Thomas G Dietterich on 2015

This AI Prediction was made by Thomas G Dietterich in 2015.

Predicted time for AGI / HLMI / transformative AI:

(Hover for explanation)Types of advanced artificial intelligence: AGI (AI that can perform many tasks at a human-level), HLMI (more advanced AI that surpasses human intelligence in specific areas), and Transformative AI (AI that could significantly impact society and the world)

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Opinion about the Intelligence Explosion from Thomas G Dietterich:

How can we prevent an intelligence explosion? We might hope that Step 2 fails—that we have already found all structural short cuts to efficient algorithms or that the remaining shortcuts will not have a big impact. But few electrical engineers or computer scientists would claim that their research has reached its limits.

Flycer’s explanation for better understanding:

Preventing an intelligence explosion is a challenge. It is hoped that all structural shortcuts to efficient algorithms have been found or that the remaining shortcuts will not have a significant impact. However, few researchers believe that their research has reached its limits.

The future of humanity with AGI / HLMI / transformative AI:

Steps 1, 2, and 3 have the potential to greatly advance scientific knowledge and computational reasoning capability with tremendous benefits for humanity. But it is essential that we humans understand this knowledge and these capabilities before we devote large amounts of resources to their use. We must not grant autonomy to systems that we do not understand and that we cannot control.

Flycer’s Secondary Explanation:

Advancements in scientific knowledge and computational reasoning can benefit humanity greatly through steps 1, 2, and 3. However, it is crucial that humans understand these capabilities before investing significant resources into them. Systems that are not understood or controllable should not be granted autonomy.

About:

Thomas G. Dietterich is a renowned computer scientist and professor who has made significant contributions to the field of artificial intelligence and machine learning. He received his Ph.D. in computer science from Stanford University in 1984 and has since held various academic positions at Oregon State University, University of Oregon, and Carnegie Mellon University.Throughout his career, Dietterich has conducted groundbreaking research in the areas of decision trees, ensemble methods, and reinforcement learning. He has also been a pioneer in the development of machine learning algorithms for ecological modeling, robotics, and natural language processing.Dietterich has received numerous awards and honors for his contributions to the field of computer science, including the ACM SIGKDD Innovation Award, the AAAI Classic Paper Award, and the IJCAI Computers and Thought Award. He is a fellow of the Association for Computing Machinery (ACM), the Association for the Advancement of Artificial Intelligence (AAAI), and the American Association for the Advancement of Science (AAAS).In addition to his research, Dietterich has also been an influential educator and mentor, training many successful researchers and practitioners in the field of machine learning. He has authored over 200 publications and served on the editorial boards of several leading journals in computer science.Today, Dietterich continues to be an active researcher and advocate for the responsible development and use of artificial intelligence. He is currently a professor emeritus at Oregon State University and a senior advisor at the Allen Institute for Artificial Intelligence.