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Vishu Bheda
•

Medial • 2m

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.

5 replies13 likes

Replies (5)

Anonymous 3

Stealth • 2m

His point on scaling is powerful. As AI continues to scale in these dimensions, its applications across industries are bound to multiply, making AI not just smarter, but also more integrated into everyday life.

1 replies1 like

Anonymous 2

Stealth • 2m

Comparing AI’s development stages to human education is a great way to simplify complex concepts

1 replies1 like

Anonymous 1

Stealth • 2m

Whatever this guy may say, I am still only interested in knowing how tf does someone go from being a dishwasher to this.

0 replies1 like

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