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12 SMT007 MAGAZINE I APRIL 2025 If transmitting and receiving electrochem- ical signals via neurons are essentially the thoughts, emotions, actions, and automatic functions of the human body, then the neu- rons' knowledge controls how to use the combined power of the conscious and uncon- scious mind to think in a healthier, more flex- ible, resilient, and goal-supporting way. Is thinking linked to electrical signals zooming inside our heads, forming a complex code carried by our neurons? Can we say the brain is the hardware, the mind is the soware, and the operating system gathers, stores, and manages information by using our brain's massive processing resources and capacities as the basis of human intelligence? What is artificial intelligence, and what is human intelligence? Artificial Intelligence vs. Human Intelligence Currently, there is no single established test that can authoritatively measure artifi- cial or human intelligence. Humans gener- ate data, acquire information, and translate it into knowledge. Cumulative knowledge builds intelligence. As such, it is plausible to define human intelligence as the capacity to acquire knowledge and the ability to apply it to achieve desired outcomes. Computer science defines artificial intel- ligence as any device that perceives its envi- ronment and takes actions that maximize its chance of successfully achieving its goals. It also includes a system's ability to interpret correctly external data, learn from such data, and use what it has learned to achieve specific goals and tasks through flexible adaptation. At its broadest level, intelligence is the abil- ity to achieve a range of goals in different and unpredictable environments. Higher intelli- gent systems can fulfill a wider range of goals in a wider range of predictable and unpre- dictable environments. A marvel of the human brain is that it can deal with the unexpected. Today, we need to advance the understanding of the brain to advance AI. Meanwhile, AI is fostering brain research. Brain Research AI enables new kinds of research 2 . e capacity of modern computer systems to process more data than in the past opens immense possibilities. Mathematics makes many kinds of AI possible, such as clus- ter models. One example of this method- ology is to amass a pool of data that groups people into different clusters and uses arti- ficial neuron networks to interpret the elec- trical signals of hundreds of neurons in the brain. e research's main finding was that the actual substance of thought and the pat- terns that constitute the mind we use to read is dynamic electrical activity in our brains, rather than something physically anchored to neurons. is is an important finding. It perhaps points to the immense complexity, nuance, and intricacy of brain dynamics— our mind, thoughts, and the mechanism of thinking and reasoning. While neural networks in the brain are vastly more complicated, the result of this simulation is a model system that is both close enough to its biological equivalent and simple enough to offer hints about how the brain works.