In our age of brain tickling nose swabs, there is a renewed interest in fast, accurate, and non-invasive tests for diagnosing illnesses. We’ve all probably experienced a Q-tip going just a little too far at some point in the last couple of years. Well researchers from University of South Florida, Cornell, and 10 other institutions are working with the National Institutes of Health to develop AI that could make medical diagnoses based on a person’s speech.
Process Automation has long been the domain of large businesses seeking to produce their TPS reports faster or blast emails to potential customers. These business processes aren’t the only examples though. When Tony Stark tells JARVIS to paint his suit red or divert power to thrusters, that’s process automation. It may seem like there’s a wide gulf between sending automated emails and managing energy consumption of a powered suit of armor, but they’re closer than you think. As technology evolves, these types of automations become closer to reality.
A cyborg soldier controlled entirely by AI. A cybernetically enhanced human roaming the streets doing all kinds of jobs for money. These sound like plots out of a movie or video game. That’s because they are! But don’t let fiction fool you. These developments are coming to the real world sooner than you think.
We’ve all heard of self-driving cars, but how about self-flying planes? Earlier this month, DARPA held a contest called AlphaDogfight (https://www.wired.com/story/dogfight-renews-concerns-ai-lethal-potential/). The goal was to see if an AI could be developed to pilot an F-16 in a dogfight situation better than a human can. Teams from several companies competed and eventually the winner battled a highly trained human Air Force pilot in a simulated dog fight. An AI developed by Heron Systems defeated the other AIs and went on to defeat the human pilot as well. It wasn’t just a lucky shot either. There were five test battles and Heron’s AI shot down the human pilot in all five.
If you attended my Introduction to Machine Learning class, or our March Madness Challenge (which we sadly won’t get to play out), you might have some ideas about how we can use AI to fight COVID-19. At a high level, machine learning is giving the computer many data samples so that it learns to identify something (training) then having the computer look at new data and identify it. My first thought was perhaps we could use lung imaging to diagnose the virus faster. We could train algorithms with CT scans of healthy lungs and scans of COVID-19 infected lungs. The algorithm should quickly be able to learn the differences and identify people with the virus at a high level of accuracy.