Artificial intelligence

A new study suggests that so-called emergent abilities actually develop gradually and predictably, depending on how you measure them.

Terence Tao, who has been called the “Mozart of Mathematics,” wrote an essay in 2007 about the common ingredients in “good” mathematical research. In this episode, the Fields Medalist joins Steven Strogatz to revisit the topic.

Far from being “stochastic parrots,” the biggest large language models seem to learn enough skills to understand the words they’re processing.

Artificial intelligence learned how to generate text and art better than ever before, while computer scientists developed algorithms that solved long-standing problems.

By bringing together disparate approaches, machines can reach a new level of creative problem-solving.

Alexei Efros has spent his career learning how machines see differently from humans. Now he’s helping to bridge the gap.

To better understand how neural networks learn to simulate writing, researchers trained simpler versions on synthetic children’s stories.

Some modern image generators rely on the principles of diffusion to create images. Alternatives based on the process behind the distribution of charged particles may yield even better results.

By using “classical shadows,” ordinary computers can beat quantum computers at the tricky task of understanding quantum behaviors.