The ultimate objective of biomolecular modeling is to provide molecular dynamics simulations with quantum-mechanical accuracy at system sizes and timescales relevant to realistic applications. Current approaches often face trade-offs among efficiency, accuracy, scalability, and transferability. Machine learning force fields have successfully bridged the gap between some of these factors, but achieving truly general molecular simulations remains elusive. Kabylda et al. report a pretrained neural network and universal pairwise force fields that demonstrated robust performance in nanosecond-long simulations of small biomolecular systems, high transferability throughout biochemical space, and scalability to hundreds of thousands of atoms. Although many biomolecular processes are currently beyond reach, the proposed method is a promising step toward the long-standing goal of accurate large-scale modeling across extended chemical space.

The work of researchers at the University of Wyoming was featured in a year-end review of content produced by a prestigious international journal. In 2017, the video team for the journal Science created nearly 180 videos on various topics. The most-viewed entry for the entire year accompanied a special package on artificial intelligence and featured Science staff writer Paul Voosen. The basis for the video, "A.I. detectives are cracking open the black box of deep learning," came largely from the work of a team of researchers, two of whom are associated with UW: Department of Computer Science Associate Professor Jeff Clune and graduate student Anh Nguyen, who now is an assistant professor at Auburn University. Science's video explores information from a video, titled "Deep Visualization Toolbox" (www.youtube.com/watch?v AgkfIQ4IGaM) and a paper, "Understanding neural networks through deep visualization," both including contributions from Clune and Nguyen, along with Cornell University's Jason Yosinski and Hod Lipson, and California Institute of Technology's Tom Fuchs.

UC San Diego is creating an outdoor site where it can test fly unmanned aerial vehicles, which are rapidly coming into common use by everyone from police investigating crime scenes to scientists looking for archaeological remains. The aerodrome will be a net cage that will be 30 feet high and roughly 50 feet long and wide, making it similar to a facility that's being built at the University of Michigan, a leader in drone research. San Diego chipmaker Qualcomm gave UC San Diego $200,000 to create the flight center, which is meant to help promote the school's quickly expanding research in robotic systems. The campus recently announced that it will begin testing driverless vehicles on university roads next year, using golf carts to deliver packages. The research will begin about the time that engineers start to extensively use the aerodrome.