AI Algorithm tagged posts

A trio of AI researchers at Google’s Google DeepMind, working with a colleague from the University of Toronto, report that the AI algorithm Dreamer can learn to self-improve by mastering Minecraft in a short amount of time. In their study published in the journal Nature, Danijar Hafner, Jurgis Pasukonis, Timothy Lillicrap and Jimmy Ba programmed the AI app to play Minecraft without being trained and to achieve an expert level in just nine days.

Over the past several years, computer scientists have learned a lot about how deep learning can be used to train AI applications to conduct seemingly intelligent activities such as answering questions...

How does the Earth generate its magnetic field? While the basic mechanisms seem to be understood, many details remain unresolved. A team of researchers from the Center for Advanced Systems Understanding at the Helmholtz-Zentrum Dresden-Rossendorf, Sandia National Laboratories (U.S.) and the French Alternative Energies and Atomic Energy Commission has introduced a simulation method that promises new insights into the Earth’s core.

The method, presented in the Proceedings of the National Academy of Sciences, simulates not only the behavior of atoms, but also the magnetic properties of materials...

A research team at Stanford’s Wu Tsai Neurosciences Institute has made a major stride in using AI to replicate how the brain organizes sensory information to make sense of the world, opening up new frontiers for virtual neuroscience.

Watch the seconds tick by on a clock and, in visual regions of your brain, neighboring groups of angle-selective neurons will fire in sequence as the second hand sweeps around the clock face. These cells form beautiful “pinwheel” maps, with each segment representing a visual perception of a different angle. Other visual areas of the brain contain maps of more complex and abstract visual features, such as the distinction between images of familiar faces vs. places, which activate distinct neural “neighborhoods.”

Such ...

An artificial intelligence (AI) algorithm that can detect subtle brain abnormalities that cause epileptic seizures has been developed by a UCL-led team of international researchers.

The Multicentre Epilepsy Lesion Detection project (MELD) used over 1,000 patient MRI scans from 22 global epilepsy centers to develop the algorithm, which provides reports of where abnormalities are in cases of drug-resistant focal cortical dysplasia (FCD)—a leading cause of epilepsy.

FCDs are areas of the brain that have developed abnormally and often cause drug-resistant epilepsy. The condition is typically treated with surgery, however identifying the lesions from an MRI is an ongoing challenge for clinicians, as MRI scans in FCDs can look normal.

To develop t...