From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...

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

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...

Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...

Who is a data scientist? What does he do? What steps are involved in executing an end-to-end data science project? What roles are available in the industry? Will I need to be a good ...

It is instructive to acknowledge the complex interplay among AI, energy availability, and decarbonisation. While the AI ...

Discover how AI is revolutionizing veterinary radiology, and learn how algorithms support specialists for faster, more ...

A collaborative approach to training AI models can yield better results, but it requires finding partners with data that complements your own.

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...