Rail Vision Subsidiary Achieves Quantum Error Correction Milestone Using Google Quantum AI Dataset

Rail Vision Ltd. (NASDAQ: RVSN, FSE: C80) announced today that its majority-owned subsidiary, Quantum Transportation Ltd., has achieved a significant milestone in quantum error correction. The company has successfully delivered a working integration layer that incorporates a publicly accessible experimental surface-code dataset from Google Quantum AI into its patent-pending quantum error correction transformer pipeline. This advancement moves Quantum Transportation's transformer-based quantum decoder technology beyond internal data environments, establishing a scalable foundation for training and benchmarking neural quantum error correction systems using external experimental datasets.

The milestone is important because it reduces technical risk and demonstrates that Quantum Transportation's technology can work with real-world experimental data from a leading quantum computing player like Google. By leveraging Google's dataset, the company can validate its algorithms on publicly available data, which accelerates development and enhances credibility. This progress could have implications for the broader quantum computing industry, as error correction is a critical challenge that must be solved for practical quantum computing to become viable.

Rail Vision holds a 51% stake in Quantum Transportation, which has an exclusive sub-license for rail technologies under an innovative pending patent in quantum error correction owned by Ramot, the technology transfer company of Tel Aviv University. The integration of Google Quantum AI's dataset into Quantum Transportation's pipeline marks a step forward in the commercialization of quantum error correction technologies.

Rail Vision is an early commercialization stage technology company transforming railway safety through advanced AI-integrated sensing systems. The company develops proprietary, multi-spectral electro-optic platforms that provide extended-range situational awareness and real-time hazard detection. Its cloud-based platform transforms railway operational data into actionable insights to help optimize performance, reduce downtime, and improve safety. As the company expands its global footprint, it delivers AI-driven perception that supports safer operations and enables the transition to fully autonomous operations.

For more information about Rail Vision and its technologies, visit the company's newsroom at http://nnw.fm/RVSN. The full press release is available at https://nnw.fm/yIoih.