Imagine shrinking a giant, room-sized supercomputer down to a single tiny chip that fits on a desk. Instead of using standard electricity, it uses special silicon bits that can handle massive amounts of data simultaneously. It's like replacing a single-lane road with a thousand-lane highway to make AI run much faster and with less power.
Current AI is limited by the energy consumption and processing power of classical computers. Businesses struggle to scale data-intensive AI without incurring massive carbon footprints and hardware costs.
A Quantum System-on-a-Chip (QSoC) processor and a workstation-sized MVP demonstrator called Aquaris.
If you are a biotech company dealing with data-intensive molecular simulations — this project developed a Quantum System-on-a-Chip (QSoC) that provides massive acceleration for AI applications. This allows for faster discovery of new compounds while reducing the carbon footprint of the computing process.
If you are a fund manager dealing with complex risk modeling and AI-driven trading — this project developed a workstation-sized MVP called Aquaris. It leverages a quantum neural network array to process financial data more efficiently than classical computers.
If you are a logistics provider dealing with massive routing optimization problems — this project developed a scalable QPU based on silicon qubit technology. This enables the solving of complex AI challenges today with a more sustainable energy profile.
Based on available project data, specific pricing is not listed, but the project aims for 'affordability' by using existing commercial silicon foundry ecosystems to lower costs.
Yes, the project targets systems with >1M qubits by using commercial silicon processes to ensure scalability for advanced quantum computing use.
Based on available project data, the technology is developed by Equal1 Laboratories, but specific licensing terms are not provided in the report.
The technology is designed as a workstation-sized MVP (Aquaris) or a desktop quantum computer, integrating a QSoC processor into a cryogenic system.
The project period ended December 2024, with a first product launch based on a six-qubit device at the March 2025 APS meeting.
The consortium is highly streamlined, consisting of 2 SMEs from Ireland and Romania. With a 100% industry ratio, the project is focused on commercial delivery rather than academic research, leveraging commercial silicon foundries to accelerate the path to market.
Contact Equal1 Laboratories Ireland Limited for QSoC processor specifications.
Contact us to find partners for quantum-enhanced AI integration.
