This week’s AI news in a nutshell? Meta is moving towards building AI-powered humanoid robots. Skepticism remains about the true efficiency of China’s DeepSeek model, and experts predict it’s only a matter of time before something bigger takes its place. For enterprises, these advancements are reshaping the way businesses operate – companies rely on AI for predictive modeling, cybersecurity, supply chain optimization, customer insights, and much more…

But as AI does more and gets smarter, it also gets hungrier for more power, more processing, and more bandwidth. Data centers are feeling the heat, literally and figuratively. According to Reuters, 80% of data center operators expect major increases in AI-driven workloads. But the biggest challenge – and opportunity – isn’t just about power or cooling; it’s about the networks that keep everything connected.

The problem? Today’s networks weren’t built for AI at this scale. Legacy infrastructure is struggling to keep up with the sheer amount of data AI requires. If the infrastructure can’t keep up, businesses face downtime, rising costs, and missed opportunities 

More servers and more power aren’t enough to support the AI data center boom. To sustain AI’s rapid growth, and ensure enterprises can fully leverage it, we need to build more modern long-haul networks – faster, denser, and more resilient than ever before. These networks are the key to seamlessly transporting massive AI workloads between hyperscale data centers. As data centers expand and rack densities soar, networks must scale with them.