David Silver of Google DeepMind thinks AIs that ‘learn by experience’ are the future of AI – but maybe not in particle colliders or nuclear arsenals
Read article: The pros and cons of reinforcement learning in physical science
Some highly intelligent human mathematicians certainly seem to think so, as Margaret Harris reports from the maths-and-computer-science-focused Heidelberg Laureate Forum
Read article: Are we heading for a future of superintelligent AI mathematicians?
This podcast explains what happens when 66,000 research papers are used as training data
Read article: Artificial intelligence predicts future directions in quantum science
Honor Powrie looks at the perils and possibilities of AI for physicists
Read article: Garbage in, garbage out: why the success of AI depends on good data
AI model analyses electrocardiogram traces to flag patients at high risk of structural heart disease
Read article: Deep-learning model outperforms cardiologists in identifying hidden heart disease
Tara Shears discusses how the fields of AI and physics could help advance each other
Read article: How AI can help (and hopefully not hinder) physics
Optical microscopy technique shows promise for diagnostics
Read article: Deep learning classifies tissue for precision medicine
AI4S will meet the need for high-quality journals dedicated to artificial intelligence
Read article: New open-access journal AI for Science aims to revolutionize scientific discovery
A multidisciplinary research team shares tips on how to mitigate bias in artificial intelligence models used in radiology
Read article: AI algorithms in radiology: how to identify and prevent inadvertent bias
The first generative AI tool to be integrated into a clinical workflow eases the creation of radiography reports
Read article: Generative AI speeds medical image analysis without impacting accuracy
