In oncology, the patient state is characterized by a whole spectrum of modalities, ranging
from radiology, histology, and genomics to electronic health records. Current artificial …

The past decade has witnessed the great success of deep neural networks in various
domains. However, deep neural networks are very resource-intensive in terms of energy …

The binding and catalytic functions of proteins are generally mediated by a small number of
functional residues held in place by the overall protein structure. Here, we describe deep …

Animal genomes are folded into loops and topologically associating domains (TADs) by
CTCF and loop-extruding cohesins, but the live dynamics of loop formation and stability …

Recent breakthroughs have used deep learning to exploit evolutionary information in
multiple sequence alignments (MSAs) to accurately predict protein structures. However …

Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …

Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …

RNA molecules adopt three-dimensional structures that are critical to their function and of
interest in drug discovery. Few RNA structures are known, however, and predicting them …

Molecular classification has transformed the management of brain tumors by enabling more
accurate prognostication and personalized treatment. However, timely molecular diagnostic …

This paper argues that a range of current AI systems have learned how to deceive humans.
We define deception as the systematic inducement of false beliefs in the pursuit of some …