Michelle Lee, PhD, unpacks how physical AI that integrate scientific reasoning with the wet lab will accelerate biological discovery.

The team used an AI method known as equation discovery to develop a model to simulate the interactions between small eddies—circular, vortex-like currents—and large-scale ones. These interactions are ...

AI systems are beginning to produce proof ideas that experts take seriously, even when final acceptance is still pending.

Print Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal reasoning.

Published in Nature, the study details the first large-scale demonstration of a photonic Ising machine operating without the ...

A Cornell University fellow develops strategies to extract more than correlations from algorithms’ predictions.

Estimating the number of triangles in a graph is a fundamental problem and has found applications in many fields. This ...

Coding can help students understand the building blocks of world languages, and it provides an authentic way to tell stories.

A new technique from Stanford, Nvidia, and Together AI lets models learn during inference rather than relying on static ...

We've all heard the best approach to solve a problem is to "sleep on it." It turns out there may be more truth to this adage ...

Existing technology is being upcycled and deployed in new ways as companies seek to measure more data, more accurately.