MIT Technology Review: General Electric Builds an AI Workforce

I find GE is a bellwether for the future. They are an execution machine and when I see them make sea changes like this that tells me how serious AI has become. They back up their strategy with re-allocating resources, training for the future and monetize on the technology.

MIT Technology Review: General Electric Builds an AI Workforce

https://www.technologyreview.com/s/607962/general-electric-builds-an-ai-workforce/?utm_source=MIT+Technology+Review&utm_campaign=93922b9d9d-weekly_roundup_2017-06-29_edit&utm_medium=email&utm_term=0_997ed6f472-93922b9d9d-153820093&goal=0_997ed6f472-93922b9d9d-153820093&mc_cid=93922b9d9d&mc_eid=627436cb83

Quotes:

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.

GE Global Research, where Jason Nichols works, is setting up online programs that teach machine learning and symposia where scientists can explore new roles. So far, nearly 400 employees from across the company have completed GE’s certification program for data analytics, and about 50 scientists have moved into digital analytics jobs of the kind Nichols has taken on.

The technology depends on artificial intelligence to continually update itself. What’s more, if data is corrupted or missing, the company fills in the gaps with the aid of machine learning, a type of AI that lets computers learn without being explicitly programmed

Take the tiny robot, a little bigger than a Matchbox car, used to inspect working engines. Using computer vision and a variety of AI techniques, the bot can look for cracks inside plane engines by riding on top of a slowly moving fan blade.

Similar technology can be attached to a drone to find corrosion on the 200-foot-high flare stacks that burn off excess gas released at oil and gas production sites.

Parris, the software research leader, admits that some of GE’s 2,000 researchers still regard certain aspects of the new approach as a “passing fad.”

But scientists who don’t make the leap may get left behind. In January, the company laid off researchers in areas deemed peripheral to GE’s “digital industrial” strategy. That’s after creating 100 new research jobs related to AI and robotics in 2016.