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 ...

Pushing against years of scepticism, an analysis suggests quantum computers may offer real advantages for running machine ...

Machine learning is rapidly emerging as a pivotal tool in plant tissue culture research, offering innovative approaches to optimise protocols, predict morphogenic responses, and streamline ...

Explore how AI in high-throughput screening improves drug discovery through advanced data analysis, hit identification and ...

Gain a deeper understanding of artificial intelligence with Machine Learning Fundamentals: Principles and Applications. This course explores core concepts and practical uses of supervised and ...

The integration of machine learning techniques into microstructure design and the prediction of material properties has ushered in a transformative era for materials science. By leveraging advanced ...

NPU-equipped MCUs open the door to optimized edge AI in systems ranging from wearable health monitors to physical AI in ...

Machine learning, a type of artificial intelligence, has many applications in science, from finding gravitational lenses in the distant universe to predicting virus evolution. Hubble Space Telescope ...

The IAEA hosts a webinar focused on the strategic integration of Artificial Intelligence (AI) in Waste Management and Nuclear Decommissioning. This session highlights how AI technologies such as ...

Read more about AI can’t deliver climate gains without strong governance and capacity building on Devdiscourse ...

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper publishing April 22 in the Cell Press ...