SaxonQ and Quantum Machines Debut First Live Application Demo on Mobile Quantum Computer

SaxonQ and Quantum Machines have unveiled the first public demonstration of real-time quantum applications, including image recognition, on a portable room-temperature quantum computer—reshaping possibilities for industrial Artificial Intelligence.

SaxonQ, a pioneer in mobile quantum computing, and Quantum Machines, known for their advanced hybrid quantum-classical control platforms, announced a breakthrough demonstration at Hannover Messe 2025. For the first time, applications such as quantum chemical calculations and real-time image recognition were run live on SaxonQ´s portable, room-temperature quantum computer, directly showcasing its potential outside controlled laboratory environments.

The standout feature of SaxonQ’s device is its ability to operate in real-world industrial settings without the need for cryogenic cooling, a significant technical leap over conventional quantum systems. The demonstration was made possible through the integration of Quantum Machines’ sophisticated control solutions, which enable robust, on-site quantum operations. According to Dr. Frank Schlichting, CEO of SaxonQ, this event underscores the reliability and flexibility of their technology, marking a major step toward mainstream adoption of quantum computing in manufacturing and other industrial applications.

The event not only highlighted quantum-based chemical simulations—such as energy level calculations for hydrogen molecules—but also illustrated the feasibility of real-time, quantum-powered image recognition. These practical examples signal an emerging new class of portable quantum devices capable of advancing on-the-go Artificial Intelligence, complex simulations, and optimization tasks in diverse industries. With their plug-and-play approach, SaxonQ and Quantum Machines have paved the way for broader, more accessible industrial quantum computing.

84

Impact Score

Crescent library brings privacy to digital identity systems

Crescent is a cryptographic library that adds unlinkability to common digital identity formats, preventing tracking across credential uses while preserving selective disclosure. It supports JSON Web Tokens and mobile driver’s licenses without requiring issuers to change their systems.

Artificial Intelligence-powered remote drug testing removes barriers to recovery

Q2i and King’s College London are collaborating to evaluate an Artificial Intelligence-powered at-home drug testing system aimed at people recovering from opioid use disorder. The solution delivers digitally observed, clinically reliable results and pairs testing with contingency management and telehealth to reduce logistical barriers to care.

Contact Us

Got questions? Use the form to contact us.

Contact Form

Clicking next sends a verification code to your email. After verifying, you can enter your message.