Three decades of AI progress have arrived at an inflection point. Machine Learning first freed systems from static, rule-based programming in the 2000s, letting them learn from historical data and improve with experience. Multimodality followed in the 2010s, teaching agents to interpret images, audio, documents, and structured datasets within a unified reasoning framework. The 2020s delivered the decisive leap: autonomous agentic systems that interpret goals, plan independently, decompose tasks
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