Page 9: Research news on Artificial intelligence

Artificial intelligence, as a technique, refers to computational methods that enable machines to perform tasks that typically require human cognitive capabilities, such as perception, reasoning, learning, and decision-making. Core AI techniques include search and optimization algorithms, symbolic reasoning and knowledge representation, probabilistic inference, and machine learning approaches such as supervised, unsupervised, and reinforcement learning. These techniques often rely on statistical modeling, function approximation, and gradient-based optimization to construct models that generalize from data. AI techniques are implemented in software frameworks, integrated into pipelines for training, validation, and deployment, and are evaluated using task-specific performance metrics and robustness assessments.

AI shapes the design of the electron-ion collider

Artificial intelligence and machine learning are shaping major design and research decisions for the planned Electron-Ion Collider (EIC), a next-generation nuclear physics research facility that will collide electrons with ...

AI generates first complete models of proteins in motion

Many drug and antibody discovery pathways focus on intricately folded cell membrane proteins. When molecules of a drug candidate bind to these proteins, like a key going into a lock, they trigger chemical cascades that alter ...

A roadmap for safer, explainable protein-design AI

Protein language models are artificial intelligence tools which help engineer proteins with useful properties, including completely new structures never seen before in nature.

AI cuts wildlife tracking time from months to days

Artificial intelligence can dramatically speed up the painstaking work of tracking wildlife with remote cameras, cutting analysis time from months or even a year to just days while producing nearly the same scientific conclusions ...

page 9 from 40