based Cadence Design Systems.

“Leading AI hardware innovators trust IC Link as a key partner to bring cutting-edge ASIC concepts to manufacturing through design with foundry partner TSMC.” Ozgur Gursoy, Portfolio and Strategy Director for ASIC Services at IC-Link. “We are proud to partner with Signaloid in bringing the C0 Dreadnought ASIC from concept to design cycle and delivering a new class of computing efficiency for distribution-enhanced computing applications.”

Commenting on the partnership, John Heighton, Sales Group Director, North and Central EMEA, Cadence, said: “Cadence is setting the industry standard for enabling leading companies to tape out cutting-edge AI silicon, including Signaloid’s C0-Dreadnought, which is currently in production at TSMC. We are supporting startups driving next-generation computing by offering our high-performance Artisan SRAM memory for Signaloid’s ASICs.”

availability

C0-ASIC bump die engineering samples will be available in Q3 2026. A two-page preliminary design summary of the C0-ASIC is available immediately to eligible customers. Customers interested in robotics and industrial automation use cases can also see UxHw technology in action at the Bosch Connected World flagship event in Berlin on June 10-11, 2026.

About Signaloid

Signaloid was founded by Professor Philip Stanley Marvell, a former professor of physics and computing at the University of Cambridge and a former researcher at Bell Laboratories, IBM, Apple, and MIT. Signaloid provides a computing platform that benefits computationally challenging workloads. Many workloads can be reformulated in terms of algorithms that handle probability distributions. Its technology is already used by more than 3,000 users worldwide and is available in the cloud, on-premises, and as low-power edge hardware. www.signaloid.com

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contact address

Press contact: press@signaloid.com



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