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– 00:00 🚀 Nvidia’s founding and perspective on computing
– Nvidia was founded during the PC Revolution, emphasizing the limitations of general-purpose computing.
– The company believed in accelerated computing, adding specialized components to CPUs for more efficient problem-solving.
– Recognized the need for a new form of computing and started focusing on accelerated computing.
– 03:54 💡 Journey to building Nvidia: The beginning and challenges
– Started Nvidia with a unique vision, relying on specialized technology, and a video game as a killer app.
– Faced significant challenges with the technology, market, and ecosystem but received pivotal support from key industry figures.
– Despite low odds of success, Nvidia’s focus on a specialized computing approach paid off.
– 06:53 🔶 Accelerated Computing and Artificial Intelligence: Scaling and simplicity
– Accelerated Computing is heralded as a cost-effective solution for training neural networks and processing large datasets.
– Building AI models, like GPT-3, involves significant hardware infrastructure, data, and investments but isn’t as expensive as perceived.
– Nvidia’s GPUs have a crucial role in training neural networks, requiring massive clusters of GPUs for complex models like GPT-3.
– 12:28 🎢 Leading Nvidia through growth and challenges
– Managing hyper-growth entails doubling company size under a year, navigating supply chains, customer relationships, and financial aspects.
– Despite the complexities, Jensen Huang reflects on the journey of building Nvidia, emphasizing the vital role of talent and resilience in the industry.
– Acknowledges the constant competitive landscape in technology, driving the need for continuous innovation and adaptation.
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