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Nvidia CEO: Why the Next Stage of AI Needs A Lot More Computing Power
- Nvidia CEO Jensen Huang highlighted the growing need for massive computing power in the AI industry, particularly for advanced AI models like AI agents and reasoning models.
- The shift towards reasoning models in AI requires significantly more computational power compared to traditional large language models.
- Huang emphasized the importance of faster computation to maintain responsiveness in AI models as reasoning processes take longer.
- Despite doubts over GPU demand following news about startup DeepSeek using fewer Nvidia chips, Huang believes demand will increase due to the rise of agentic AI and reasoning.
- Nvidia demonstrated the higher efficiency and complexities of reasoning models compared to traditional AI models like Meta’s Llama open-source model.
- Nvidia also announced a collaboration with General Motors to use custom AI systems in vehicle production and robotics.
- Further collaborations with Google, Alphabet, and GE HealthCare aim to advance AI in various industries, including robotics, healthcare, and energy.
- Nvidia introduced desktop supercomputers under the DGX brand, powered by the Grace Blackwell platform, to enable AI development and research.
- The company is venturing into quantum computing with the establishment of the Nvidia Accelerated Quantum Research Center to integrate quantum hardware with AI supercomputers.
- Nvidia is focusing on enhancing computing power capabilities to support the evolving needs of AI in various sectors, emphasizing faster computation, collaborations, and quantum computing research.
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