Early this spring as the pandemic began accelerating, AJ Venkatakrishnan took genetic data from 10,967 samples of the novel coronavirus and fed it into a machine. The Stanford-trained data scientist did not have a particular hypothesis, but he was hoping the artificial intelligence would pinpoint possible weaknesses that could be exploited to develop therapies. He was awed when the program reported back that the new virus appeared to have a snippet of DNA code -- "RRARSAS" -- distinct from its predecessor coronaviruses. This sequence, he learned, mimics a protein that helps the human body regulate salt and fluid balance. Venkatakrishnan, director of scientific research and partnerships at AI start-up Nference, wondered whether this change might allow the virus to act as a kind of Trojan horse. Could this explain its high infection and transmission rates?

While the human brain can process only so much information at a time, machines are whizzes at finding subtle patterns in huge amounts of data, and they are being deployed against covid-19 -- the disease caused by the coronavirus -- in ways only imagined in the past. Data scientists are aiming AI at some of the coronavirus's biggest mysteries -- why the disease looks so different in children vs. adults, what makes some people "superspreaders" while others don't transmit the virus at all -- and other, lesser questions we have made little headway in understanding.