Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...

In a future perhaps not too far away, artificial intelligence and its subfield of machine learning (ML) tools and models, ...

Government-funded academic research on parallel computing, stream processing, real-time shading languages, and programmable ...

This project implements a complete pipeline for in-kernel machine learning inference on network packets, with automated design space exploration inspired by Karpathy's autoresearch.

Abstract: The analysis of satellite images has attracted significant research interest due to its numerous applications and unparalleled scalability in Earth observation (EO). Although artificial ...

The association between recurrent pregnancy loss (RPL) and environmental exposure has attracted increasing attention. However, associations between RPL and metal exposure in northwestern China ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

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The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...