December 20, 2022
By Allison Gasparini, Princeton Research
A Covid-19 patient is rushed to the emergency room for trouble breathing and placed on a ventilator. The ventilator senses various conditions including the pressure in the patient’s lungs and injects the appropriate amount of oxygen to help the patient breathe normally again.
It’s a real-life scenario — and it’s one in which artificial intelligence (AI) could make all the difference. By harnessing computers to learn the patient’s needs, calculate the amount of oxygen needed, deliver it, and automatically adjust to the patient’s changing status, all on the fly, Princeton researchers hope to improve the control of ventilator activity and enhance patient outcomes. This project, a collaboration between Princeton and Google scientists, is one of many examples where Princeton researchers are pushing computers to mimic the intelligence and skills displayed in nature by humans and animals, all with the goal of building a better world.
However, for AI to realize its potential — to relieve humans from mundane tasks, make life easier, and eventually invent entirely new solutions to our problems — computers will need to surpass us at two things that we humans do pretty well: see the world around us and understand our language.
“Learning to see and learning to read are the two main things we need for the computer to do to gain knowledge,” said Jen Rexford, chair of Princeton’s computer science department and the Gordon Y.S. Wu Professor in Engineering. “We call these fields computer vision and natural language processing. These two fields have evolved independently but our faculty are bringing them together in interesting ways.”
In recent years, researchers at Princeton and beyond have made major strides in these two fields, opening up rapid progress across a variety of applications. “There’s been this huge transformation in the last decade,” said Olga Russakovsky, an assistant professor of computer science who works with computer vision. “We’re entering this second decade of things actually working.”
Read the full article in Discovery magazine from Princeton Research.