A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

More information: Zhenghao Yin et al, Experimental quantum-enhanced kernel-based machine learning on a photonic processor, Nature Photonics (2025). DOI: 10.1038/s41566-025-01682-5 ...

Simulating tiny robots that could one day be used for targeted drug delivery and cellular-level disease interventions.

A UK biotech firm spent years gathering genetic data that has uncovered 1 million previously unknown microbial species and billions of newly identified genes – but even this trove of data may not be e ...

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a ...

In recent times, with the incremental demand for fully autonomous systems, research interests are observed in learning machine-based intelligent, self-organizing, and evolving controllers. In this ...

Multidisciplinary AI- and physics-driven modeling of the viral fusion process has enabled the discovery of an orally available drug inhibiting infection with multiple coronaviruses.

Advancements in artificial intelligence (AI) are dramatically transforming the field of protein science, offering powerful ...

Machine Learning Department at CMU Research Services Pittsburgh, Pennsylvania 64,191 followers One of the world's preeminent institutions for artificial intelligence and machine learning research ...

I am a computational biologist interested in interpretable machine learning for genomics and health care. Interpretable ...

So now, suddenly, when faced with terms like “hyperparameter tuning” and “unsupervised learning,” a 50-year-old brain initiates its own version of a denial-of-service attack in these courses.

Some of the most encouraging results for reaction-enhancing catalysts come from one material in particular: tin (Sn). While ...