Core Insights - PureVoltage Hosting announces a major expansion at the Telehouse facility in Staten Island, New York, reinforcing its position as the largest client at this location and commitment to providing high-performance infrastructure services globally [1][2] Capacity Expansion and Power Investment - The expansion includes the addition of 96 secure private-locking racks and 500kW of power, enhancing the company's ability to support enterprise, cloud, colocation, and AI workloads with improved reliability and flexibility [2] - PureVoltage has increased its connectivity to the New York International Internet Exchange (NYIIX), now exceeding 800Gbps of capacity, ensuring ultra-low latency and fast routing to major carriers and ISPs [4] Infrastructure Resilience - PureVoltage has maintained over 12 years of uninterrupted service at the Telehouse facility, demonstrating resilience even during catastrophic events like Hurricane Sandy, with no power-related downtime [3] Robust Features and Custom Solutions - The company offers a range of services including dedicated servers, bare metal, colocation, and cloud VPS solutions, designed to scale seamlessly for various workloads such as AI training clusters and fintech applications [5][10] - Key features include DDoS protection, 24/7 proactive network monitoring, carrier-neutral bandwidth, and compliance-ready environments [6] Vision for Future Growth - PureVoltage aims to expand across key markets including New York, Dallas, Los Angeles, Seattle, Tampa, and Chicago, with its relationship with Telehouse being crucial for future growth [6] - The Staten Island facility is strategically located for disaster resilience and long-term uptime, supporting enterprise digital transformation [9]

本文第一作者为中国科学院大学的博士生陈若愚，主要研究可解释 AI 以及在训练推理中的落地应用。第二作者为新加坡国立大学的梁思源，主要研究可信 AI。 主要合作者来自华为技术有限公司的刘势明和李茂森。通讯作者为中山大学的操晓春教授和中科院的张华研究员。 AI 决策的 可靠性与安全性 是其实际部署的核心挑战。当前智能体广泛依赖复杂的机器学习模型进行决策，但由于模型缺乏透明性，其决策过程往往难以被理解与 验证，尤其在关键场景中，错误决策可能带来严重后果。因此，提升模型的可解释性成为迫切需求。 目前已有的解释方法，如 Shapley Value、Integrated Gradients、Attention、Gradient（如 Grad-CAM）以及 Perturbation 等，虽然在小规模模型中取得了较好的解释效 果，但在面对多模态任务或大规模模型时，均存在不同程度的局限性，难以直接扩展或适用。因此， 发展一种在大模型与小模型中均具有良好适应性的高效可解 释归因方法具有重要意义 。 近期，中国科学院、新加坡国立大学、华为技术有限公司与中山大学的联合研究在多模态物体级基础模型的可解释归因技术方面取得了重要突破， 不 ...

LONDON, June 12, 2025 /PRNewswire/ -- Today, Corero Network Security (AIM: CNS) (OTCQX: DDOSF), the distributed denial of service (DDoS) protection specialists, announced a multi-year agreement with Rocket Fibre, a fast-growing UK broadband provider, to enhance its own network defenses and provide real-time DDoS protection for its customers.Rocket Fibre has selected Corero's SmartWall ONE™ solution to deliver scalable, real-time DDoS protection across its network. By integrating seamlessly with existing Jun ...