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2019 AI Index Report Offers Comprehensive Look at State of AI Worldwide

Stanford University's Human-Centered Artificial Institute (HAI) recently released the 2019 edition of its Artificial Intelligence (AI) Index Report (PDF), a 209-page report that takes an in-depth look at the state of AI in nine areas, including research and development, education, technical performance, the economy, autonomous systems and societal considerations, among others.

According to HAI, this year's report offers three times the data as last year's index. To go along with the report and to help the industry and public analyze all the data available in the report, HAI has made available two interactive tools: an interactive Global AI Vibrancy tool and the arXiv Monitor, a "full paper search engine tool" that lets you "automatically and continuously track technical metrics from papers published on arXiv. AI Progress monitor is intended to provide a high-level overview of AI progress across task, dataset, category, technical metrics and other relevant categories." HAI also makes the raw data that goes into the Vibrancy tool available here.

As for this year's study's findings, some major highlights include:

  • The time needed to train a "large image classification system on cloud infrastructure" fell during the last 18 months, from approximately three hours in October 2017 to 88 seconds in July 2019. (During the same time period, the report states that the cost to train such a system has dropped similarly.)
  • "Prior to 2012, AI results closely tracked Moore's Law, with compute doubling every two years. Post-2012, compute has been doubling every 3.4 months."
  • The fastest growth in AI hiring over the past five years has taken place in Singapore, Brazil, Australia, Canada and India.
  • AI (and related topics) is now the most popular specialization among Ph.D. computer science candidates.
  • 60 percent of global AI patent activity is from North America. Europe and East Asia are now almost even.
  • 32 percent of journal citations are credited to East Asia.
  • In the United States, San Jose/Sunnyvale, Calif., offers the most AI-related jobs, followed by San Francisco, Seattle, Boston/Cambridge, New York City/New Jersey, Chicago and Southern California. Most of these jobs are focused on machine learning-related skills (58 percent).
  • Deep learning jobs are growing the fastest, with a 12x growth rate between 2015 and 2018.
  • Singapore has submitted the most deep learning papers per capita in the last three years, followed by Switzerland, Australia and Israel. When it comes to total number, it is the United States in the lead, followed by China, the United Kingdom and Germany.
  • AI is most often mentioned on the earnings calls of companies in the non-energy minerals sector, followed by consumer durables, health technology, consumer non-durables and industrial services.
  • TensorFlow is the most popular and fastest-growing AI-related "GitHub" star.

Much, much more information can be found online here.

About the Author

Becky Nagel is the vice president of Web & Digital Strategy for 1105's Converge360 Group, where she oversees the front-end Web team and deals with all aspects of digital strategy. She also serves as executive editor of the group's media Web sites, and you'll even find her byline on PureAI.com, the group's newest site for enterprise developers working with AI. She recently gave a talk at a leading technical publishers conference about how changes in Web technology may impact publishers' bottom lines. Follow her on twitter @beckynagel.

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