Nature Index 2020 Artificial Intelligence

A look at one of the most rapidly advancing and controversial topics in scientific research.

As revenues and research output soar in the field of AI, global competition between the United States, China and Europe heats up.

Collaborations on AI-related papers in journals tracked by the Nature Index reveal country strengths.

From radio galaxies to robots, these trailblazers are at the forefront of AI advances.

To ensure that AI meets its potential as a transformative tool, it must be developed by a truly representative research community, say Tess Posner and Li Fei-Fei.

From facial recognition to drug discovery, these emerging technologies are the ones to watch.

Sebastian Seung outlines his quest for convenient and natural interaction with machines.

AI can decide which papers are worth reading, and condenses them to make the literature more accessible.

AI-generated summaries of three articles selected from a data set of 175 Springer Nature publications.

A description of the terminology and methodology used in this supplement, and a guide to the functionality available free online at nature.com/nature-index/.

A data-driven approach to medical research is helping to shed new light on cancer and other heterogeneous diseases.

An innovative young company, Standigm Inc., is creating cutting-edge AI technology for discovering and developing new therapeutics.

The Japanese Government is driving the development of AI-based innovations that aim to ease the healthcare burden and enable professionals to deliver better quality face-to-face care.

A young mathematical school in Beijing is contributing to real-world solutions through AI innovations.

Researchers apply machine learning to the arts and sciences to help decode ancient languages and improve manufacturing processes.

By facilitating cross-disciplinary research, the University of Copenhagen's SCIENCE AI Centre brings machine learning to new arenas.

For the first time in the world, THE INVERSE SCATTERING PROBLEM, an unsolved problem in the history of applied mathematics, has been solved analytically.

An ankle sensor for he elderly is just one example of a disruptive AI technology being fostered by a venture capital company in Japan.

Supported by the positive spiral of research and development at Hitachi’s Lumada Data Science Lab, top data scientists are developing artificial intelligence solutions to help solve society's challenges.

The Technical University of Munich (TUM) is ahead of the game when it comes to AI and robotics. And that includes the societal side as much as the technological.

Tsinghua Shenzhen International Graduate School has been driving rapid progress in AI visualization and imaging, with diverse real-world applications.

Two new technologies being developed by Fujitsu Laboratories are making AI more transparent and robust.

A university lab is transforming Hongo, Tokyo, into a hub for innovation in artificial intelligence.

On a mission to mine its wealth of data for clinical insights, the Tokyo Medical and Dental University has established itself as Japan’s new hub for AI-driven clinical data science.

AI experts, in different stages of their careers, are offered generous research funding by two leading institutions.