TL;DR:
AI models start from random noise, much like a newborn with untapped potential. Through massive amounts of data and mathematical optimization, they learn by predicting missing words and refining billions of parameters. This process turns random patterns into a system capable of generating language, solving problems, and more. While impressive, these models rely on pattern recognition, leading to limitations like hallucination and overgeneralization. The journey from noise to intelligence highlights the power of machine learning and opens up questions about efficiency, ethics, and what’s next for AI.
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