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分類: Network Computing

The landscape of cyber threats is evolving rapidly, with sophisticated attacks, such as zero-day exploits, increasingly bypassing traditional signature-based network security defenses. To combat this, network security providers are integrating AI and machine learning into their solutions. This shift requires a new generation of high-performance, purpose-built network appliances capable of running complex AI inference models in real-time in order to perform deep packet inspection, behavioral analysis and automated threat response.

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分類: Telecommunication

In dense metropolitan, cellular traffic fluctuates rapidly due to dynamic user behavior — from rush-hour congestion to large public events. Traditional RAN configurations, often static and manually tuned, cannot adapt in real time to these shifting conditions. Operators need an intelligent, edge-based solution that can autonomously predict traffic surges, rebalance network resources, and maintain low-latency connectivity while minimizing energy consumption.

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分類: Power and Energy

Modern electrical grids are under pressure to maintain stability and efficiency while absorbing increasing amounts of renewable energy (solar, wind, etc.). Utilities need to modernize their substations and edge installations so they can handle bidirectional flows, real-time control, and interoperability among legacy and new equipment.

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分類: Network Computing

Today’s cyber adversaries no longer need advanced expertise to carry out attacks. Although highly skilled attackers have historically achieved greater success, modern technology, the widespread availability of sophisticated tools, and reduced costs have lowered the barrier to entry. Even less experienced actors can now exploit these resources to devise new and effective methods of breaching user accounts, penetrating infrastructure, moving laterally within networks, and extracting sensitive data—often within hours rather than days.

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分類: Edge AI

Aquaculture operations face significant challenges in monitoring fish growth and welfare. Traditional manual inspections are labor-intensive, time-consuming, and prone to human error. Fluctuations in water quality, environmental stress, and undetected health issues can negatively impact fish growth, welfare, and overall yield. Operators need real-time, accurate insights to make data-driven decisions that optimize fish health, improve productivity, and reduce operational costs.

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分類: Edge AI

Physical AI is redefining how robots operate in real-world environments. By combining AI vision, navigation, and real-time decision-making, autonomous machines can adapt to dynamic outdoor conditions and perform complex physical tasks with precision. This evolution goes beyond traditional automation, powering new applications in agriculture, logistics, inspection, and smart facility management.

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分類: Edge AI

Security screening at airports, border checkpoints, and large public venues demands both speed and precision. Traditional 2D X-ray systems often struggle to detect complex or hidden threats due to limited depth perception, resulting in blind spots, false positives, and slower inspection processes. These inefficiencies can lead to delays, reduced throughput, and increased operational costs—while still leaving potential vulnerabilities in threat detection.

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