
The refinement of the backpropagation algorithm in the 1980s provided a mathematical framework for machines to adjust their internal weights and minimize errors during the learning process. This foundational shift moved artificial intelligence away from the rigid constraints of symbolic logic, where every possible outcome had to be pre-defined by human programmers. In those earlier decades, technology was largely static,










