#Humanbrain

A groundbreaking wave of neuroscience research is redefining what it means to think—and, crucially, why artificial intelligence (AI) still falls far short of the intricacies of the human mind. A newly published feature in Salon highlights the distinct evolutionary adaptations that make the human brain more than a glorified computer, challenging decades-old assumptions fundamental to AI development and the neural network concept that underlies machine learning models.

For years, popular understanding—and much of AI research—has treated the brain as a vast network made up of nearly identical neurons whose intelligence emerges through the patterns of their collective firing. This view inspired so-called artificial neural networks, computer systems designed to solve problems by mimicking the way brains process information. Such analogies, cemented over decades, fostered the belief that if machines could imitate the structure and connectivity of brains, they might one day match, or even surpass, human intellect. But recent scientific discoveries show this metaphor misses the mark in fundamental ways, with profound implications for both neuroscience and the future of AI.

New neuroscience findings are reshaping what we mean by “thinking.” They show that artificial intelligence, though powerful, still lags far behind the human brain’s complexity and adaptability. A recent feature highlights how evolutionary advances give humans unique capabilities that machines struggle to replicate, challenging long-standing AI assumptions rooted in neural network models.

Why this matters for Thai readers. As Thailand accelerates digital transformation in health, education, and business, understanding how intelligence works—biological and artificial—helps shape better policies and practical AI applications. These insights also matter for how AI is used in Thai classrooms, hospitals, and public services, where accuracy, empathy, and cultural context matter.