Page 2: 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.

Rating community resilience with a deep learning framework

An understanding of community resilience and risk analysis is vital when it comes to protecting civilians and infrastructure from natural hazards, such as hurricanes or earthquakes. Artificial intelligence is an efficient ...

One man, his dog, and ChatGPT: Australia's AI vaccine saga

Desperate to help his sick dog, one Australian man went down the ultimate ChatGPT research hole, using artificial intelligence to design a personalized experimental treatment and finding top scientists to administer it.

Designing proteins by their motion, not just their shape

Proteins are far more than nutrients we track on a food label. Present in every cell of our bodies, they work like nature's molecular machines. They walk, stretch, bend, and flex to do their jobs, pumping blood, fighting ...

AI tool predicts wildfire danger faster than current systems

A wildfire forecasting system powered by artificial intelligence (AI) could help detect dangerous fire conditions earlier and reduce the cost of wildfire response, according to new research from Te Whare Wānanga o Waitaha, ...

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