Computers Evolve a New Path Toward Human Intelligence | Quanta Magazine
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 produce a diversity of results and solve problems. Thus, ignoring an objective can get you to the solution faster than pursuing it. He showed this through an approach named novelty search.
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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.
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.
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.