Artificial intelligence engineer Andrew Ng, founder of the Google Brain research lab and former chief scientist of Baidu, once built a computer vision system using 350 million images. But when he asked the audience at a recent manufacturing conference how much data they used in their systems, the majority of attendees replied around 50 images or fewer.

The solution to this issue, Ng explained at Fortune's Brainstorm A.I. conference in Boston on Monday, lies in data-centric A.I., which allows manufacturers to utilize machine learning even with small data sets. That's where Ng's startup, Landing AI, comes in.

While consumer software can operate under one monolithic search engine or A.I. system, most other industries need their systems to adapt to their unique needs. For example, every hospital has its own way of coding electronic health records, so one A.I. model cannot oversee all records across all hospitals. Landing AI’s tech allows manufacturers to teach and build sophisticated A.I. models instead of hiring tens of thousands of engineers to do it for them.

Just on November 8, Ng announced that Landing AI closed a $57 million Series A funding round led by McRock Capital. Key investors included Intel Capital, Samsung Catalyst Fund, and Insight Partners.

Ng is optimistic that A.I. can create and preserve jobs, especially given its potential in the manufacturing industry. In terms of big breakthroughs for A.I. expected in the next five to seven years, he's looking ahead to a shift away from the consumer software internet industry—and toward a focus on data-centric A.I. over the software or neural networks themselves.

“What we’re missing is a more systematic engineering discipline of treating good data that feeds A.I. systems,” Ng said. “I think this is the key to democratizing access to A.I.”