“Agile companies will take advantage of AI and boost their position.Companies less so will perish,” the CEO told graduating students at the National Taiwan University in Taipei. “While some worry that AI may take their jobs, someone who's expert with AI will.”28 mins ago
Signage with logo at the Silicon Valley headquarters of computer graphics hardware company Nvidia, ... [+]
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NVIDIA CEO Jensen Huang kicked off GTC 2023 by saying, “For nearly four decades, Moore’s Law has been the governing dynamics of the computer industry, which in turn, has impacted every industry.” Although “the exponential performance increase at constant cost and power has slowed down […], computing advance has gone to light speed.” The underlying factor is Artificial Intelligence (AI), and we should all pay attention.
Incremental increases in CPU processing capabilities have been expected to fall short of Moore’s Law at some point. Physical limits on miniaturization and the challenges associated with improving superconductor properties make this inevitable. Software developers and systems engineers have worked hard to be ready for this moment for years and they succeeded—all thanks to AI. Now, AI software and AI-enabled systems can pick up where Moore’s Law left off. AI tools and applications—more specifically Generative AI—allow existing infrastructure to do 1,000-X what it did with traditional computing.
With Generative AI, processing power currently available can be used to create entirely new products and services and transform industries beyond just optimizing existing operations. With the creation of AI-enabled task-specific servers and computing farms, the business landscape is changing rapidly for everyone. AI is no longer a nice-to-have, it is a must-have. Most businesses will see their offerings become obsolete very soon unless they integrate them with AI-enabled tools that can compete in an ever-more immersive consumer experience.
Yet there is a new challenge on the horizon. As businesses become ever more proficient in the use of AI, they start to wonder how they can make it even better. There is never enough of a good thing, right? But makers of AI tools cannot anticipate every single demand from every single process for every single operation. This is where businesses become interested in manufacturing their own company-specific AI. They want to manufacture their own intelligence. But since it is also an impractical possibility that every business will become an AI powerhouse capable of to not only using but developing its own AI, there is a monumental business opportunity for customizable AI applications. These would allow AI vendors to provide flexible platforms for clients to develop their own company-specific AI suits.
To that end, the NVIDIA “DGX Supercomputer will become a modern AI factory. Every company will manufacture intelligence,” said Huang. By expanding their current business model with NVIDIA DGX Cloud in partnership with Microsoft Azure, Google GCP, and Oracle OCI, NVIDIA plans to bring AI to every company, from a browser.
At GTC 2023, NVIDIA also introduced NVIDIA AI Foundations. Per an email sent to developers, this new service pack is meant “to enable software companies, service providers, and enterprises to realize the potential of generative AI. NVIDIA AI Foundations is a set of cloud services that provides a simplified approach to building and running custom generative AI, starting with state-of-the-art foundation models for text, visual media (image, video, and 3D), and the language of biology. Adobe, Getty Images, Shutterstock, and Morningstar are among the companies creating AI models, applications, and services with NVIDIA AI Foundations.”
So, yes, we just entered the era where companies will not only use, but also manufacture their own AI.
“You are running for food, or you are running from becoming food. And often times, you can’t tell which. Either way, run.”
NVIDIA founder and CEO Jensen Huang today urged graduates of National Taiwan University to run hard to seize the unprecedented opportunities that AI will present, but embrace the inevitable failures along the way.Whatever you pursue, he told the 10,000 graduates of the island’s premier university, do it with passion and conviction — and stay humble enough to learn the hard lessons that await.
“Whatever it is, run after it like we did. Run. Don’t walk,” Huang said, having swapped his signature black leather jacket for a black graduation robe, with the school’s plum-blossom emblem highlighting a royal blue, white and aqua collar.
“Remember, either you are running for food; or you are running from becoming food. And often times, you can’t tell which. Either way, run.”
Huang, who moved from Taiwan when he was young, recognized his parents in the audience, and shared three stories of initial failures and retreat. He called them instrumental in helping forge NVIDIA’s character during its three-decade journey from a three-person gaming-graphics startup to a global AI leader worth nearly a trillion dollars.
“I was … successful — until I started NVIDIA,” he said. “At NVIDIA, I experienced failures — great big ones. All humiliating and embarrassing. Many nearly doomed us.”
The first involved a key early contract the company won to help Sega build a gaming console. Rapid changes in the industry forced NVIDIA to give up the contract in a near-death brush with bankruptcy, which Sega’s leadership helped avert.
“Confronting our mistake and, with humility, asking for help saved NVIDIA,” he said.
The second was the decision in 2007 to put CUDA into all the company’s GPUs, enabling them to crunch data in addition to handling 3D graphics. It was an expensive, long-term investment that drew much criticism didn’t pay off for years until the chips started being used for machine learning.
“Our market cap hovered just above a billion dollars,” he recalled. “We suffered many years of poor performance. Our shareholders were skeptical of CUDA and preferred we improve profitability.”
The third was the decision in 2010 to charge into the promising mobile-phone market as graphics-rich capabilities were coming into reach. The market quickly commoditized, though, and NVIDIA retreated just as quickly, taking initial heat but opening the door to investing in promising new markets — robotics and self-driving cars.
“Our strategic retreat paid off,” he said. “By leaving the phone market, we opened our minds to invent a new one.”
Huang told grads that of the parallels in terms of boundless promise between the world he entered upon graduating four decades ago, on the cusp of the PC revolution, and the brave new age of AI they are entering today.
“For your journey, take along some of my learnings,” he said. Admit mistakes and ask for help; endure pain and suffering to realize your dreams; and make sacrifices to dedicate yourself to a life of purpose.
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