The new capabilities are designed to enable enterprises in regulated industries to securely build and refine machine learning ...

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.

Vice President, AI & Quantum Computing, Paul Smith-Goodson, dives in as a few weeks ago, a new set of MLCommons training results were released, this time for MLPerf 2.1 Training, which the NVIDIA ...

Microsoft announced on-device training of machine language models with the open source ONNX Runtime (ORT). The ORT is a cross-platform machine-learning model accelerator, providing an interface to ...

To a large extent, supervised ML is for domains where automated machine learning does not perform well enough. Scientists add supervision to bring the performance up to an acceptable level.

He thinks the platform will be especially helpful for researchers trying to develop machine learning models with limited training data, he says. “It’s the next level of machine learning for ...

By checking the machine learning model’s performance on this validation dataset, developers can ensure that the model is able to generalize its learning beyond the training data, avoiding ...

A machine learning approach leverages nuclear microreactor symmetry to reduce training time when modeling power output ...