The Volume of Activity metrics capture engagement in AI activities by academics, corporations, entrepreneurs, and the general public. Volumetric data ranges from the number of undergraduates studying AI, to the percent of female applicants for AI jobs, to the growth in venture capital funding of AI startups.
The Technical Performance metrics capture changes in AI performance over time. For example, we measure the quality of question answering and the speed at which computers can be trained to detect objects.
The 2018 AI Index adds additional country-level granularity to many of last year’s metrics, such as robot installations and AI conference attendance. Additionally, we have added several new metrics and areas of study, such as patents, robot operating system downloads, the GLUE metric, and the COCO leaderboard. Overall, we see a continuation of last year’s main takeaway: AI activity is increasing nearly everywhere and technological performance is improving across the board. Still, there were certain takeaways this year that were particularly interesting. These include the considerable improvement in natural language and the limited gender diversity in the classroom.
Below is some related thought leadership.
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