Chase is the CEO of ProAI, an AI-powered platform providing customized tools and advisory to help businesses start, fund and scale. In an increasingly volatile business landscape, data-driven ...

Water demand forecasting is an indispensable element in the sustainable management of water resources, as growing populations and climatic uncertainties intensify the pressure on water supplies.

Traditional long-term forecasting models are no longer sufficient as electrification, DER growth, EV adoption, extreme weather events and new large loads introduce unprecedented complexity. The future ...

The AI insights highlight where accuracy is improving or deteriorating, enabling proactive responses. Private LLM-generated explanations help teams focus on insights that matter most. Likewise, ...

Pre-trained foundation models are making time-series forecasting more accessible and available, unlocking its benefits for smaller organizations with limited resources. Over the last year, we’ve seen ...

Legacy load forecasting models are struggling with ever-more-common, unpredictable events; power-hungry AI offers a solution.

On Tuesday, the peer-reviewed journal Science published a study that shows how an AI meteorology model from Google DeepMind called GraphCast has significantly outperformed conventional weather ...

Researchers from the Netherlands’ Utrecht University and EKO Instruments Europe developed a novel machine learning and all-sky imaging-based short-term solar irradiance forecasting. The model is based ...

For decades, morning weather reports have relied on the same kinds of conventional models. Now, weather forecasting is poised to join the ranks of industries revolutionized by artificial intelligence.

The landscape of demand forecasting, data science and machine learning is rapidly evolving, as companies seek innovative approaches to handle the intricate intersection between technology and consumer ...