We're sorry but this page doesn't work properly without JavaScript enabled. Please enable it to continue.
Feedback

7th HLF – Lecture: Grand Challenges in AI: Unfinished Agenda

Formal Metadata

Title
7th HLF – Lecture: Grand Challenges in AI: Unfinished Agenda
Title of Series
Number of Parts
24
Author
License
No Open Access License:
German copyright law applies. This film may be used for your own use but it may not be distributed via the internet or passed on to external parties.
Identifiers
Publisher
Release Date
Language

Content Metadata

Subject Area
Genre
Abstract
In this talk I will discuss some Grand Challenges of AI, successes of the past 30 years, and the unfinished agenda for the 21st century. In 1988, I presented a list of unsolved open Grand Challenge Problems in AI, as part of the Presidential Address of American Association for AI (https://www.aaai.org/ojs/index.php/aimagazine/article/view/950). Since then some of the problems have been solved. The World Champion Chess Machine challenge was settled in 1996 when IBM Deep Blue (developed by Hsu, Anantharaman, Campbell, Hoane et al) defeated the then reigning World Champion of Chess, Boris Kasparov (https://en.wikipedia.org/wiki/Deep_Blue_(chess_computer). The Accident Avoiding Car (Driverless Car) challenge was decided in 2005 when Stanford’s Stanley headed by Sebastian Thrun and CMU’s Sandstorm headed by Red Whittaker were among the five cars to successfully complete the challenge (https://en.wikipedia.org/wiki/DARPA_Grand_Challenge_(2005). The Challenge to demonstrate Understanding of Science Textbooks by taking an Exam was successfully demonstrated recently in 2019. https://www.wired.com/2016/02/the-best-ai-still-flunks-8th-grade-science/ and http://bit.ly/aristo90. Starting from a failing performance in 2016, Peter Clark, Oren Etzioni and team at Allen Institute for AI developed a system that answered over 90% of the questions correctly in the NY Regents Science Exams. The Unfinished Agenda for 21st Century includes: Discovery of a Major Mathematical Result by AI; Summarization of Media (Books, Talks, Music and Movies); Remote Repair in Space; Encyclopedia on Demand; Provide the Right Information to the Right People at the Right Time in the Right Language; Self-Reproducing Robots; Any Language to Any Language Translation among the top 100 languages with less than 5% error; and Any Spoken Language to Any Spoken Language (Speech To Speech) Translation among the top 100 languages with less than 5% error. Each of the above seemingly realistic problems would require significant breakthroughs and fundamental advances in AI and all other subfields of Computer Science and Technology. The opinions expressed in this video do not necessarily reflect the views of the Heidelberg Laureate Forum Foundation or any other person or associated institution involved in the making and distribution of the video.