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Vishu Bheda

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Medial • 3m

Jensen Huang, the CEO of NVIDIA, describes how AI is advancing in three key dimensions: 1. Pre-training: This is like getting a college degree. AI models are trained on massive datasets to develop broad, general knowledge about the world. 2. Post-training: Similar to specializing in a career, AI is fine-tuned to become an expert in specific fields like healthcare, finance, or language. 3. Test-time compute: This represents "thinking on the spot." When AI is deployed, it uses its knowledge to solve real-world problems in real time, adapting to new challenges. These three stages—learning broadly, specializing deeply, and thinking quickly—are driving the rapid progress of AI. Huang highlights that this multi-dimensional development is why AI scaling continues, enabling smarter, faster, and more efficient systems capable of solving increasingly complex problems in every field.

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