A Different Kind Of AI

Robert Zwilling

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Besides standing for artificial intelligence, AI can also stand for animal intelligence, actual intelligence, and animated intelligence. Animated intelligence is were a complex natural system is copied to get advanced work done.

The CRSPIR process is a natural function performed by microbes. The CRSPIR process is making rapid advancements in detecting microbe and virus induced illnesses. A process to detect pathogens is being developed using the CRSPIR process that clips a piece of DNA off a pathogen sequence. This selected piece of DNA is now isolated, uncurled and "easy" to see what it is composed off. From that information the pathogen can quickly identified in 20 minutes for just a few dollars. The normal process is the traditional polymerase chain reaction (PCR) test which make millions of copies of a pathogen’s signal and that can take hours to process. It also requires complex laboratory equipment and highly trained technicians, and is expensive where the amount of money charged determines how fast the results are obtained.

To become really effective the CRSPIR test needs to be able to simultaneously sense multiple targets instead of just one. Medical applications often require this capability because certain conditions can have multiple common markers, so you need to be able to find the markers that are unique to that condition.

Another instance where copying the actions of live entities are helping people get faster answers is the common slime mold. It has already been identified as making intelligent decisions to get around and find resources. It used to be considered fungi, but is now classified as a unicellular organism, along with algae. Now the way the slime mold moves around has been used by researchers to chart out how the universe’s matter became the chaotic netting of filaments, tendrils and voids, known as the cosmic web, it is today. It didn't start out that way. To find out how the universe got to where it is today, researchers used the Monte Carlo Physarum Machine algorithm. This is inspired by the feeding habits of the slime mold, which is known to generate highly efficient interconnected networks when searching for food. This behavior has been used to model spatial problems in various disciplines, from neuroscience to civil engineering.
 

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