The Rise of Data-Driven Approaches

A paradigm shift occurred in the 1980s and 1990s as AI researchers began harnessing machine learning—a methodology where systems learn from data rather than relying solely on fixed rules. Key developments during this era included:

• Neural Networks and Deep Learning: Inspired by the human brain, artificial neural networks started to take shape, eventually evolving into the deep learning architectures that power today’s language, image, and speech recognition systems.
• Algorithmic Innovation: Techniques such as support vector machines, decision trees, and reinforcement learning further refined how machines learn and make decisions in complex environments 2.
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