The challenges of using AI in critical systems

Artificial intelligence (AI) is increasingly vital in managing critical systems, enhancing decision-making by analyzing vast data quickly. However, challenges remain, including ensuring AI’s suggestions are valid and explainable. Thales emphasizes the importance of cybersecurity to protect AI systems from vulnerabilities, ensuring trust in their deployment across various sectors.

Optimize data center networking for AI workloads [London – United Kingdom]

Organizations must optimize data center networking to handle the unique demands of AI workloads, which require high bandwidth, low latency, and reliable connectivity. This involves evolving both back-end and front-end networks, leveraging Ethernet technologies, and implementing flexible hardware and automation tools to support AI training and inference effectively.

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