On the same day that the AlphaFold2 paper was published, Baker and his colleagues released an independent, freely accessible alternative that predicts protein structure with similar accuracy to ...

Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

Hyperparameters Hyperparameters are configurations used to control the training process of machine learning models. Unlike model parameters, which are derived from the training data during the ...

Based on the headlines these days, it is obvious to see the rapidly emerging role that AI and machine learning play in nearly every facet of our lives. The evolution of ChatGPT has made AI a household ...

Applying machine learning to find the properties of atomic pieces of geometry shows how AI has the power to accelerate discoveries in maths. Applying machine learning to find the properties of atomic ...

ML is a subset of artificial intelligence (AI) that allows computers to learn without being explicitly programmed. In simple terms, machine learning (ML) is a subset of artificial intelligence (AI) ...

Applying machine learning to find the properties of atomic pieces of geometry shows how AI has the power to accelerate discoveries in maths. Mathematicians from Imperial College London and the ...

(Nanowerk News) Mathematicians from Imperial College London and the University of Nottingham have, for the first time, used machine learning to expand and accelerate work identifying ‘atomic shapes’ ...