Researchers developed an attention-based graph neural network that reconstructs particle collision tracks in fifty ...
Accurate molecular energy prediction relies on representations of atomic species and three-dimensional structure. However, repeated aggregation over local neighborhoods can make it difficult for ...
Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...
Engineers have uncovered an unexpected pattern in how neural networks -- the systems leading today's AI revolution -- learn, suggesting an answer to one of the most important unanswered questions in ...
Artificial intelligence is becoming increasingly vital to everyday activities across diverse sectors of society, from AI assistants to autonomous vehicles to healthcare. But the way these systems are ...
An AI safety researcher has published a formal argument that the alignment problem is not a specification problem — it is a geometry problem. Stuart Armstrong, co-founder of Aligned AI and a former ...
Researchers at DeepMind, the artificial intelligence research division of Alphabet Inc., have created software that’s able to solve difficult geometry proofs that are often used to test the brightest ...
Penn Engineers have uncovered an unexpected pattern in how neural networks — the systems leading today’s AI revolution — learn, suggesting an answer to one of the most important unanswered questions ...
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