As part of this effort, today, Thales is breaking new ground as a member of multiple new consortia that have been set up since late 2022 in these domains:

    • Quantum repeaters, with the Delft University: QIA (Quantum Internet Alliance) – led by the Delft University of Technology in the Netherlands;
    • Quantum key distribution: QKISS – coordinated by Exail – and QUARTER – led by LuxQuanta.
    • Certification of quantum communication: PETRUS – led by Deutsche Telekom – is the official coordinator of 32 EuroQCI projects, on behalf of the European Commission.
    • Satellites quantum communications: TeQuantS – led by Thales Alenia Space – aims at developing quantum space-to-Earth communications technologies, necessary for cybersecurity applications and future quantum information networks, through the construction of satellites and optical ground stations by the end of 2026.

Specifically, the Thales teams taking part in these projects are working to develop quantum key generation, distribution and management equipment and the associated communication encryption devices, as well as defining the architecture of these quantum communication infrastructures. Click here to read the BusinessWire release in-entirety.

SandboxAQ receives FedHealthIT Disruptive Tech Award

At the FedHealthIT Disruptive Tech Summit, SandboxAQ received the FedHealthIT Disruptive Tech Award, recognizing SandboxAQ’s Security Suite. The cryptographic management software is currently deployed at the U.S. Department of Health and Human Services.
SandboxAQ recently delivered the first post-quantum cryptography (PQC) inventory in the federal health IT community to HHS–three months ahead of the scheduled delivery date, in partnership with SandboxAQ performed network cryptography analysis and assessed the cybersecurity architecture of’s HHS fulfillment network. SandboxAQ also implemented PQC discovery tools to plan for the protection of systems and sensitive data
The FedHealthIT Disruptive Tech Awards recognize programs from both industry and government that drive transformational progress in the federal market and have a measurable impact on culture and mission.  Click here to read announcement in-entirety.

Quantum techniques could bring Generative AI to the enterprise

Christopher Savoie, PhD, the CEO & founder of Zapata Computing,  is the author of an April 10 Forbes article in which he describes how quantum-inspired techniques could bring Generative AI tools to the market. Quantum News Briefs summarizes.
Generative AI tools have the potential to transform entire industries.  But all that potential value comes at a steep cost. The more complex the generative model, the more expensive the required compute resources. ChatGPT itself costs $100,000 a day to run, while Google’s ChatGPT competitor, Bard, will reportedly cost the company 10 times more per query than a standard keyword search. The environmental costs of this excessive compute consumption will no doubt be just as steep, and this doesn’t include the high costs of training such a complex model, the learning curve to understand new mathematical formulations, or the need to develop specialized expertise in the tooling and infrastructure to make these solutions work.
To truly start the generative AI revolution for enterprise applications, the costs need to come down significantly.
Techniques inspired by quantum physics could have the potential to reduce the computational costs for large language models (LLMs). What’s more, these quantum-inspired techniques could broaden the use cases of generative AI for enterprises—particularly in solving complex optimization problems.
The quantum-inspired techniques we’re concerned with here are tensor networks—essentially, efficient linear algebraic structures for representing complex correlations between variables.
Tensor networks could potentially play a critical role in the development of quantum computing: They can simulate quantum circuits on classical hardware today and could be replaced with real quantum circuits in the future. Thus, tensor networks could allow users to start developing “quantum applications” on classical hardware that can run on the fault-tolerant quantum computers of the future. This would allow enterprises to develop capabilities that could be useful once we have fault-tolerant or strongly error-mitigated quantum computers.
Not only can tensor networks compress generative models, but the resulting tensorized generative models could also generate higher-quality samples. This could have major implications for enterprise applications of generative AI.  Click here to read Savoi’s article in-entirety.


Sandra K. Helsel, Ph.D. has been researching and reporting on frontier technologies since 1990.  She has her Ph.D. from the University of Arizona.