AI Research Rankings 2019: Insights from NeurIPS and ICML, Leading AI Conferences

Introduction

Methodology

AI Research Rankings 2019

AI Research Rankings 2019—Top 40 Global Organizations (Industry & Academia) Leading in AI Research in 2019
AI Research Rankings 2019 — Top 20 Regions Leading in AI Research in 2019
AI Research Rankings 2019 — Top 20 Countries Leading in AI Research in 2019
AI Research Rankings 2019 — Top 20 American Universities Leading in AI Research in 2019
AI Research Rankings 2019 — Top 20 Global Universities Leading in AI Research in 2019
AI Research Rankings 2019 — Top 20 Companies Leading in AI Research in 2019

Further Analysis

AI Research Rankings 2019 — Academia vs. Industry
AI Research Rankings 2019 — Top 150 Words in 2200 Paper Titles at NeurIPS 2019 and ICML 2019
AI Research Rankings 2019 — Top 30 Countries by Per Capita Publication Index
AI Research Rankings 2019 — Treemap of Top 40 Organizations Leading in AI Research
The Herfindahl index calculation: si is the market share (percents are used as whole numbers, as in 75 instead of 0.75), and N is the number of participants.
  • An H below 100 indicates a highly competitive industry.
  • An H below 1,500 indicates an unconcentrated industry.
  • An H between 1,500 to 2,500 indicates moderate concentration.
  • An H above 2,500 indicates high concentration.

Discussion: Who’s Ahead in AI?

  • Two major events happened in AI in 2016: in March, Google’s AlphaGo became the first computer program to beat a 9-dan Go professional, Lee Sedol, without handicaps; in October, President Obama’s administration released a strategy on future directions and considerations for AI called Preparing for the Future of Artificial Intelligence.
  • In China, these two events created a “Sputnik moment” which helped convince the Chinese government to prioritize and dramatically increase funding for artificial intelligence (see Kai-Fu Lee’s AI Superpowers).
  • In response, in July 2017 the Communist Party of China set 2030 as the deadline for an ambitious AI goal: it called for China to reach the top tier of AI economies by 2020, achieve major new breakthroughs by 2025, and become the global leader in AI by 2030. The strategy became known as the New Generation Artificial Intelligence Development Plan, and it has spurred many policies and billions of dollars of investment in research and development from ministries, provincial governments, and private companies.
  • Certain think tanks, such as CNAS, have argued that China’s AI strategy reflected the key principles from the Obama administration report — now it is China adopting them, instead of the United States.
  • This copying strategy isn’t new: to quote Peter Thiel’s Zero to One, “The Chinese have been straightforwardly copying everything that has worked in the developed world: 19th-century railroads, 20th-century air conditioning, and even entire cities. They might skip a few steps along the way — going straight to wireless without installing landlines, for instance — but they’re copying all the same.”
  • 2017 is precisely the year when we started tracking the state of AI research, so we established China’s baseline summarized in the following chart showing that the United States had an 11x lead in the total Publication Index over China:
Top 10 Countries Leading in AI in 2017: the USA had an 11x lead over China
  • In 2019 the United States has a 7x lead (USA — 1260.2, China — 184.5), so the gap is clearly narrowing. Furthermore, the analysis by the Allen Institute for Artificial Intelligence found that China has steadily increased its share of authorship of the top 10% most-cited papers: China’s share was at 26.5% in 2018, not far behind the United States at 29%.

Dataset

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Gleb Chuvpilo

Gleb Chuvpilo

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Serial Entrepreneur & Investor | AI @ MIT & MBA @ Wharton | Thundermark, Peter Thiel, Y Combinator, Palantir, Goldman Sachs