By - Bizz Gossips

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Five Key Stages In The Evolution Of AI

Early AI research focused on symbolic reasoning and rule-based systems, attempting to emulate human intelligence through logical rules.

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1. Symbolic AI (1950s-1960s)

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The development of expert systems, which captured human expertise in narrow domains, marked this stage. These systems made decisions based on structured knowledge.

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2. Expert Systems (1960s-1970s)

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Machine learning approaches gained popularity, with a shift from rule-based systems to algorithms that learn from data. Neural networks and statistical methods made significant advancements.

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3. Machine Learning (1980s-1990s)

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Deep learning emerged as a subset of machine learning, with neural networks comprising many layers. This approach revolutionized AI, enabling breakthroughs in tasks like image and speech recognition.

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4. Deep Learning (2010s)

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The most recent stage involves increased awareness and action on ethical concerns, bias, and the responsible development of AI systems. Regulations and guidelines are being introduced to ensure AI is used ethically and safely.

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5. Ethical and Responsible AI (2020s and beyond)

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