A Stanford-led group of leading AI thinkers called the AI100 has launched an index that will provide a comprehensive baseline on the state of artificial intelligence and measure technological progress in the same way the gross domestic product and the S&P 500 index track the U.S. economy and the broader stock market. They have produced a 101 page AI Index 2017 report.
This report aggregates a diverse set of data, makes that data accessible, and includes discussion about what is provided and what is missing. Most importantly, the AI Index 2017 Report is a starting point for the conversation about rigorously measuring activity and progress in AI in the future.
The number of AI papers produced each year has increased by more than 9x since 1996. Introductory AI class enrollment at Stanford has increased 11x since 1996.
AI conference attendance numbers show that research focus has shifted from symbolic reasoning to machine learning and deep learning
Despite shifting focus, there is still a smaller research community making steady progress on symbolic reasoning methods in AI. The performance of AI systems on the object detection task in the Large Scale Visual Recognition Challenge (LSVRC) Competition.
Error rates for image labeling have fallen 2.5% from 28.5% to below 2.5% since 2010. Despite the difficulty of comparing human and AI systems, it is interesting to catalog credible claims that computers have reached or exceeded human-level performance. Read more from nextbigfuture.com…
thumbnail courtesy of nextbigfuture.com