Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

Discover how AI and machine learning are transforming electric utilities—boosting grid reliability, resilience, and ...

Perovskites are a class of materials with great potential as solar cells. UC Davis materials scientists have used machine learning to explore the wide variety of perovskite formulas to find those best ...

Researchers have determined how to build reliable machine learning models that can understand complex equations in real-world situations while using far less training data than is normally expected.

Quantum hardware is starting to hit a wall that has little to do with flashy new qubit designs and everything to do with how precisely those qubits are tuned. As devices scale, tiny errors in charge ...

The massive datasets that power machine learning algorithms and systems are complex, noisy, and vulnerable to various kinds of errors, contamination, and adversarial corruptions. As data science and ...

A new technical paper titled “Post-hoc Uncertainty Learning using a Dirichlet Meta-Model” was published (preprint) by researchers at MIT, University of Florida, and MIT-IBM Watson AI Lab (IBM Research ...

Report from wireless connectivity trade body outlines frameworks and priorities needed to scale intelligent Wi-Fi through artificial intelligence and machine learning without industry fragmentation.

Machine learning is a multibillion-dollar business with seemingly endless potential, but it poses some risks. Here's how to avoid the most common machine learning mistakes. Machine learning technology ...