The chatbot industry sees more data as the answer to building a truly conversational system. But the industry may be teaching chatbots the wrong thing.
L’expertise universitaire, l’exigence journalistique
Articles sur Machine learning
Affichage de 241 à 260 de 311 articles
A branch of AI research promises to deliver computers that evolve their own software but the tech industry has yet to catch on.
Can a computer model correctly predict the results of the first round in this year’s tournament? These mathematicians think so.
Machine learning isn’t reliable enough yet – and it’s short-sighted to only train this detection tech on jihadi content.
The history of human-machine collaboration suggests that AI will evolve into a “cognitive partner” to humankind rather than as all-powerful, all-knowing, labour replacing robots.
Does big data threaten how humans explore the natural world? We need to protect our impulses to observe, compare, play, discover and love, no matter what technological capabilities are available.
Predicting human behavior is big business. But science may never be able to do so with perfect certainty.
Google’s artificial intelligence has been taught to look for planets around other stars. It’s already making new discoveries that scientists have missed.
DeepMind’s machine learning collaboration with another NHS trust (this time, it’s applying the tech to breast cancer) kicks up more questions of trust.
For future machines to be as smart as we are, they’ll need to be able to learn like we do.
The new AlphaGo Zero artificial intelligence took just days to learn to play Go from scratch, with no human intervention. It even learned strategies never seen before in human play.
Blade Runner 2049 misses modern strides in artificial intelligence, which is now capable of performing creative work alongside humans.
Creating an ethical machine learning system is no simple task, but maths can help.
Combining machine learning, artificial intelligence and autonomous vehicles could revolutionize how people with disabilities get around their communities.
Computers today are fast and powerful but they still can’t think like a human when it comes to some tasks we find easy. That’s why tech companies are turning to neuroscience for help.
Digital games now know you so well they can predict your behaviour.
The future and the past, money, technology and politics documented and imagined in fact and fiction, in an economist’s recommended reading.
How the idea of a hyper-connected society could quickly go from utopia to dystopia and why neither scenario is likely to last.
Self-driving vehicles will need to communicate and work together.
Methods stemming from decades of research on disordered materials are used to describe algorithmic phase transitions, and to design new algorithms in machine-learning problems.
Les contributeurs les plus fréquents
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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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Research Assistant Professor of Industrial & Systems Engineering, University of Southern California
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Professor in Robotics, Queensland University of Technology
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Associate Professor in Behavioral Data Science, University of Technology Sydney
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Professor of Chemistry, Connecticut College
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Head of the Marketing Innovation and Distribution Program at EMLV, Pôle Léonard de Vinci
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Professor of Marketing and Consumer Behaviour, Queensland University of Technology
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Professor of Artificial Intelligence, University of Bath
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Professor of AI, Research Group Leader, UNSW Sydney
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Professor of Computer Science, Queen Mary University of London
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Assistant Professor of Integrative Biology & Computer Science and Engineering, Michigan State University
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PhD student, Human–AI Creative Collaboration, UNSW Sydney
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Senior Lecturer in Applied Ethics & CyberSecurity, Griffith University
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Professor of Computer Science and Engineering; Director, UB Media Forensic Lab, University at Buffalo
