Beware those who say it is a solved problem.
Academic rigour, journalistic flair
Articles on Machine learning
Displaying 161 - 180 of 297 articles
On October 23 Google announced that it built a quantum computer thousands of times faster than classic computers. This could have immense impacts on finance, cryptography and other fields.
Google’s Smart Compose feature is meant to help deal with the deluge of email, but does it increase the pressure to respond quicker?
Algorithm-based apps can recommend clothes based on what other people have worn, but they have a long way to go before they understand fashion.
If artificial intelligence can amaze us with its prowess, there are many areas where it falls flat when compared to human and animal intelligence.
Artificial Intelligence can perpetuate existing social imbalances in a harmful manner. Can this undesirable scenario be avoided?
Creativity isn’t the only route to discovery – automated analysis of huge amounts of data works too.
A key element of the battle between truth and propaganda has nothing to do with technology. It has to do with how people are much more likely to accept something if it confirms their beliefs.
Artificial intelligence holds great promise for medicine, but safeguards are needed to ensure it does not harm patients.
There are potential issues with any use of machine learning in policing. But if used in the right way, it could go a long way towards more effective policing.
Using machine learning and natural language processing, researchers are developing an algorithm that can distinguish between real and fake news articles.
CC BY-NC-ND4.87 MB (download)
Quantum machine learning is an exciting, rapidly growing field.
To be sustainable, the NHS needs to invest in AI and other advanced technologies.
The idea that robots will take our jobs is not radically new – but artificial intelligence is now completely reorganising the global economy. Australia must act now to keep up with the world.
Hardware could exploit the properties of scattered light so that computations happen at high speed and with low power consumption.
Instead of trying to explain the mystifying mathematics behind how algorithms work, this researcher started looking at how they actually ‘see’ the world we live in.
Prominent thinkers exaggerating the potential or danger of artificial intelligence are pushing us towards a new AI winter.
A proposed bill would force tech companies to tell users how much their data is worth. But how can a single number capture data’s power to predict your actions or sway your decisions?
Finding out more about how the brain works could help programmers translate thinking from the wet and squishy world of biology into all-new forms of machine learning in the digital world.
Research has found ways to detect deepfakes through flaws that can’t be fixed easily by the fakers.
Top contributors
-
Research Fellow in AI Accountability, Queensland University of Technology
-
Professor of Information Systems, Michigan State University
-
Associate Professor in Behavioral Data Science, University of Technology Sydney
-
Professor in Robotics, Queensland University of Technology
-
Research Assistant Professor of Industrial & Systems Engineering, University of Southern California
-
Head of the Marketing Innovation and Distribution Program at EMLV, Pôle Léonard de Vinci
-
Associate research scientist Cambridge Judge Business School and lecturer GEM, Grenoble École de Management (GEM)
-
Assistant Professor of Integrative Biology & Computer Science and Engineering, Michigan State University
-
Professor of Machine Learning, University of Sheffield
-
Professor of Marketing and Consumer Behaviour, Queensland University of Technology
-
Professor of Computer Science and Director of the Art & AI Lab, Rutgers University
-
Professor, ESCP Business School
-
Associate Professor
-
Professor of Neuroscience and Mathematics, The University of Queensland
-
Professor of AI, Research Group Leader, UNSW Sydney
