Choose appropriate methods or models for a given problem, using information from observation or knowledge of the system being studied. Employ quantitative methods, mathematical models, statistics, and ...

Math offers us lots of problem-solving techniques that help us distill the essence of questions. Many of us will be familiar with reading a math problem, and needing to figure out what's being asked, ...

The Parallel-R1 framework uses reinforcement learning to teach models how to explore multiple reasoning paths at once, ...

Ever stared at a math problem feeling completely lost, even when you've memorised all the formulas? Or maybe you've wondered why certain math rules even exist? The true secret weapon that unlocks ...

Back in 2019, a group of computer scientists performed a now-famous experiment with far-reaching consequences for artificial intelligence research. At the time, machine vision algorithms were becoming ...

Add articles to your saved list and come back to them any time. Children in the early years of primary school will be taught to use phonics to sound out words as they learn to read and encouraged to ...

While effective, this approach has notable limitations: it heavily relies on human annotations, making it costly and difficult to scale; models only mimic humans, struggling to surpass human reasoning ...

Hallucination is fundamental to how transformer-based language models work. In fact, it's their greatest asset.

At one point during this year’s SXSWedu—a slick Austin conference heavy on marketing for education technology—an audience member stood and asked a panel of Texas lawmakers the question most in the ...