AI has now transformed how most industries work, but not many people had had seemed interested the technology when it was being launched.
NVIDIA CEO Jensen Huang recently shared a revealing anecdote that underscores the foresight and risk-taking that paved the way for today’s AI boom. In a candid reflection, he recounted the lukewarm reception of what would become a foundational piece of technology for modern artificial intelligence, highlighting a moment of uncertainty that has since transformed into a multi-trillion dollar industry.
The Dawn of the AI Supercomputer
Huang’s story begins in 2016 with the launch of the DGX-1, a machine he describes as the genesis of the AI supercomputing era. “We built an AI supercomputer in 2016. It’s called the DGX-1. It was the first version of everything that I’ve been talking about,” he said. This groundbreaking machine was a powerhouse of its time, featuring “eight Volta GPUs connected with NVLink.”
The development of the DGX-1 was a monumental undertaking for NVIDIA. “It took us billions of dollars to build,” Huang revealed. Yet, the initial unveiling was met not with the fanfare one might expect for such a technological leap, but with silence and bewilderment.
“On the day we announced it, DGX-1, there were no customers, no interest, no applause,” Huang recalled. “A hundred percent confusion. Why would somebody build a computer like that? Does it run Windows? Nope.”
Despite the lack of immediate validation, NVIDIA’s conviction in its vision for accelerated computing did not waver. “And so we built it anyways,” Huang said.
A Glimmer of Hope from a “Non-Profit Startup”
Just when it seemed the DGX-1 was a solution in search of a problem, a glimmer of interest emerged from an unexpected source. “Thankfully, a young company, a startup, a non-profit startup in San Francisco was so delighted to see the computer. They said, ‘Can we have one?'”
But the sale came with a twist. “And I thought, ‘Oh my gosh, we sold one.’ But then I discovered it was a nonprofit,” Huang humorously lamented. Yet, the significance of this first adopter was not lost on him. In a move that has now become legendary in Silicon Valley lore, Huang took it upon himself to make the delivery.
“I put a computer, put a DGX-1 in my car and I drove it up to San Francisco and the name of that company is OpenAI,” he shared.
Reflecting on the experience, Huang offered a lighthearted takeaway: “I don’t know what the life lesson is there. There are a lot of nonprofits, you know. But maybe the lesson is this: If a developer reaches out to you and needs a GPU, the answer is yes.”
The Ripple Effects of a Single GPU
Huang’s anecdote is more than just a charming story; it’s a powerful illustration of a fundamental principle that has driven NVIDIA’s success: empowering developers and researchers. The decision to provide OpenAI with its first AI supercomputer was a pivotal moment, enabling the then-fledgling research organization to pursue the large-scale models that would eventually lead to breakthroughs like GPT-3 and ChatGPT.
The initial confusion surrounding the DGX-1 in 2016 is also a stark reminder of how nascent the AI landscape was just a few years ago. The question, “Does it run Windows?” perfectly encapsulates the prevailing PC-centric mindset of the time, a paradigm that NVIDIA was actively working to disrupt. The company was betting on a future where the parallel processing power of GPUs would be essential for training complex neural networks, a bet that has unequivocally paid off.
This trend of building for a future that the market doesn’t yet fully comprehend continues to be a hallmark of the tech industry. The development of the DGX-1 and its successors has fueled an arms race in the AI hardware sector, with companies like Google, AMD, and a host of startups all vying to create more powerful and efficient processors for AI workloads. The demand for these systems has skyrocketed, a stark contrast to the empty order books for the first DGX-1.
NVIDIA’s journey from a quiet launch in 2016 to its current position as a linchpin of the AI industry serves as a crucial lesson for innovators and investors alike. It highlights the importance of long-term vision, the willingness to invest in technologies ahead of their time, and the understanding that sometimes, the most transformative ideas are the ones that are initially met with confusion rather than applause.