Research in the field of machine learning and AI, now a key technology in practically every industry and company, is far too voluminous for anyone to read it all. This column, Perceptron (previously Deep Science), aims to collect some of the most relevant recent discoveries and papers -- particularly in, but not limited to, artificial intelligence -- and explain why they matter.

This week in AI, a team of engineers at the University of Glasgow developed "artificial skin" that can learn to experience and react to simulated pain. Elsewhere, researchers at DeepMind developed a machine learning system that predicts where soccer players will run on a field, while groups from The Chinese University of Hong Kong (CUHK) and Tsinghua University created algorithms that can generate realistic photos -- and even videos -- of human models.

According to a press release, the Glasgow team's artificial skin leveraged a new type of processing system based on "synaptic transistors" designed to mimic the brain's neural pathways. The transistors, made from zinc-oxide nanowires printed onto the surface of a flexible plastic, connected to a skin sensor that registered changes in electrical resistance.

Image Credits: University of Glasgow

While artificial skin has been attempted before, the team claims that their design differed in that it used a circuit built into the system to act as an "artificial synapse" -- reducing input to a spike in voltage. This sped up processing and allowed the team to "teach" the skin how to respond to simulated pain by setting a threshold of input voltage whose frequency varied according to the level of pressure applied to the skin.

The team sees the skin being used in robotics, where it could, for example, prevent a robotic arm from coming into contact with dangerously high temperatures.

Tangentially related to robotics, DeepMind claims to have developed an AI model, Graph Imputer, that can anticipate where soccer players will move using camera recordings of only a subset of players. More impressively, the system can make predictions about players beyond the view of the camera, allowing it to track the position of most --  if not all -- players on the field fairly accurately.