Scientists have introduced the concept of an AI-based model that can think like a human. Researchers have already presented its first assembly.
The researchers explained that cognitive and neuroscientists are trying to understand how neural activity in the brain translates into language, mathematics, logic, reasoning, planning, and other functions. If scientists can formulate how the brain works in terms of mathematical models, then they will open up the possibility of creating artificial intelligence (AI) systems that can mimic the human mind.
A team of scientists proposed to create a concept of a mathematical model of the brain called “interacting recurrent networks.” In this model, the brain is divided into a finite number of regions, each of which contains several million neurons. Within each area, neurons interact with each other, with all of them having connections to several other areas. These interregional connections can be excited or inhibited.
This model already provides randomness, plasticity and inhibition. Randomness means that neurons in each area of the brain are connected in a random way. In addition, different areas have random connections with each other. Plasticity allows the connections between neurons and regions to change under the influence of experience and learning. And inhibition means that a limited number of neurons are fired at any given time.
Together with a group of scientists from various academic institutions, the researchers detailed this model in the scientific journal Proceedings of the National Academy of Sciences. While the model is at the assembly level, it can perform a set of operations that allow you to process, store and retrieve information.
The researchers suggest that assemblage and assembly calculus are the correct model for explaining cognitive functions of the brain such as reasoning, planning, and language. Moreover, most of the knowledge can correspond to this model.
