Page 7: 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.

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 ...

Identifying severe weather hazards further in the future with AI

An artificial intelligence (AI) tool built by the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR) can help forecasters look further into the future as they work to identify the potential ...

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