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Glücksspiel

Can Wholly Random Processes Produce Information?

Can information result, without intention, from a series of accidents? Some have tried it with computers…

In Define information before you talk about it, neurosurgeon Michael Egnor interviewed engineering prof Robert J. Marks on the way information, not matter, shapes our world (October 28, 2021). In the first portion, Egnor and Marks discussed questions like: Why do two identical snowflakes seem more meaningful than one snowflake. Then they turned to the relationship between information and creativity. Is creativity a function of more information? Or is there more to it? And human intervention make any difference? Does Mount Rushmore have no more information than Mount Fuji? Does human intervention make a measurable difference? That’s specified complexity. Putting the idea of specified complexity to work, how do we measure meaningful information? How do we know Lincoln contained more…

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Blockchain Network, Data Stream

Define Information Before You Talk About It: Egnor Interviews Marks

Has anyone ever given you some useless information? What does it even mean for information to be meaningful? This week, on Mind Matters News, guest host Dr. Michael Egnor interviews our own Robert J. Marks about information, as well as the creative limits of artificial intelligence, and why evolutionary algorithms aren’t the magic bullet they’re often presented to be. Show…

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Inside an old Silo

Robert J. Marks On AI Evolutionary Computing (Part III)

Can artificial intelligence algorithms prove Darwinian evolution? Why won’t some scientists admit the design inherent in evolutionary computing? Do random processes disprove intelligent design? Dr. Michael Egnor discusses evolutionary computing, the no free lunch theorem, and the role of purpose in chance with Dr. Robert J. Marks. Show Notes 00:41 | Introducing Dr. Robert J. Marks 01:10 | The role…

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Evolving Technology

Can Computers Evolve to Program Themselves Without Programmers?

How much computing power would we need to evolve the programmer’s intelligence via Darwinian evolution

At Science earlier this year, we were told that “Researchers have created software that borrows concepts from Darwinian evolution, including ‘survival of the fittest,’ to build AI programs that improve generation after generation without human input.” Critics say it’s not that easy. Computer scientist Roman Yampolskiy (pictured) discusses the problem in an open access paper, starting with a joke: On April 1, 2016 Dr. Yampolskiy posted the following to his social media accounts: “Google just announced major layoffs of programmers. Future software development and updates will be done mostly via recursive self-improvement by evolving deep neural networks”. The joke got a number of “likes” but also, interestingly, a few requests from journalists for interviews on this “developing story”. To non-experts…

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Fake bugs on yellow background

7: Computers can develop creative solutions on their own!

AI help, not hype, with Robert J. Marks: Programmers may be surprised by which solution, from a range they built in, comes out on top
Sometimes the results are unexpected and even surprising. But they follow directly from the program doing exactly what the programmer programmed it to do. It’s all program, no creativity. Read More ›