Scientists have discovered a possible driving force behind some of nature’s stunning displays paving the approach for more complex and autonomous AI. Researchers wanted to replicate the basic mechanisms behind some of the most highly organized patterns seen in the animal kingdom such as huge swirling starling murmurations and immense twisting herring shoals. The aim was to obtain a minimal model for general features of self-organization in the natural, or animal, world. The principle of ‘maximize your options’ which is a simple, almost trivial ambition produces complex organizational patterns, known as the Goldstone mode, a concept of how a giant flock of starlings can suddenly change direction collectively as if there was a central brain, however in reality, there is no core intelligence driving the behavior. But in reality, it could be down to basic survival instincts.
There were complex patterns and the appearance of synchronized group behaviors which were created by each individual in the group responding simply too tiny influences from its closest neighbors. Learning about how living organisms process and react to their surroundings could help improve artificial intelligence by giving AI systems basic cognitive skills, making them less reliant on human intervention.
The current paradigm of AI relies largely on amounts of data and neural networks.
Such a strategy might have some limitations. When faced with a new situation, current AI approaches require retraining and specific human intervention that costs time and money.
A promising way to improve it is to develop ways that can process novel information just like organisms with brains do.
The first step would then be to identify ways of processing information that can adapt to new inputs easily.
The approach has potential because it is inspired by organisms that have adapted to process and resolve new challenges for millions of years of their evolution.