Pain has long been subjectively measured, leading to frustrations for patients and doctors alike. Identifying neural biomarkers of pain could improve diagnosis and lead to better treatments of chronic pain conditions.
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Articles on Machine learning
Displaying 41 - 60 of 289 articles
Metaphorical black boxes shield the inner workings of AIs, which protect software developers’ intellectual property. They also make it hard to understand how the AIs work – and why things go wrong.
The shortcuts made when AI was being developed can guide society’s responses to the technology.
Artificial intelligence tools are making waves in almost every aspect of life, and astronomy is no different. An astronomer explains the history and future of AI in understanding the universe.
if a machine can ascribe intent to the events and experiences befalling it, this raises the question of identity and what it means to be aware of oneself and others
Machine learning is becoming an indispensable tool in astronomy by sorting through enormous datasets from telescopes.
Pausing AI development will give our governments and culture time to catch up with and steer the rush of new technology.
Machine learning may not seem to have much connection with wildlife, but it’s starting to play a central role in bird conservation.
Our tendency to view machines as people and become attached to them points to real risks of psychological entanglement with AI technology.
An automatic system to determine political ideology from online posts could be a powerful tool against online radicalisation.
The technology exists to build autonomous weapons. How well they would work and whether they could be adequately controlled are unknown. The Ukraine war has only turned up the pressure.
There won’t be an easy tech fix for the questions about authorship raised by ChatGPT and other text generators.
Can artificial intelligence transform the search for alien intelligence?
AI’s ability to identify ‘technosignatures’ missed by classical algorithms is an exciting step forward for radio astronomers.
AI models are increasingly being used to make important decision about people’s lives – just take Robodebt. Yet the complexity of these systems means we hardly understand them.
People often struggle to distinguish between real faces and artificial ones made by a computer.
The majority of flood-related deaths involve vehicles in water. What if flood models could warn of the risks street by street using real-time storm forecasts? Machine learning can make it possible.
To understand the potential for machine learning to transform medicine, we must go back to the controversial origins of data use in healthcare
Now that AI systems can generate realistic images and convincing prose, are creative and knowledge workers endangered or poised for productivity gains? A panel of experts says it’s not so clear-cut.
From ChatGPT to Lensa, it feels like AI is here to take over. But despite some impressive results, such systems still have plenty of limitations.
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Top contributors
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Research Fellow in AI Accountability, Queensland University of Technology
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Professor of Information Systems, Michigan State University
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Associate Professor in Behavioral Data Science, University of Technology Sydney
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Professor in Robotics, Queensland University of Technology
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Professor of Machine Learning, University of Sheffield
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Professor of Computer Science and Director of the Art & AI Lab, Rutgers University
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Professor of AI, Research Group Leader, UNSW Sydney
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Professor of Neuroscience and Mathematics, The University of Queensland
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Senior Lecturer in Applied Ethics & CyberSecurity, Griffith University
