At Google’s cloud computing conference in San Francisco last week, CEO Sundar Pichai mused on his company’s commitment to openness in artificial intelligence.
“We create open platforms and share our technology because it helps new ideas get out faster,” Pichai said. Then he name-checked TensorFlow, the machine-learning software Google developed and uses internally. The company open-sourced the code in 2015, and it has since been downloaded more than 15 million times. “We created TensorFlow to make it possible for anyone to use AI,” Pichai said.
Such homilies to openness have become standard from the large tech companies competing intensely to develop AI technology. Facebook, Amazon, and Microsoft have all, like Google, released software their own engineers use for machine learning as open source. All, including to some extent famously secretive Apple, encourage their AI researchers to publish their latest ideas---helping the companies recruit the brightest faculty and grad students from universities.
At the same time, these proponents of AI openness are also working to claim ownership of AI techniques and applications. Patent claims related to AI, and in particular machine learning, have accelerated sharply in recent years. So far, tech companies haven’t converted those patents into lawsuits and legal threats to thwart rivals. But should AI patents become corporate weapons, the current openness around AI research and ideas could end, likely hampering research.
A National Bureau of Economic Research study released this month shows US filings related to machine learning, the technology driving the current AI boom, increasing rapidly. “We’ve seen a huge explosion of patenting activity in AI and machine learning, and I see this exponential growth continuing,” says Michael Webb, a Stanford researcher and coauthor of the study.
In 2010, there were 145 US patent filings that mentioned machine learning, the study says. In 2016, there were 594—a figure that’s incomplete, since the US Patent and Trademark Office only makes filings public 18 months after they have been registered. (Webb and his colleagues gathered their data in February.) Patent filings mentioning neural networks, a machine-learning technique, climbed to 485 in 2016, from 94 in 2010.