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Show Notes
In the early days of AI, during the 1950s and 1960s, researchers focused on symbolic AI, creating rule-based systems for problem-solving. Progress was slow due to limited computing power. The 1980s saw a shift towards machine learning, with algorithms designed to improve performance based on data. In the 1990s, neural networks gained popularity but faced challenges. The 21st century brought breakthroughs in deep learning, fueled by large datasets and powerful GPUs. Today, AI applications are ubiquitous, from voice assistants to advanced machine learning models transforming various industries.
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