The infrastructure to develop and power generative artificial intelligence models will require further “trillions” of dollars in investment, the head of top AI chipmaker Nvidia said Wednesday.
“We’re now a few hundred billion dollars into it… there are trillions of dollars of infrastructure that needs to be built out” in fields including energy, cloud computing and electronics, he added.
Nvidia has come to dominate spending on the processors needed for training and operating the large language models (LLMs) behind chatbots like OpenAI’s ChatGPT or Google Gemini.
Sales of its graphics processing units (GPUs) — originally developed for 3D gaming — powered the company’s market cap to over $5 trillion in October, although the figure has since fallen back by more than $600 billion.
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LLM developers like OpenAI are directing much of the mammoth investment they have received into Nvidia’s products, rushing to build GPU-stuffed data centres to serve an anticipated flood of demand for AI services.
Huang on Wednesday dismissed warnings from some observers that the spending spree looks increasingly like a bubble that could soon burst.
“The AI bubble comes about because the investments are large. And the investments are large because we have to build the infrastructure necessary for all of the layers of AI above it,” he said.
“I think the opportunity is really quite extraordinary”.
Huang also sought to dispel fears of AI destroying large numbers of jobs as its use filters into workplaces, saying instead that it would create new forms of work.
Microsoft chief executive Satya Nadella had on Tuesday struck a more cautious note, saying widespread AI adoption was needed to avoid a crash in the industry.
“For this not to be a bubble by definition, it requires that the benefits of this are much more evenly spread,” he said.
Nadella was nevertheless “confident that this is a technology that will in fact build on the rails of cloud and mobile, diffuse faster,” making for “economic growth all around the world,” he added.
AFP
