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TagMichael I. Jordan

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Danaylov: Right on Technology, Wrong on AI

Danaylov's confidence in the future of AI super-intelligence is exaggerated

Our future is determined by the stories we tell ourselves. So says futurist Nikola Danaylov in his online series exploring the years and decades to come for humanity. In our previous posts, we introduced you to Danaylov and examined his perspective on science. Now we will turn to his treatment of technology and artificial intelligence. The Technology Story Like his perspective on science, Danaylov brings a balanced understanding to technology. Technology “is not an end-in-itself,” he says. “Instead, technology is merely a means-to-an-end, a tool.”  Jonathan Bartlett has also written about technology as a tool. In 2019, Elon Musk and Jack Ma shared a stage to debate the future of technology and artificial intelligence. Here’s what Bartlett had to say about it: For Ma, Read More ›

Shot of Corridor in Working Data Center Full of Rack Servers and Supercomputers with Pink Neon Visualization Projection of Data Transmission Through High Speed Internet.
Shot of Corridor in Working Data Center Full of Rack Servers and Supercomputers with Pink Neon Visualization Projection of Data Transmission Through High Speed Internet.

AI Researcher: Stop Calling Everything “Artificial Intelligence”

It’s not really intelligence, says Berkeley’s Michael Jordan, and we risk misunderstanding what these machines can really do for us

Computer scientist Michael I. Jordan, a leading AI researcher, says today’s artificial intelligence systems aren’t actually intelligent and people should stop talking about them as if they were: They are showing human-level competence in low-level pattern recognition skills, but at the cognitive level they are merely imitating human intelligence, not engaging deeply and creatively, says Michael I. Jordan, a leading researcher in AI and machine learning. Jordan is a professor in the department of electrical engineering and computer science, and the department of statistics, at the University of California, Berkeley. Katy Pretz, “Stop Calling Everything AI, Machine-Learning Pioneer Says” at IEEE Spectrum (March 31, 2031) Their principal role, he says, is to “augment human intelligence, via painstaking analysis of large Read More ›