Artificial Intelligence in the Second Machine Age
The advancement of artificial intelligence (AI) in this second machine age is, and will continue to be, the defining feature of this age. With smart machines everything changes. This department tracks what is happening on the AI front and how this technology is changing every area of our lives.
A group of researchers from the UK and the US have used machine learning techniques to successfully predict earthquakes. Although their work was performed in a laboratory setting, the experiment closely mimics real-life conditions, and the results could be used to predict the timing of a real earthquake.
An interdisciplinary team of researchers at the University of California San Diego has developed a method to identify the molecular structures of natural products that is significantly faster and more accurate than existing methods. The method works like facial...
Using advanced machine learning, a cross disciplinary team of University of California San Diego researchers developed technology that mined Twitter to identify entities illegally selling prescription opioids online. Between June and November 2015, some 619,937 tweets containing the keywords codeine, Percocet, fentanyl, Vicodin, Oxycontin, oxycodone and hydrocodone were collected.
Researchers have demonstrated how to decode what the human brain is seeing by using artificial intelligence to interpret fMRI scans from people watching videos, representing a sort of mind-reading technology.
New method allows on-the-fly analysis of how catalysts change during reactions, providing crucial information for improving performance.
Team led by University of Texas at Austin researchers shines in Multimodal Brain Tumor Segmentation Challenge. Primary brain tumors encompass a wide range of tumors depending on the cell type, the aggressiveness, and stage of tumor.
Engineers create atomically thin superlattice materials with precision. Control is a constant challenge for materials scientists, who are always seeking the perfect material — and the perfect way of treating it — to induce exactly the right electronic or optical activity required for a given application.
Progress on the way to smart nanomachines: LMU chemists have modified the synthesis of a molecular motor so as to reduce the speed of its light-driven rotation, thus permitting the researchers to analyze the mechanism of motion in complete detail.
A recent study, led by Professor Kyoung Jin Choi in the School of Materials Science and Engineering at UNIST has introduced a new advanced energy harvesting system, capable of generating electricity by simply being attached to clothes, windows, and outer walls of a building.
Neural networks carry out chemical simulations in record time. Researchers at the Universities of Vienna and Göttingen have succeeded in developing a method for predicting molecular infrared spectra based on artificial intelligence. These chemical “fingerprints” could only be simulated by common prediction techniques for small molecules in high quality. With the help of the new technology, which is based on neuronal networks similar to the human brain and is therefore capable of learning, the team led by Philipp Marquetand from the Faculty of Chemistry at the University of Vienna was able to carry out simulations that were previously not possible.
AI Department Head