When a fan asked Nvidia CEO Jensen Huang Sign his chest Earlier this month, it could be a sign that the hype around the chipmaker has reached unsustainable heights.
Over the past few years, Nvidia’s computer chips — which have certain technological capabilities that make them suitable for AI applications — have catapulted the company to new levels of profitability. Last week, Nvidia briefly became the world’s most valuable company; Three days later, it lost that title amid a day-long sell-off of its shares. Although its stock price has recovered somewhat, it is now the world’s Third most valuable Companies with a market capitalization $3.1 trillionAfter Microsoft and Apple.
The sell-off was halted amid concerns that Nvidia was overpriced. Recently, Deutsche Bank financial research strategist Jim Reid warned “Signs of overexcitement“About Nvidia, and Nvidia executives have Even off sale Some of their holdings in the company.
There’s still plenty of reason to be excited about Nvidia: The company has established itself as an industry-leading chipmaker, reaping the benefits of early bets on AI that chatbots like OpenAI’s ChatGPT have brought to the technology’s wider public attention.
“It’s very early in the AI race,” said Daniel Newman, CEO of Futurum Group, a technology research and analytics firm. “But the people who are building AI so far have probably done some of their most important work at Nvidia.”
The stock market responded accordingly. Nvidia called “The Magnificent Seven“Technology stocks that accounted for most of the stock market’s growth last year. Its share price has soared About 155 percent Since the market is closed on Wednesdays since January.
But whether Nvidia can continue to replicate that kind of growth depends on advances in AI, as well as how much — and how quickly — businesses adopt it.
How Nvidia became one of the most important chipmakers in the world
Nvidia has long been considered a major producer of graphics cards for gaming. However, its graphics processing units (GPUs), the main component of graphics cards, have gained popularity amid the rise of cryptocurrency mining, a process that involves solving complex mathematical problems to mint new cryptocurrency coins.
That’s because Nvidia GPUs are highly optimized for what’s called “parallel processing” — essentially, dividing up a computationally difficult problem and assigning thousands of processor cores to different parts of the GPU simultaneously, solving the problem faster and more efficiently than traditional computing methods. . .
As it turns out, generative AIO relies on parallel processing. Whenever you ask ChatGPT a question, for example, the AI model has to parse large data sets — the sum total of the world’s text-based online content, according to ChatGPT’s latest knowledge update — to give you an answer. Doing this in real time and at the scale that companies like OpenAI hope to build requires parallel processing in data centers with thousands of GPUs.
Nvidia realized what it could gain from the GPU demands of generative AI. Huang referred to 2018 as a “The company’s moment bet” in which Nvidia reimagined GPUs for AI before ChatGPT came on the scene. The company has structured its research and development and mergers and acquisitions strategies to benefit from the coming AI boom.
“They were playing the game when no one else was,” Newman said.
In addition to offering GPUs optimized for that purpose, Nvidia developed a programming model and parallel computing platform called Compute Unified Device Architecture (CUDA) that has become the industry standard. This software makes the power of Nvidia GPUs more accessible to developers.
So even as Nvidia’s competitors such as AMD and Intel came to introduce similar offerings, even at lower price points, Nvidia retained the lion’s share of the business GPU market, as developers got used to CUDA and didn’t want to. switch
“What [Nvidia] Realized early on that if you want to win in hardware, you have to win in software,” Newman said. “Many developers who are building apps for AI have built them and are comfortable using CUDA to build them and run them on Nvidia hardware.”
All of this positions Nvidia to capitalize on the growing demand for generative AI.
Can Nvidia keep up the good times?
Nvidia’s competitors likely pose no immediate threat to its position as the industry leader.
“In the long term, we expect the tech titans to try to find second-source or in-house solutions to outpace Nvidia in AI, but likely, these efforts won’t remove, but not eliminate, Nvidia’s AI dominance,” Brian Colello, strategist at Morningstar, said recently. wrote in a report.
However, Nvidia’s ability to sustain the level of growth it has seen over the past year is tied to the future of generative AI and how much it can be monetized.
Anyone can currently access ChatGPT for free, although a $20 monthly subscription fee will give you access to its latest and greatest version. But individual consumers are currently not where the real money is.
Rather, it is with business. And at this point, it’s anyone’s guess how companies will integrate generative AI into their business models in the coming years.
For Nvidia’s growth to be sustainable, big companies like Salesforce or Oracle – which sell software to enterprises – will have to offer new software that will “consume tons of AI” to the point that these big companies are signing annual contracts that give them access to massive amounts of computing power. , Newman said.
“Otherwise, that central thesis of putting up these massive megawatt data centers around the world full of GPUs becomes a bit of a risk.”
So should you buy Nvidia stock? It depends on how bullish you are about AI and its potential to enter the economy.
“We think Nvidia’s prospects will be tied to the AI market, for better or worse, for quite some time,” Colello wrote.
