When Jason Nichols joined GE Global
Research in 2011, soon after completing
postdoctoral work in organic chemistry
at the University of California, Berkeley,
he anticipated a long career in chemical research. But after four years creating materials and systems to treat
industrial wastewater, Nichols moved
to the company’s machine-learning lab.
This year he began working with augmented reality. Part chemist, part data
As part of its shift toward high-tech businesses, the
125-year-old company is threading artificial intelligence
throughout its operations, starting with its scientists.
By Elizabeth Woyke
scientist, Nichols is now exactly the type of hybrid employee crucial to the future
of a company working to inject artificial intelligence into its machines and indus-
Fifteen years ago, GE’s machine operators and technicians monitored its aircraft engines, locomotives, and gas turbines by listening to their clanks and whirs
and checking their gauges. Today, the company uses AI to do the equivalent,
even predicting failures in advance. By marshaling this technology, GE hopes to
become one of the world’s top software providers by 2020, a quest that amped up
in 2011 with a $1 billion initiative to collect and analyze sensor data from machines.
Creating smarter models via AI is the next step in the company’s strategy—one
that it hopes will give it an advantage over longtime rivals like Siemens and soft-