Mind Matters Natural and Artificial Intelligence News and Analysis

TagBlind Watchmaker thesis

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weasel peering out of a burrow

Dawkins’ Weasel Program vs the Information Life Acquires En Route

To demonstrate what is wrong with fully naturalist assumptions like those of Richard Dawkins’ Weasel program, I developed Weasel Libs, modeled on Mad Libs

In his famous Weasel program zoologist and philosopher Richard Dawkins shows that the simple combination of random mutation and natural selection (Darwinian evolution) can produce the English sentence, “Methinks it is like a weasel”, in a short time period. The point of his program is to demonstrate that evolution can generate the complex, pre-specified DNA sequences we find in biology before the heat death of the universe. His argument sounds persuasive because both English sentences and DNA sequences are made up of symbols. Both can be randomly modified anywhere, and by cumulative selection, they can plausibly adapt to the environment in reasonably short order. Writers in English can learn to pen best-selling novels through trial and error and audience feedback.…

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Large cog wheels in the motor.

Can Computers –- and People — Learn To Think From the Bottom Up?

That’s the big promise made in a recent article at Aeon

Tufts University biologist Michael Levin and Columbia University neuroscientist Rafael Yuste have an ambitious project in hand: To explain how evolution “‘hacked’ its way to intelligence from the bottom up,” that is, from nothing. They base their thesis on computer science: This is intelligence in action: the ability to reach a particular goal or solve a problem by undertaking new steps in the face of changing circumstances. It’s evident not just in intelligent people and mammals and birds and cephalopods, but also cells and tissues, individual neurons and networks of neurons, viruses, ribosomes and RNA fragments, down to motor proteins and molecular networks. Across all these scales, living things solve problems and achieve goals by flexibly navigating different spaces –…