Intelligence agencies have a limited number of trained human analysts looking for undeclared nuclear facilities, or secret military sites, hidden among terabytes of satellite images. But the same sort of deep learning artificial intelligence that enables Google and Facebook to automatically filter images of human faces and cats could also prove invaluable in
Topic: Machine Learning
The Advances in Machine Learning to Improve Scientific Discovery at Exascale and Beyond (ASCEND) project aims to use deep learning to assist researchers in making sense of massive datasets produced at the world's most sophisticated scientific facilities. Deep learning is an area of machine learning that uses artificial neural networks to enable self-learning
Whenever you move your hand or finger or eyeball, the brain sends a signal to the relevant muscles containing the information that makes this movement possible. This information is encoded in a special way that allows it to be transmitted through neurons and then actioned correctly by the relevant muscles. Exactly how this code works is something of a
Physicists have applied the ability of machine learning algorithms to learn from experience to one of the biggest challenges currently facing quantum computing: quantum error correction, which is used to design noise-tolerant quantum computing protocols. In a new study, they have demonstrated that a type of neural network called a Boltzmann machine can be
In 2016, more than three billion passwords were harvested from breaches by criminals in the U.S., according to Shape Security."Criminals exchange passwords on the Dark Web and use a technique called credential stuffing to apply passwords to targeted web domains and automatically attempt authentication for tens of thousands of compromised passwords," Routh
Machine learning (ML) may well be The Next Big Thing, but it has yet to register in mainstream enterprise adoption. While breathless prognosticators proclaim 50% of organisations lining up to magically transform themselves in 2017 with ML, more canny observers put the number closer to 15%. And that's being generous.
Machine learning for network intrusion detection is an area of ongoing and active research (see references in  for a representative selection), however nearly all results in this area are empirical in nature, and despite the significant amount of work that has been performed in this area, very few such systems have received nearly the widespread support