A machine learning (ML) model might retrain or drift between quarterly operational syncs. This means that, by the time an ...

There are three critical areas where companies most often go wrong: data preparation and training, choosing tools and specialists and timing and planning.

We’ve blown past the Turing test, but "indistinguishable" isn’t "equivalent." Psychology must continue to learn from people, ...

Maternal mortality remains disproportionately high in low-income and middle-income countries, where pyramidal health systems ...

Princeton has firmly established its presence at the forefront of AI research — including transformative work in humanities scholarship.

With a 6–3 majority, the Supreme Court struck down President Donald Trump’s tariffs, but the ruling lacks full consensus on ...

In a new study, University of Rhode Island Ph.D. graduate Kyle McElroy and Marine Affairs Professor Austin Becker explore the role of data and biases, as well as the challenges and decision-making ...

AI models are trained on massive amounts of data. But that training doesn’t do much good without what’s known as “reinforcement learning,” a process that involves human experts teaching models the ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

As you explore how to create new opportunities with AI, it’s crucial to first take a close look at your data architecture.

For Joe Powell (pictured), chief digital officer at Gallagher Bassett, that framing reshaped how the organization approached innovation across its claims operation, from frontline adjuster workflows ...