Intelligence is a sometimes effusive concept. In the natural world, for example, intelligence appears in different ways, such as a bat deploying echolocation to navigate in the dark; or an octopus adapting to survive when a predator is nearby. In the silicon world, there are debates as to how “intelligent” machines are, and there are clearly different forms of artificial intelligence are emerging.
How do these concepts of natural world intelligence and computer science intelligence inform us about human intelligence. This is something cognitive neuroscientists have been pondering. According to the Cognitive Neuroscience Society, researchers are exploring ways to use emerging artificial intelligence networks to enhance our understanding of the human brain.
According to one of the researchers, Dr. Aude Oliva from the Massachusetts Institute of Technology: “The fundamental questions cognitive neuroscientists and computer scientists seek to answer are similar,. They have a complex system made of components — for one, it’s called neurons and for the other, it’s called units — and we are doing experiments to try to determine what those components calculate.”
The research undertaken by Dr. Oliva takes the form of using “artificial neurons” (lines of code) with neural network models to parse out the different elements that are required to recognize a specific place or object. When training an artificial network to recognize hundreds of different places, like kitchens, bedrooms, parks and so on, the researchers found their platform could learn to recognize people and animals.
The researchers hope to develop the model further and to work out how humans can recognize the objects around them in the blink of an eye. This remains a new, but rapidly developed, field of science. The findings to date have been presented to the recent 25th annual meeting of the Cognitive Neuroscience Society, which took place towards the end of March 2018 in Boston, Massachusetts.
As an example of artificial intelligence’s superiority to humans in some matters, machines have succeeded in out-performing humans in spotting, counting and cataloging craters on the Moon. This is discussed in the Digital Journal story “AI is superior to humans in Moon mapping challenge.”
