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Nvidia CEO Huang Renxun: we bet everything on AI five years ago

2025-03-17 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > IT Information >

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CTOnews.com August 9, Nvidia founder and CEO Huang Renxun (Jensen Huang) said in a keynote speech at the SIGGRAPH conference in Los Angeles today that the company made an existential business decision in 2018, but few people realize that it will redefine its future and help reshape a growing industry.

CTOnews.com noted that in his speech, Huang Renxun reviewed the turning point five years ago, when he chose to use AI to process images, namely ray tracing (ray tracing) and intelligent rendering: RTX and DLSS, respectively. "We realize that rasterization has reached its limit," he said. Rasterization is a traditional and widely used method of rendering 3D scenes. "2018 is a desperate moment that requires us to reinvent hardware, software and algorithms. And when we reinvented CG (computer graphics) with AI, we were also reinventing GPU (graphics processor) for AI."

While RayTracing and DLSS are still in the process of being adopted by consumer GPU and gaming, the architecture they have created for this is found to be a perfect match with the growing machine learning development community. The large amount of computation required to train larger and more complex generative models can only be provided by systems such as H100 that were designed from the outset to perform the necessary operations on a large scale. It can be said that AI development is only limited by the availability of these computing resources to some extent.

But Mr Huang insists this is just the beginning. The new model not only needs to be trained, but also needs to be run in real time by millions or even billions of users on a regular basis. "in the future, LLM [large language models] will be at the forefront of almost everything: 'human' is the new programming language," he said. Huang Renxun speculates that natural language interfaces will be used to some extent in fields ranging from visual effects to rapidly digitized manufacturing, factory design and heavy industry. "the whole factory will be defined and robotized by software, and the cars they build will also be robotic. So this is robot design robot construction robot," he said.

Huang Renxun did not mention many of the challenges and regulatory issues facing AI.

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