In a recent speech at CalTech, Jensen Huang, CEO of NVIDIA Corporation NVDA, shed light on the company’s significant investments in deep learning.
What Happened: Huang recalled the significant event in 2012 when Jeff Hinton, Alex Krzyzewski, and Ilya Sutskever utilized NVIDIA’s CUDA GPUs to train AlexNet, winning the ImageNet Challenge. This marked the onset of the AI revolution, leading to significant changes for NVIDIA and the wider tech industry.
Despite the potential cost of hundreds of millions of dollars, NVIDIA chose to explore deep learning’s boundaries.
Huang recalled, “How could we explore the limits of deep learning without having to build these massive GPU clusters? At the time we were a rather small company, building these massive GPU clusters could cost hundreds and hundreds of millions of dollars.”
“However, no one knew how far deep learning could scale. And if we didn't build it, we'd never know. This is one of those, if you build it, will they come? Our logic is if we don't build it, they can't come.”
Believing in deep learning’s potential, NVIDIA made the investment, which has since proven to be transformative for the company.
Why It Matters: In the same speech at Caltech, Huang urged graduates to pursue “zero-billion-dollar markets” and view setbacks as growth opportunities. He highlighted NVIDIA’s early struggles and the importance of investing in untapped markets with billion-dollar potential.
NVIDIA’s stock has seen a significant rise since the start of the year, outpacing most of the market. The company has become the biggest beneficiary of the AI boom, with its chips in high demand as tech companies race to train and build their AI models. NVIDIA’s market cap rose to $3.33 trillion, surpassing tech giant Microsoft Corp, making it the most valuable public company in the world.
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This story was generated using Benzinga Neuro and edited by Pooja Rajkumari
© 2024 Benzinga.com. Benzinga does not provide investment advice. All rights reserved.
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