AI is only overhyped because AI companies are currently using most of their GPUs to race towards super intelligence and not for customer application.

Most people think data centres run flat-out, 24/7. They don’t. As Tyler H. Norris points out on the Power & Policy blog, the common mix-up between “load factor” and “capacity utilization” makes it look like facilities run near 100% of their limit. In reality, redundancy, maintenance, and spiky workloads keep them well below peak. That gap matters. It shapes how we build infrastructure and how we can use energy more wisely.

From energy efficiency to automation, the modern data center is governed by physical laws, operational truths, and strategic imperatives. These ten principles strip away complexity to reveal the design rules driving scale, performance, and sustainability.

AI’s explosive growth demands a power source as resilient as the digital systems it fuels. SMRs offer clean, constant, on-site energy - bridging the gap between performance, sustainability, and scale. For data centers, they could be the ultimate unlock.

As data centers expand globally, the energy challenge grows louder. Geothermal power offers a rare combination: clean, steady, around-the-clock energy that’s ideal for AI infrastructure. In a world demanding both performance and sustainability, it might be the smartest energy bet yet.

AI Is the New Climb
In an internal memo, Shopify CEO Tobi Lütke reframes AI not as a futuristic bonus, but a baseline skill. Embracing AI as a collaborator - across every level of an organization - is now essential to stay relevant. In this new era of speed, hesitation equals obsolescence

AI’s explosive growth is running headfirst into the limits of legacy power systems. As demand for high-speed compute outpaces grid timelines, the gap between energy supply and AI innovation—what we call the “Watt-Bit Spread” - is widening. This post explores how utilities, hyperscalers, and policymakers must rethink energy infrastructure to meet the moment.

As AI reshapes industries, the network is becoming the backbone of performance. From flexible cloud workloads to generative AI and massive AI factories, each use case demands tailored infrastructure. Ethernet works for everyday cloud, but cutting-edge AI needs high-performance fabrics like NVIDIA’s Spectrum-X and InfiniBand to scale effectively and future-proof operations.

As AI evolves, the real challenge lies in bringing intelligence to physical systems in the real world. This article explores the breakthroughs in reliability, security, and scalability that are making edge AI viable and why it's the key to unlocking the next industrial transformation.

This shift isn’t just about industry - it’s laying the groundwork for what comes next. As we move toward intimate interfaces and sensory AI, technology is becoming more human in how it sees, hears, and responds. Scaling edge AI is the infrastructure layer enabling devices to anticipate, adapt, and orchestrate our lives - effortlessly and invisibly.

Hyperscaler offtakers like AI firms and cloud giants are driving a new era of energy infrastructure—one defined by unprecedented scale, speed, and compute demand. This article breaks down what they need, why traditional utilities can’t keep up, and how energy developers must evolve to capture the opportunity.

Deglobalisation, emerging market growth, and new tech-driven alliances are disrupting the traditional global order. As power decentralizes from the U.S. and China, a multipolar economic landscape is taking shape—creating new risks, new alliances, and massive new opportunities.

AI’s Energy Footprint: Challenge or Catalyst?
As AI’s hunger for compute grows, its impact on energy systems is accelerating. Data centers could soon double global power demand—posing short-term pressure on grids, but also unlocking innovation in energy efficiency and sustainability. The race is on to balance power and progress.