The Institute of Artificial Intelligence at Stanford University recently released its 2019 AI Index Report. The report covers a wide range of areas, and the following are some of the main sections extracted from the report, all raw data and charts can be found in the Google Cloud Drive.
Research on artificial intelligence is increasing, with the number of peer-reviewed AI papers increasing by more than 300 percent between 1998 and 2018.
China now publishes as many AI journals and conference papers each year as Europe and more than the United States. However, the “weighted citation impact” of United States publications is still 50 per cent higher than that of Chinese publications.
The number of participants in AI meetings continues to increase significantly.
Over a year and a half, the time required to train a large image classification system on a cloud infrastructure decreased from about three hours in October 2017 to about 88 seconds in July 2019;
In the SuperGLUE and SQuAD 2.0 benchmarks, some of the extensive natural language processing (NLP) classification tasks progressed very quickly; Performance is still low.
In the U.S., the percentage of AI jobs increased from 0.3% in 2012 to 0.8% in 2019. The demand for artificial intelligence is growing, especially in high-tech services and manufacturing.
Globally, investment in AI start-ups continues to grow steadily. From $1.3B raised in 2010 to $40.4B in 2018 ($37.4B as of November 4), the funds grew at an average annual growth rate of more than 48%.
Self-driving cars (AVs) have gained the largest share of global investment over the past year, at $7.7B (9.9 per cent of the total), followed by drugs, cancer and treatment ($4.7B, 6.1%), facial recognition ($4.7B, 6.0%), video content ($3.6B, 4.5%) and fraud detection and finance ($3.1B, 3.9%)).
Fifty-eight percent of large companies surveyed said they adopted AI in at least one function or business unit in 2019, up from 47 percent in 2018.
At the graduate level, artificial intelligence has quickly become the most popular major among Doctor already computer science students in North America, with twice as many students as the second most popular major (security/information assurance). In 2018, more than 21% of Ph.D.s in computer science will focus on artificial intelligence/machine learning.
Fairness and interpretability are considered the most frequently cited ethical challenges in the 59 Ethics AI principles.