<p>量子运输公司的独特解码器在高性能云环境中取得了新的进展</p>
<p>以色列拉阿纳纳，2026 年 2 月 24 日（全球新闻通讯社）——Rail Vision Ltd.（纳斯达克：RVSN）（“Rail Vision” 或 “公司”），一家专注于转变铁路安全和铁路数据市场的早期商业化技术公司，今天宣布其控股子公司 Quantum Transportation Ltd.（“Quantum Transportation”），一家量子计算创新公司，已成功在 AWS 云上实施其基于变压器的神经解码器，这标志着在运输领域实现现实世界量子应用的重要里程碑。</p>
<p>在最近推出的变压器神经解码器的基础上，该解码器在模拟中超越了经典量子错误校正（QEC）算法，并交付了其第一个通用错误校正原型，Quantum Transportation 的云部署现在提供了处理复杂量子数据所需的可扩展基础设施。</p>
<p>这一成就使 Quantum Transportation 能够与量子硬件设计合作伙伴合作，并进入下一个阶段：在不同架构的物理量子硬件上直接测试其无代码解码器。通过解决噪声量子设备中的错误校正挑战，这项技术可能在铁路异常检测、预测性维护和自主操作方面具有长期潜力。</p>
<p>“这次云实施是 Quantum Transportation 的一个关键进展，与 Rail Vision 探索将量子人工智能创新融入运输领域的使命完美契合，” Rail Vision 首席执行官 David BenDavid 表示。“作为 Quantum Transportation 的控股股东，我们很高兴利用这个可扩展的平台来提高铁路运营的效率和安全性，充分利用我们基于人工智能的视觉系统与量子错误校正之间的协同效应。”</p>
<p>Rail Vision 于 2026 年 1 月 14 日通过股份交换交易完成了对 Quantum Transportation 51% 股份的收购。Quantum Transportation 持有来自特拉维夫大学技术转移公司 Ramot 的一项创新待申请专利的铁路技术的独占子许可。</p>
<p><strong>关于 Quantum Transportation</strong></p>
<p>Quantum Transportation 提议开发一个由专利变压器基础的通用解码器（PD）驱动的量子错误校正模拟器。该解码器利用深度学习技术，能够跨量子代码进行泛化，从噪声模式中学习，并提供可扩展且与硬件无关的错误校正方法。专利的深度量子错误校正变压器（DQECCT）引入了一种新型机器学习解码器，使用基于变压器的架构预测和修正量子错误，结合来自奇偶校验矩阵的掩蔽层，并优化逻辑错误率（LER）、比特错误率（BER）和噪声估计误差的组合损失函数。这项技术旨在在准确性和速度上超越经典解码器（例如 MWPM），并独特地处理故障测量场景。它适用于各种代码，包括表面码、颜色码、自行车码和乘积码。</p>
<p><strong>关于 Rail Vision Ltd.</strong></p>
<p>Rail Vision 是一家专注于转变铁路安全和铁路数据市场的早期商业化技术公司。该公司开发了尖端的、基于人工智能的行业领先技术，专门为铁路设计。该公司开发的铁路检测系统旨在拯救生命、提高效率，并大幅降低铁路运营商的费用。Rail Vision 相信，其技术将显著提高全球铁路安全，同时为依赖铁路生态系统的每个人创造显著的利益并增加价值：从使用火车进行运输的乘客到利用铁路运输货物和服务的公司。此外，该公司相信，其技术有潜力将自主列车的革命性概念变为现实。有关更多信息，请访问 https://www.railvision.io/</p>
<p><strong>前瞻性声明</strong></p>
<p>本新闻稿包含《私人证券诉讼改革法案》和其他证券法所定义的 “前瞻性声明”。诸如 “预计”、“预期”、“打算”、“计划”、“相信”、“寻求”、“估计” 等词语及其类似表达或变体旨在识别前瞻性声明。这些期望、信念和预测是以善意表达的。例如，Rail Vision 在讨论 Quantum Transportation 与量子硬件设计合作伙伴合作并进入项目的下一个阶段时，使用了前瞻性声明，Rail Vision 的使命是探索量子人工智能创新在交通运输领域的整合，并利用 Quantum Transportation 的可扩展平台提升铁路运营的效率和安全性，利用其基于人工智能的视觉系统与量子纠错之间的协同效应。然而，无法保证管理层的期望、信念和预测将会实现，实际结果可能与前瞻性声明中所表达或指示的内容有实质性差异。前瞻性声明受到风险和不确定性的影响，这可能导致实际表现或结果与前瞻性声明中所表达的内容有实质性差异。有关影响公司的风险和不确定性的更详细描述，请参考公司不时向证券交易委员会（“SEC”）提交的报告，包括但不限于在 2025 年 3 月 31 日向 SEC 提交的截至 2024 年 12 月 31 日的财政年度的 20-F 表格年报中详细列出的风险。前瞻性声明仅在声明发布之日有效。公司不承担更新前瞻性声明以反映实际结果、后续事件或情况、假设变化或影响前瞻性信息的其他因素变化的义务，除非适用的证券法要求。如果公司更新一项或多项前瞻性声明，不应推断公司将就此或其他前瞻性声明进行额外更新。提供的参考和链接仅为方便，网站上包含的信息并未被纳入本新闻稿的引用。Rail Vision 对第三方网站的内容不承担责任。</p>
<p><strong>联系方式</strong></p>
<p>David BenDavid</p>
<p>首席执行官</p>
<p>Rail Vision Ltd.</p>
<p>15 Ha'Tidhar St</p>
<p>以色列拉阿纳纳，邮政编码 4366517</p>
<p>电话：+972- 9-957-7706</p>
<p><strong>投资者关系：</strong></p>
<p>Michal Efraty</p>
<p>investors@railvision.io</p>
<p><img src="https://imageproxy.pbkrs.com/https://www.globenewswire.com/newsroom/ti/query-bmY9T1RZMk1EQXpPU00zTkRVeE5ETTNJelV3TURFek1EY3dOQT09?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="" original-src="https://imageproxy.pbkrs.com/https://www.globenewswire.com/newsroom/ti/query-bmY9T1RZMk1EQXpPU00zTkRVeE5ETTNJelV3TURFek1EY3dOQT09"/></p>
<p><img src="https://imageproxy.pbkrs.com/https://ml.globenewswire.com/media/NWE1MjIyZmMtZTM2Yi00MDMwLWIyMGYtYmFhYmM4YjZiNDY4LTUwMDEzMDcwNC0yMDI2LTAyLTI0LWVu/tiny/Rail-Vision-Ltd-.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="" original-src="https://imageproxy.pbkrs.com/https://ml.globenewswire.com/media/NWE1MjIyZmMtZTM2Yi00MDMwLWIyMGYtYmFhYmM4YjZiNDY4LTUwMDEzMDcwNC0yMDI2LTAyLTI0LWVu/tiny/Rail-Vision-Ltd-.png"/></p>

RVSN

RVSNW

<p>Rail Vision Ltd.（纳斯达克代码：RVSN）宣布其子公司 Quantum Transportation 已成功在 AWS 云上实施基于变压器的神经解码器，这标志着在交通运输领域实现真实世界量子应用的重要一步。这一成就使得与量子硬件合作伙伴的协作以及在物理量子硬件上的测试成为可能。该技术旨在通过先进的错误纠正方法提高铁路安全性和效率。Rail Vision 于 2026 年 1 月收购了 Quantum Transportation 51% 的股份，进一步推动其将量子人工智能创新整合到铁路行业的使命</p>

<p><em>Quantum Transportation’s unique decoder is making another step forward by being validated in high-performance cloud environments</em></p>
<div class="lb-trans"><p>量子运输公司的独特解码器在高性能云环境中取得了新的进展</p>
</div><p>Ra’anana, Israel, Feb. 24, 2026 (GLOBE NEWSWIRE) -- Rail Vision Ltd. (Nasdaq: RVSN) (“Rail Vision” or the “Company”), an early commercialization stage technology company focused on transforming railway safety and the rail data markets, announced today that its majority owned subsidiary Quantum Transportation Ltd. (“Quantum Transportation”), a quantum computing innovator, has successfully implemented its transformer-based neural decoder on the AWS cloud, marking a significant milestone toward real-world quantum applications within the transportation sector.</p>
<div class="lb-trans"><p>以色列拉阿纳纳，2026 年 2 月 24 日（全球新闻通讯社）——Rail Vision Ltd.（纳斯达克：RVSN）（“Rail Vision” 或 “公司”），一家专注于转变铁路安全和铁路数据市场的早期商业化技术公司，今天宣布其控股子公司 Quantum Transportation Ltd.（“Quantum Transportation”），一家量子计算创新公司，已成功在 AWS 云上实施其基于变压器的神经解码器，这标志着在运输领域实现现实世界量子应用的重要里程碑。</p>
</div><p>Building on the recent unveiling of its transformer neural decoder, which outperformed classical quantum error correction (QEC) algorithms in simulations, and the delivery of its first prototype for universal error correction, Quantum Transportation's cloud deployment now provides the scalable infrastructure needed to process complex quantum data efficiently.</p>
<div class="lb-trans"><p>在最近推出的变压器神经解码器的基础上，该解码器在模拟中超越了经典量子错误校正（QEC）算法，并交付了其第一个通用错误校正原型，Quantum Transportation 的云部署现在提供了处理复杂量子数据所需的可扩展基础设施。</p>
</div><p>This achievement positions Quantum Transportation with the ability to collaborate with quantum hardware design partners and enter the next phase: direct testing of its code-agnostic decoder on physical quantum hardware across diverse architectures. By addressing error correction challenges in noisy quantum devices, this technology may have long-term potential for railway anomaly detection, predictive maintenance, and autonomous operations.</p>
<div class="lb-trans"><p>这一成就使 Quantum Transportation 能够与量子硬件设计合作伙伴合作，并进入下一个阶段：在不同架构的物理量子硬件上直接测试其无代码解码器。通过解决噪声量子设备中的错误校正挑战，这项技术可能在铁路异常检测、预测性维护和自主操作方面具有长期潜力。</p>
</div><p>“This cloud implementation is a pivotal advancement for Quantum Transportation and aligns seamlessly with Rail Vision’s mission to explore the integration of quantum-AI innovations into the transportation sector,” said David BenDavid, CEO of Rail Vision. “As Quantum Transportation’s majority owner, we are excited to leverage this scalable platform to enhance efficiency and safety in railway operations, capitalizing on the synergies between our AI-driven vision systems and quantum error correction.”</p>
<div class="lb-trans"><p>“这次云实施是 Quantum Transportation 的一个关键进展，与 Rail Vision 探索将量子人工智能创新融入运输领域的使命完美契合，” Rail Vision 首席执行官 David BenDavid 表示。“作为 Quantum Transportation 的控股股东，我们很高兴利用这个可扩展的平台来提高铁路运营的效率和安全性，充分利用我们基于人工智能的视觉系统与量子错误校正之间的协同效应。”</p>
</div><p>Rail Vision completed its acquisition of a 51% stake in Quantum Transportation on January 14, 2026, through a share exchange transaction. Quantum Transportation holds an exclusive sub-license for rail technologies from an innovative pending patent in quantum error correction owned by Ramot, the technology transfer company of Tel Aviv University.</p>
<div class="lb-trans"><p>Rail Vision 于 2026 年 1 月 14 日通过股份交换交易完成了对 Quantum Transportation 51% 股份的收购。Quantum Transportation 持有来自特拉维夫大学技术转移公司 Ramot 的一项创新待申请专利的铁路技术的独占子许可。</p>
</div><p><strong>About Quantum Transportation</strong></p>
<div class="lb-trans"><p><strong>关于 Quantum Transportation</strong></p>
</div><p>Quantum Transportation proposes to develop a Quantum Error Correction Simulator powered by a patented Transformer-based Universal Decoder (PD). This decoder, leveraging deep learning techniques, generalizes across quantum codes, learns from noise patterns, and delivers a scalable and hardware-agnostic approach to error correction. The patented Deep Quantum Error Correction Transformer (DQECCT) introduces a novel machine-learning decoder that predicts and refines quantum errors using transformer-based architectures, incorporates masking layers derived from parity-check matrices and optimizes a combined loss function over Logical Error Rate (LER), Bit Error Rate (BER), and Noise Estimation Error. This technology aspires to outperform classical decoders (e.g., MWPM) in both accuracy and speed and uniquely handles faulty measurement scenarios. It is adaptable to various codes - including Surface, Color, Bicycle, and Product Codes.</p>
<div class="lb-trans"><p>Quantum Transportation 提议开发一个由专利变压器基础的通用解码器（PD）驱动的量子错误校正模拟器。该解码器利用深度学习技术，能够跨量子代码进行泛化，从噪声模式中学习，并提供可扩展且与硬件无关的错误校正方法。专利的深度量子错误校正变压器（DQECCT）引入了一种新型机器学习解码器，使用基于变压器的架构预测和修正量子错误，结合来自奇偶校验矩阵的掩蔽层，并优化逻辑错误率（LER）、比特错误率（BER）和噪声估计误差的组合损失函数。这项技术旨在在准确性和速度上超越经典解码器（例如 MWPM），并独特地处理故障测量场景。它适用于各种代码，包括表面码、颜色码、自行车码和乘积码。</p>
</div><p><strong>About Rail Vision Ltd.</strong></p>
<div class="lb-trans"><p><strong>关于 Rail Vision Ltd.</strong></p>
</div><p>Rail Vision is an early commercialization stage technology company focused on transforming railway safety and the rail data markets. The company has developed cutting edge, artificial intelligence based, industry-leading technology specifically designed for railways. The company has developed its railway detection systems to save lives, increase efficiency, and dramatically reduce expenses for the railway operators. Rail Vision believes that its technology will significantly increase railway safety around the world, while creating significant benefits and adding value to everyone who relies on the train ecosystem: from passengers using trains for transportation to companies that use railways to deliver goods and services. In addition, the company believes that its technology has the potential to advance the revolutionary concept of autonomous trains into a practical reality. For more information, please visit https://www.railvision.io/</p>
<div class="lb-trans"><p>Rail Vision 是一家专注于转变铁路安全和铁路数据市场的早期商业化技术公司。该公司开发了尖端的、基于人工智能的行业领先技术，专门为铁路设计。该公司开发的铁路检测系统旨在拯救生命、提高效率，并大幅降低铁路运营商的费用。Rail Vision 相信，其技术将显著提高全球铁路安全，同时为依赖铁路生态系统的每个人创造显著的利益并增加价值：从使用火车进行运输的乘客到利用铁路运输货物和服务的公司。此外，该公司相信，其技术有潜力将自主列车的革命性概念变为现实。有关更多信息，请访问 https://www.railvision.io/</p>
</div><p><strong>Forward-Looking Statements</strong></p>
<div class="lb-trans"><p><strong>前瞻性声明</strong></p>
</div><p>This press release contains “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act and other securities laws. Words such as “expects,” “anticipates,” “intends,” “plans,” “believes,” “seeks,” “estimates” and similar expressions or variations of such words are intended to identify forward-looking statements. Such expectations, beliefs and projections are expressed in good faith. For example, Rail Vision is using forward-looking statements when it discusses Quantum Transportation collaborating with quantum hardware design partners and entering the next phase of the project, Rail Vision’s mission to explore the integration of quantum-AI innovations into the transportation sector and leveraging Quantum Transportation’s scalable platform to enhance efficiency and safety in railway operations, capitalizing on the synergies between its AI-driven vision systems and quantum error correction. However, there can be no assurance that management’s expectations, beliefs and projections will be achieved, and actual results may differ materially from what is expressed in or indicated by the forward-looking statements. Forward-looking statements are subject to risks and uncertainties that could cause actual performance or results to differ materially from those expressed in the forward-looking statements. For a more detailed description of the risks and uncertainties affecting the Company, reference is made to the Company’s reports filed from time to time with the Securities and Exchange Commission (“SEC”), including, but not limited to, the risks detailed in the Company’s annual report on Form 20-F for the fiscal year ended December 31, 2024, filed with the SEC on March 31, 2025. Forward-looking statements speak only as of the date the statements are made. The Company assumes no obligation to update forward-looking statements to reflect actual results, subsequent events or circumstances, changes in assumptions or changes in other factors affecting forward-looking information except to the extent required by applicable securities laws. If the Company does update one or more forward-looking statements, no inference should be drawn that the Company will make additional updates with respect thereto or with respect to other forward-looking statements. References and links to websites have been provided as a convenience, and the information contained on such websites is not incorporated by reference into this press release. Rail Vision is not responsible for the contents of third-party websites.</p>
<div class="lb-trans"><p>本新闻稿包含《私人证券诉讼改革法案》和其他证券法所定义的 “前瞻性声明”。诸如 “预计”、“预期”、“打算”、“计划”、“相信”、“寻求”、“估计” 等词语及其类似表达或变体旨在识别前瞻性声明。这些期望、信念和预测是以善意表达的。例如，Rail Vision 在讨论 Quantum Transportation 与量子硬件设计合作伙伴合作并进入项目的下一个阶段时，使用了前瞻性声明，Rail Vision 的使命是探索量子人工智能创新在交通运输领域的整合，并利用 Quantum Transportation 的可扩展平台提升铁路运营的效率和安全性，利用其基于人工智能的视觉系统与量子纠错之间的协同效应。然而，无法保证管理层的期望、信念和预测将会实现，实际结果可能与前瞻性声明中所表达或指示的内容有实质性差异。前瞻性声明受到风险和不确定性的影响，这可能导致实际表现或结果与前瞻性声明中所表达的内容有实质性差异。有关影响公司的风险和不确定性的更详细描述，请参考公司不时向证券交易委员会（“SEC”）提交的报告，包括但不限于在 2025 年 3 月 31 日向 SEC 提交的截至 2024 年 12 月 31 日的财政年度的 20-F 表格年报中详细列出的风险。前瞻性声明仅在声明发布之日有效。公司不承担更新前瞻性声明以反映实际结果、后续事件或情况、假设变化或影响前瞻性信息的其他因素变化的义务，除非适用的证券法要求。如果公司更新一项或多项前瞻性声明，不应推断公司将就此或其他前瞻性声明进行额外更新。提供的参考和链接仅为方便，网站上包含的信息并未被纳入本新闻稿的引用。Rail Vision 对第三方网站的内容不承担责任。</p>
</div><p><strong>Contacts</strong></p>
<div class="lb-trans"><p><strong>联系方式</strong></p>
</div><p>David BenDavid</p>
<div class="lb-trans"><p>David BenDavid</p>
</div><p>Chief Executive Officer</p>
<div class="lb-trans"><p>首席执行官</p>
</div><p>Rail Vision Ltd.</p>
<div class="lb-trans"><p>Rail Vision Ltd.</p>
</div><p>15 Ha'Tidhar St</p>
<div class="lb-trans"><p>15 Ha'Tidhar St</p>
</div><p>Ra'anana, 4366517 Israel</p>
<div class="lb-trans"><p>以色列拉阿纳纳，邮政编码 4366517</p>
</div><p>Telephone: +972- 9-957-7706</p>
<div class="lb-trans"><p>电话：+972- 9-957-7706</p>
</div><p><strong>Investor Relations:</strong></p>
<div class="lb-trans"><p><strong>投资者关系：</strong></p>
</div><p>Michal Efraty</p>
<div class="lb-trans"><p>Michal Efraty</p>
</div><p>investors@railvision.io</p>
<div class="lb-trans"><p>investors@railvision.io</p>
</div><p><img src="https://imageproxy.pbkrs.com/https://www.globenewswire.com/newsroom/ti/query-bmY9T1RZMk1EQXpPU00zTkRVeE5ETTNJelV3TURFek1EY3dOQT09" alt="" original-src="https://www.globenewswire.com/newsroom/ti?nf=OTY2MDAzOSM3NDUxNDM3IzUwMDEzMDcwNA=="/></p>
<p><img src="https://imageproxy.pbkrs.com/https://ml.globenewswire.com/media/NWE1MjIyZmMtZTM2Yi00MDMwLWIyMGYtYmFhYmM4YjZiNDY4LTUwMDEzMDcwNC0yMDI2LTAyLTI0LWVu/tiny/Rail-Vision-Ltd-.png" alt="" original-src="https://ml.globenewswire.com/media/NWE1MjIyZmMtZTM2Yi00MDMwLWIyMGYtYmFhYmM4YjZiNDY4LTUwMDEzMDcwNC0yMDI2LTAyLTI0LWVu/tiny/Rail-Vision-Ltd-.png"/></p>

Rail Vision：量子运输正朝着量子硬件集成的方向发展 | RVSN 股票新闻