AI can beat human brain in chess, but not in memory: Study
New Delhi : A group of scientists have found that the human brain’s efficiency in keeping up memories is more efficient than the Artificial Intelligence (AI).
The new study, carried out by SISSA scientists in collaboration with Kavli Institute for Systems Neuroscience & Centre for Neural Computation, Trondheim, Norway, has been published in Physical Review Letters.
In the last decade, AI has proved to be efficient in several fields, including Chess. In 1996, for the first time, the computer Deep Blue beat a human player, chess champion Garry Kasparov.
A memory is a tweak in connections between the neurons. Making them stronger or weaker, some neurons become more active, some less, until a pattern of activity emerges; AI uses complex algorithms to understand them and chose action while human brain does it in a way simpler form.
In the brain, each connection between neurons changes just based on how active the two neurons are at the same time.
The new research shows: the fewer number of memories stored using the brain strategy depends on such an unrealistic assumption. When the simple strategy used by the brain to change the connections is combined with biologically plausible models for single neurons response, that strategy performs as well as, or even better, than AI algorithms.
Overall, this research highlights how biologically plausible self-organized learning procedures can be just as efficient as slow and neurally implausible training algorithms.