The illustration above describes a global population of ~5k researchers whose papers were accepted to the leading 2019 conference in deep neural nets. To be precise they looked at ~700 authors of a randomly chosen subset of papers. There is also a more select population of individuals who gave presentations at the meeting. This is certainly not the entire field of AI, but a reasonable proxy for it.
Global AI talent tracker:
For its December 2019 conference, NeurIPS saw a record-breaking 15,920 researchers submit 6,614 papers, with a paper acceptance rate of 21.6%, making it one of the largest, most popular, and most selective AI conferences on record.
1. The United States has a large lead over all other countries in top-tier AI research, with nearly 60% of top-tier researchers working for American universities and companies. The US lead is built on attracting international talent, with more than two-thirds of the top-tier AI researchers working in the United States having received undergraduate degrees in other countries.
2. China is the largest source of top-tier researchers, with 29% of these researchers having received undergraduate degrees in China. But the majority of those Chinese researchers (56%) go on to study, work, and live in the United States.
3. Over half (53%) of all the top-tier AI researchers are immigrants or foreign nationals currently working in a different country from where they received their undergraduate degrees.Prediction: PRC share in all 3 categories will increase in coming decades as their K12, undergraduate, and graduate schools continue to improve, and their high-tech economy grows much larger. See Ditchley Foundation meeting: World Order today.
Using conference papers as the filter probably misses a lot of world class work (especially implementation at scale) that is going on in PRC at tech companies. Note in the list below the only Chinese institutions are Tsinghua and Beijing universities. But I would be surprised if those were the main accumulation of top AI talent in China, compared to large tech companies.