Blog

Only 8% of energy data is used today. Dan Jeavons explains how Orbital, Applied Computing’s foundation model for energy, is unlocking the rest, helping redefine the future of energy intelligence in the AI age.

Explores how AI is commercializing intelligence and reshaping work, advocating an emphasis on ethics, human oversight, and continuous upskilling so productivity gains augment, and not sideline, human judgment.

Explores how physics-grounded AI combines machine learning with natural laws to boost accuracy, cut downtime, and unlock scalable innovation in manufacturing and energy.

Explores how Physics-Informed Neural Networks (PINNs) embed physics into AI, enabling smart buildings to cut costs, boost renewables, and reduce emissions through accurate, real-time energy optimisation.

Explores how physics-informed AI improves energy forecasting in manufacturing by embedding thermodynamic laws into machine learning models, and highlights how this approach drives efficiency, lowers emissions, and supports ESG goals across hybrid energy systems.

This summer has marked a step-change for Applied Computing as we strengthen the leadership behind Orbital, our foundation model for energy operations. We’re pleased to welcome Stephen Fowler as Senior Advisor - Refining, Petrochemicals and Biofuels.

Explores how AI can transform buildings from exorbitant energy consumers into dynamic, efficient systems, helping cut HVAC energy use, lower emissions, and unlock financial gains for early adopters in real estate and infrastructure.

Explores how AI-powered hyperspectral satellite systems can detect methane leaks globally, offering a breakthrough tool for curbing and regulating one of the most potent greenhouse gases.

Explores how right-sized models, quantization and intentional prompting strategies can cut LLM energy use by 50-90% with minimal accuracy loss, turning everyday prompts into measurable ESG wins.