The idea that artificial intelligence can “reason” is more intuitive than ever. But intuitions can be wrong, and the science is far from settled.

A technique that allows developers to shrink powerful artificial intelligence models into cheaper, more efficient systems has ...

For companies that want control over data, model behavior and fine-tuning, that smaller footprint may be more important than ...

From accelerated computing and simulation to data operations, open-source tooling, validation engineering, and continuous ...

Applied Intuition believes the next competitive edge in artificial intelligence won’t come from building bigger models, but ...

The capabilities of large AI systems are constantly improving, but they consume a great deal of energy during training and ...

For most of modern science, the first stages of a research idea were largely invisible. A researcher noticed an anomaly, ...

Considering the price and ease of use plotters/vinyl cutters made by the biggest brands on the block, could Vevor be a decent ...

Researchers at The University of Manchester have developed a new computational approach to help identify two-dimensional materials that may host unusual quantum behavior. The work, published in ...

Large language models can write essays, solve math problems, and generate computer code, but it’s not fully understood how they do it. Researchers can observe the billions of parameters inside these ...

Abstract: In machine fault diagnosis, conventional data-driven models trained by empirical risk minimization (ERM) often fail to generalize across domains with distinct data distributions caused by ...

Abstract: Disentangled Representation Learning (DRL) aims to learn a model capable of identifying and disentangling the underlying factors hidden in the observable data in representation form. The ...