Page 16: 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.

Human intuition fuels AI-driven quantum materials discovery

Many properties of the world's most advanced materials are beyond the reach of quantitative modeling. Understanding them also requires a human expert's reasoning and intuition, which can't be replicated by even the most powerful ...

AI reveals hidden features of a developing embryo model

Scientists have sought to capture the first days of how a person comes to be, by recreating those early moments in a lab via models made up of induced pluripotent stem cells, or IPSCs.

What happens when AI comes to the cotton fields

Precision agriculture uses tools and technologies such as GPS and sensors to monitor, measure and respond to changes within a farm field in real time. This includes using artificial intelligence technologies for tasks such ...

AI engineers nanoparticles for improved drug delivery

Biomedical engineers at Duke University have developed a platform that combines automated wet lab techniques with artificial intelligence (AI) to design nanoparticles for drug delivery. The approach could help researchers ...

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