Non-reciprocal interactions between particles enable the regulation of dynamic states. Most systems, whether companies, ...

New research from Johns Hopkins shows A.I. models fall short in reading social dynamics, posing risks for real-world technologies like self-driving cars.

Our new Gemini Robotics model brings Gemini 2.0 to the physical world. It enables robots that are interactive, capable of ...

Humans significantly outperform AI models in interpreting dynamic social interactions, a skill critical for technologies like ...

Scientists usually use a hypergraph model to predict dynamic behaviors. But the opposite problem is interesting, too. What if ...

Hopkins research shows AI models fall short in predicting social interactions, a skill critical for systems to navigate the ...

Despite rapid advancement, AI models still struggle at identifying how people interact with each other.

Asymmetric interactions between molecules may serve as a stabilizing factor for biological systems. A new model by ...

As described in the paper, LLNL researchers developed a novel model to better capture the complexity of protein-membrane interactions. Their approach is based on dynamic density functional theory ...

These interactions are spatially and temporally dynamic and can be challenging to disentangle. Relationships between members of an ecological community can be classified within two broad ...

Humans are better than current AI models at interpreting social interactions and understanding social dynamics in moving scenes. Researchers believe this is because AI neural networks were inspired by ...