Latest news, trends and insights from the world of AI in energy
Every supplier will show you an accuracy figure. On its own it tells you almost nothing. These are the six criteria that decide whether a corrosion prediction system survives contact with an integrity department, and the question to ask about each one.
Anomaly detection and remaining useful life answer different questions, and most demonstrations quietly show you the first while talking about the second. Six criteria for telling them apart, with the question to put to each supplier.
Which model a platform uses is the question everyone asks and the one that matters least, because it will change twice before your contract is up. Six criteria that survive the model of the month, with the question to ask about each.
At BeAI Energy we don't build black-box models. We embed 20+ physics equations (Arrhenius, Nernst, Marcus Theory) directly into neural network architectures, achieving >95% prediction accuracy with full explainability.
A look back at the AI trends that shaped renewable energy in 2025 and what to expect in 2026: from predictive maintenance to smart grid optimization.
Traditional corrosion models fail in hydrogen and ammonia environments, dropping from 95% to below 50% effectiveness. CorrosionAI bridges this gap with physics-informed AI for the energy transition.
Introducing CorrosionAI, a Physics-Informed Graph Neural Network (PI-GNN) that integrates Marcus Theory, Arrhenius equations, and flow correlations to predict industrial corrosion with R² = 96.3% accuracy.
Exploring how artificial intelligence is reshaping industries and human collaboration in the modern era.
How machine learning algorithms are revolutionizing equipment maintenance and reducing downtime in industrial operations.
We are BeAI Energy, an AI-native company driving organizations towards a smarter future. Watch our launch video and discover our mission to transform energy and industry through human-centered AI.
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