Study shows how machine learning could predict rare disastrous events, like earthquakes or pandemics
When it comes to predicting disasters brought on by extreme events (think earthquakes, pandemics or “rogue waves” that could destroy coastal structures), computational modeling faces an almost insurmountable challenge: Statistically speaking, these events are so rare that there’s just not enough data on them to use predictive models to accurately forecast when they’ll happen next.
Biophysicists have developed control software that optimizes how fluorescence microscopes collect data on living samples. Their control loop, used to image mitochondrial and bacterial sites of division in detail, is released as an open source plug-in and could inspire a new generation of intelligent microscopes.
Researchers at the University of New Hampshire have harnessed artificial intelligence to accelerate the discovery of new functional magnetic materials, creating a searchable database of 67,573 magnetic materials, including 25 previously unrecognized compounds that remain magnetic even at high temperatures.