AI Index 2019 Assesses Global AI Research, Investment, and Impact
Leaders in the AI community came together to release the 2019 AI Index report on 11 December, an annual attempt to examine the biggest trends shaping the AI industry, breakthrough research, and AI’s impact to society.
It also examines trends such as AI hiring practices, private investment, AI research contributions by nation, researchers leaving academia for industry, and how much AI plays a role in specific industries. The report also notes strides in the reduction of the amount of time it takes to train AI systems and computing costs, two of the biggest hindrances to AI adoption rates.
“In a year and a half, the time required to train a large image classification system on cloud infrastructure has fallen from about 3 hours in October 2017 to about 88 seconds in July 2019,” the report reads.
- AI is the most popular area for computer science PhD specialization, and, in 2018, 21% of graduates specialized in machine learning or AI.
- From 1998 to 2018, peer-reviewed AI research grew by 300%.
- In 2019, global private AI investment was more than $70 billion, with startup investments at $37 billion, mergers and acquisitions at $34 billion, initial public offerings at $5 billion, and minority stakes at $2 billion. Autonomous vehicles led global investment in the past year ($7 billion), followed by drug and cancer, facial recognition, video content, fraud detection, and finance.
- China now publishes as many AI journal and conference papers per year as Europe, having passed the US in 2006.
- More than 40% of AI conference paper citations are attributed to authors from North America, and about 1 in 3 come from East Asia.
- Singapore, Brazil, Australia, Canada, and India experienced the fastest growth in AI hiring from 2015 to 2019.
- The vast majority of AI patents filed between 2014 and 2018 were filed in nations such as the US and Canada, and 94% of patents are filed in wealthy nations.
- Between 2010 and 2019, the total number of AI papers on arXiv increased 20 times.
The report is compiled by the Stanford Human-Centered AI Institute in collaboration with people from OpenAI. It originated in 2016 as part of AI 100, a century-long Stanford study of AI’s progress and impact.
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