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Computers Evolve a New Path Toward Human Intelligence | Quanta Magazine

https://www.quantamagazine.org/computers-evolve-a-new-path-toward-human-intelligence-20191106/

quantamagazine.org

Computers Evolve a New Path Toward Human Intelligence | Quanta Magazine
Stanley's realization led to what he calls the steppingstone principle - and, with it, a way of designing algorithms that more fully embraces the endlessly creative potential of biological evolution. Evolutionary algorithms have been around for a long time.

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Neuroevolution

Neuroevolution is a form of artificial intelligence. It is a meta-algorithm, an algorithm for designing algorithms. It adopts the principles of biological evolution in order to design smarter algor...

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Evolutionary algorithms

Traditionally, evolutionary algorithms are used to solve specific problems. For instance, the ability to control a two-legged robot. Solutions that perform the best on some metrics are selected to ...

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The steppingstone principle

It goes beyond traditional evolutionary approaches. It explains innovation. Instead of optimizing for a specific goal, it embraces the creative exploration of a diverse population of sol...

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Producing human intelligence

Biological evolution is the only system to produce human intelligence.

If we want algorithms that can navigate the physical and social world as we do, we need to imitate nature's tactics. Ins...

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Pursuing objectives can be problematic

Pursuing specific goals can be a hindrance to reaching those objectives.

Kenneth Stanley, a computer scientist, hoped to show that by following ideas in interesting directions, algorithms can...

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Pros and Cons of Neuroevolution

Cons
  • It requires a considerable amount of computation.
  • Most people want to solve a particular problem. Neuroevolution might get you to a creative solution but could lead you astray ...

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Main uses of evolutionary algorithms

  • Maintaining a population of different solutions
  • Optimizing a single solution. 

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How much can we afford to forget, if we train machines to remember? - Gene Tracy | Aeon Ideas

How much can we afford to forget, if we train machines to remember? - Gene Tracy | Aeon Ideas

https://aeon.co/ideas/how-much-can-we-afford-to-forget-if-we-train-machines-to-remember

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When I was a student, in the distant past when most computers were still huge mainframes, I had a friend whose PhD advisor insisted that he carry out a long and difficult atomic theory calculation by hand. This led to page after page of pencil scratches, full of mistakes, so my friend finally gave in to his frustration.

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Key Ideas

Safe To Forget

As machines become increasingly capable, along with computer memory, power and space being abundantly available, our brains are in a transition phase.

Earlier we had to remember a lot, do calculations on paper, and jog our memories to recall something. More and more of such information isn't processed by our brains anymore and is taken care of by machines.

Information In Your Head

As technology advances and the internet gets dramatically more powerful, the need to retain information in our heads diminishes.

Google and other search engines which deploy AI, work as our 'memory partners' and provide us access to most of the human knowledge.

Peer-To-Peer Memory Networks

Our ancestors had a manual 'peer-to-peer' memory network to pass on knowledge to the future generations; it wasn't reliable but worked for a long time.

Now we believe AI is better and more objective to provide us with information, which might not be the case.

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