Artificial intelligence has been around for decades, and is much more than just ChatGPT. Here’s a rundown of some lesser known AI applications.
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Articles on Machine learning
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Traditionally dominated by the use of centralised, resource-intensive servers, machine learning is being democratised with the growth of “TinyML”, distinguished by its small size and low cost.
Artificial intelligence is everywhere, and the tech industry is racing along to develop ever more powerful AIs. Three scholars look ahead to the next chapter in this technological revolution.
Research suggests AI could diagnose depression from health records or even social media posts. And it could overcome GP bias when it comes to prescribing medications.
AI systems will accelerate the pace of war.
It’s the fourth most popular website in the world, but our new study shows toxic commentary can still thrive on Wikipedia. There’s a lot at stake if too many editors are driven away.
Researchers fed an advanced AI algorithm with satellite photographs to see if it could identify areas of poverty and it interpreted the data through abstract images.
The explosion of generative AI tools like ChatGPT and fears about where the technology might be headed distract from the many ways AI affects people every day – for better and worse.
Students often use generative AI tools for engaged learning. They have a critical and nuanced understanding of these tools.
This new last Beatles song, enabled in part by AI, demonstrates the importance of the profound and lasting connections between the four musicians.
A tangle of silver nanowires may pave the way to low-energy real-time machine learning.
The Turing test, first proposed in 1950 by Alan Turing, was framed as a test that could supposedly tell us whether an AI system could ‘think’ like a human.
Effective implementation of existing law can protect us from the risks posed by AI algorithms.
An AI model shows that building collapses in Lagos are location specific, and soil testing can help to check them.
AI poses a variety of ethical conundrums, but the NASA teams working on Mars rovers exemplify an ethic of care and human-robot teamwork that could act as a blueprint for AI’s future.
People can trust each other because they understand how the human mind works, can predict people’s behavior, and assume that most people have a moral sense. None of these things are true of AI.
The science of human consciousness offers new ways of gauging machine minds – and suggests there’s no obvious reason computers can’t develop awareness.
A new machine learning model can pinpoint anomalies in sports results – whether from match fixing, strategic losses or poor player performance. It could be a useful tool in the fight against cheating.
The seeds of the current commotion over AI were laid years ago.
Fraud was up 25% in the UK in 2021/22.
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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Research Assistant Professor of Industrial & Systems Engineering, University of Southern California
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Head of the Marketing Innovation and Distribution Program at EMLV, Pôle Léonard de Vinci
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Associate research scientist Cambridge Judge Business School and lecturer GEM, Grenoble École de Management (GEM)
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Assistant Professor of Integrative Biology & Computer Science and Engineering, Michigan State University
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Professor of Machine Learning, University of Sheffield
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Professor of Marketing and Consumer Behaviour, Queensland University of Technology
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Professor of Computer Science and Director of the Art & AI Lab, Rutgers University
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Professor, ESCP Business School
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Associate Professor
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Professor of Neuroscience and Mathematics, The University of Queensland
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Professor of AI, Research Group Leader, UNSW Sydney
