Mind Matters Reporting on Natural and Artificial Intelligence

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jelleke-vanooteghem-8Arw-cEpt-Q-unsplash

The Unexpected and the Myth of Creative Computers – Part II

Robert J. Marks talks with Larry L. Linenschmidt of the Hill Country Institute about the misattribution of creativity and understanding to computers. This is Part 2 of 2 parts. Other Larry L. Linenschmidt podcasts from the Hill Country Institute are available at HillCountryInstitute.org. We appreciate the permission of the Hill Country Institute to rebroadcast this podcast on Mind Matters. Show Read More ›

Happy African American guy in VR glasses

Gee-Whiz Tech and AI Reality – Part I

Robert J. Marks talks with Larry L. Linenschmidt of the Hill Country Institute about the nature and limitations of artificial intelligence from a computer science perspective. This is Part 1 of 2 parts. Other Larry L. Linenschmidt podcasts from the Hill Country Institute are available at HillCountryInstitute.org. We appreciate the permission of the Hill Country Institute to rebroadcast this podcast Read More ›

sport cyclisme velo tour de France

I Am Giving Up Cycling

It’s just not worth it if a machine can beat me

It’s not that I cannot cycle or that I don’t like to or that I’m not good at it (for a human). But just the other day, as I pedaled along, I was passed by a motorcycle. Its speed was incredible! I appeared to be pedaling in place as the machine zoomed into the distance. In that moment, it became all too clear that my days as a meaningful human were ending. The machine was my better. Okay. That is not true. I am not going to quit cycling. And, being passed by a motorcycle—a machine we built purposely to go faster than anything our two legs can achieve—is not a meaningful measure of my prowess as a cyclist. Many Read More ›

the game of go
the game of go

Why AI Appears To Create Things

When AlphaGo made a winning move, it exhibited no more creative insight than when it played pedestrian moves

Our surprise at AlphaGo’s move says more about our inability to predict what a program will do than about any creative effort of the program. We’ve known for decades that we cannot predict the results of any moderately complex computer program.

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