To do this, AI models are fed data from which they learn to recognize certain patterns. A trained AI model can then make a prediction or decision when given new data. For example, if you feed an ...

Here's one definition of science: it's essentially an iterative process of building models with ever-greater explanatory ...

Artificial intelligence that is as intelligent as humans may become possible thanks to psychological learning models, combined with certain types of AI.

A new MIT technique improves machine learning by removing key biased data points, boosting model performance for minority ...

The field of machine learning is traditionally divided into two main categories: "supervised" and "unsupervised" learning. In supervised learning, algorithms are trained on labeled data, where each ...

Researchers developed an AI debiasing technique that improves the fairness of a machine-learning model by boosting its performance for subgroups that are underrepresented in its training data, while ...

Machine learning models have shown promise in this regard, for example, by helping healthcare organizations provide more accurate medical diagnoses, conduct high-precision surgeries, or design ...

By combining scientific knowledge and data, Causal AI models can discover valid links that might otherwise go unnoticed.

Machine-learning models can fail when they try to make predictions for individuals who were underrepresented in the datasets ...

Imagine a world where smart machines ... might fail—for example, crossing a solid yellow line to go around a double-parked car. However, adding more machine learning models to the self-driving ...