A step toward safe and reliable autopilots for flying
A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.
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A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.
The inaugural SERC Symposium convened experts from multiple disciplines to explore the challenges and opportunities that arise with the broad applicability of computing in many aspects of society.
By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds.
The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.
A new multimodal technique blends major self-supervised learning methods to learn more similarly to humans.
Researchers develop an algorithm that decides when a “student” machine should follow its teacher, and when it should learn on its own.
Selecting the right method gives users a more accurate picture of how their model is behaving, so they are better equipped to correctly interpret its predictions.
The machine-learning algorithm identified a compound that kills Acinetobacter baumannii, a bacterium that lurks in many hospital settings.
This machine-learning method could assist with robotic scene understanding, image editing, or online recommendation systems.
A new machine-learning model makes more accurate predictions about ocean currents, which could help with tracking plastic pollution and oil spills, and aid in search and rescue.