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The AI Index 2018 Annual Report

The AI Index 2018 Annual Report

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SUMMARY

The mission of the report is to ground the discussion about AI in data: Based on a multitude of indicators, the report paints a rich picture of the growth and penetration of AI throughout the world.

For instance, it looks at the number of published scientific papers on AI (currently standing at 60,000 per year) by region, by topic and by sector. Taking a look at the topics, machine learning, neural networks and computer vision are the dominant areas.

Other important indicators are the enrollment in AI courses within academic institutions (strong growth), participation in large and small AI conferences (explosive growth), AI startup investment (in 2018 at around 5 bn$ in the U.S.),  number of AI job openings (especially machine learning and deep learning generate a lot of new jobs), or the number of patents filed in the field of AI (US is the leading region).

In addition to the level of activities the report is also looking at the indicators for technical performance like network training time for image detection (going down from 60 minutes to only a few minutes within the last 18 months), parsing metrics (first step to understand natural language), machine translation, question answering and so on. Almost all technical performance indicators show a strong improvement in the very recent period.

Finally, the report provides a number of other measures like the AI vibrancy index and a comparative table of recent government initiatiives in the U.S., China and Europe.

OUTLINE

Introduction to the AI Index 2018 Report

Overview

Industry

   Startups / Investment

   Jobs

   Patents

   AI Adoption Survey

   Earnings Calls

   Robot Installations

Open Source Software
   
Public Interest

Technical Performance
 
Other Measures
  
Human-Level Performance Milestones

What’s Missing?

DETAILS

Overview

Researchfinder Rating
4 out of 5 stars
Title
The AI Index 2018 Annual Report
Region
Global
Published
Dec. 15, 2018
Publisher
Stanford University
Author(s)
Yoav Shoham, Raymond Perrault, Erik Brynjolfsson, Jack Clark, James Manyika, Juan Carlos Niebles, Terah Lyons, John Etchemendy, Barbara Grosz, Zoe Bauer
Price
FREE
Language
ENGLISH

Content

Number of Pages
94
Number of Tables
2
Number of Exhibits
61
Topics
ai
Tags
AI, AI index, AI performance, AI regulation, artificial intelligence, global, machine vision, Stanford University
Author(s)
Yoav Shoham, Raymond Perrault, Erik Brynjolfsson, Jack Clark, James Manyika, Juan Carlos Niebles, Terah Lyons, John Etchemendy, Barbara Grosz, Zoe Bauer
Methodology
The AI Index 2018 Annual Report is grounded in empirical data reaching from metrics that capture engagement in AI activities by academics, corporations, entrepreneurs, and the general public to technical performance data that capture, for instance, the quality of question answering by computers or the speed at which computers can be trained to detect objects. The report uses also qualitative metrics like the level of government activity in AI.
EVALUATION

The report shows the fast and furious development of AI activities and performance across a multitude of indicators.

A multifaceted picture of AI emerges from the data. However, the report remains somewhat superficial as all of these indicators and measures are presented without much interpretation and little comparative analysis. A reader may ask what all this data means and which conclusions to draw. Many of the contributors to the report are renowned authorities in the field of AI. It would have been interesting to read their conclusions based on the wealth of data that are presented.

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