The AI Index has gathered data about the landscape of AI startup funding in the US (see the 2018 report, page. 31). Roughly 800 AI startups received their first venture-backing in 2017, compared to roughly 150 in 2012, when the modern deep learning revolution started.
Moreover, we see that the growth rate of US AI startups seems to have been increasing since 2009, and outpacing the cumulative growth rate of all startups, which seems roughly constant in the same period. Still, in 2017, only about 6% of all new US startups were AI startups.
We now ask how this trend will compare against the same trend in China:
Will growth in the number of AI startups be faster in China versus USA in 2019-2020?
- The growth in 2019-2020 will be defined as the number of active startups January 1st 2020 divided by the number of active startups January 1st 2019.
Details about what startups were included in the count can be found on page 80 of the 2018 AI Index report. Note in particular the following helpful clarifications:
- [In the database queried] companies are removed from the database once they go public, get acquired, or get shut down, however, the funding rounds prior to the company’s removal remain in the database.
- Both Crunchbase and VentureSource have difficulty discerning AI companies that develop AI systems vs those that only deploy them. Internally, we called these AI “Makers” vs “Users”. We tested a random sample of 109 of the matched companies (this is 10% of the entire set of VentureSource matches) and found that 68 of them (or 62%) were AI “Makers”. The remaining 38% of companies in our sample, while still considered AI companies, likely did not develop the AI systems themselves.
- Our list of AI categories in Crunchbase currently favor machine learning technologies
Unfortunately the AI Index are unable to provide the underlying data for this question, but the graphs in the paper can be eyeballed.