Meta founder and CEO Mark Zuckerberg speaks during the Meta Connect event at Meta headquarters in Menlo Park, California, on Sept. 27, 2023.
Josh Edelson | AFP | Getty Images
Meta is spending billions of dollars on Nvidia’s popular computer chips, which are at the heart of artificial intelligence research and projects.
In an Instagram Reels post on Thursday, Zuckerberg said the company’s “future roadmap” for AI requires it to build a “massive compute infrastructure.” By the end of 2024, Zuckerberg said that infrastructure will include 350,000 H100 graphics cards from Nvidia.
Zuckerberg didn’t say how many of the graphics processing units (GPUs) the company has already purchased, but the H100 didn’t hit the market until late 2022, and that was in limited supply. Analysts at Raymond James estimate Nvidia is selling the H100 for $25,000 to $30,000, and on eBay they can cost over $40,000. If Meta were paying at the low end of the price range, that would amount to close to $9 billion in expenditures.
Additionally, Zuckerberg said Meta’s compute infrastructure will contain “almost 600k H100 equivalents of compute if you include other GPUs.” In December, tech companies like Meta, OpenAI and Microsoft said they would use the new Instinct MI300X AI computer chips from AMD.
Meta needs these heavy-duty computer chips as it pursues research in artificial general intelligence (AGI), which Zuckerberg said is a “long term vision” for the company. OpenAI and Google’s DeepMind unit are also researching AGI, a futuristic form of AI that’s comparable to human-level intelligence.
Meta’s chief scientist Yann LeCun stressed the importance of GPUs during a media event in San Francisco last month.
″[If] you think AGI is in, the more GPUs you have to buy,” LeCun said at the time. Regarding Nvidia CEO Jensen Huang, LeCun said “There is an AI war, and he’s supplying the weapons.”
In Meta’s third-quarter earnings report, the company said that total expenses for 2024 will be in the range of $94 billion to $99 billion, driven in part by computing expansion.
“In terms of investment priorities, AI will be our biggest investment area in 2024, both in engineering and computer resources,” Zuckerberg said on the call with analysts.
Zuckerberg said on Thursday that Meta plans to “open source responsibly” its yet-to-be developed “general intelligence,” an approach the company is also taking with its Llama family of large language models.
Meta is currently training Llama 3 and is also making its Fundamental AI Research team (FAIR) and GenAI research team work more closely together, Zuckerberg said.
Shortly after Zuckerberg’s post, LeCun said in a post on X, that “To accelerate progress, FAIR is now a sister organization of GenAI, the AI product division.”
Industrial and infrastructure stocks may soon share the spotlight with the artificial intelligence trade.
According to ETF Action’s Mike Atkins, there’s a bullish setup taking shape due to both policy and consumer trends. His prediction comes during a volatile month for Big Tech and AI stocks.
“You’re seeing kind of the old-school infrastructure, industrial products that have not done as well over the years,” the firm’s founding partner told CNBC’s “ETF Edge” this week. “But there’s a big drive… kind of away from globalization into this reshoring concept, and I think that has legs.”
Global X CEO Ryan O’Connor is also optimistic because the groups support the AI boom. His firm runs the Global X U.S. Infrastructure Development ETF (PAVE), which tracks companies involved in construction and industrial projects.
“Infrastructure is something that’s near and dear to our heart based off of PAVE, which is our largest ETF in the market,” said O’Connor in the same interview. “We think some of these reshoring efforts that you can get through some of these infrastructure places are an interesting one.”
Both ETFs are lower so far this month — but Global X’s infrastructure ETF is performing better. Its top holdings, according to the firm’s website, are Howmet Aerospace, Quanta Services and Parker Hannifin.
“All of the things that are going to be required for us to continue to support this AI boom, the electrification of the U.S. economy, is certainly one of them,” he said, noting the firm’s U.S. Electrification ETF (ZAP) gives investors exposure to them. The ETF is up almost 24% so far this year.
The Global X U.S. Electrification ETF is also performing a few percentage points better than the VanEck Semiconductor ETF for the month.
At ThredUp‘s 600,000-square-foot warehouse in Suwanee, Georgia, roughly 40,000 pieces of used clothing are processed each day. The company’s logistics network — four facilities across the U.S. — now rivals that of some fast-fashion giants.
“This is the largest garment-on-hanger system in the world,” said Justin Pina, ThredUp’s senior director of operations. “We can hold more than 3.5 million items here.”
Secondhand shopping is booming. The global secondhand apparel market is expected to reach $367 billion by 2029, growing almost three times faster than the overall apparel market, according to GlobalData.
About 97 percent of clothing sold in the U.S. is imported, mostly from China, Vietnam, Bangladesh and India, according to the American Apparel and Footwear Association.
“When tariffs raise those costs, resale platforms suddenly look like the smart buy. This isn’t just a fad,” said Jasmine Enberg, co-CEO of Scalable. “Tariffs are accelerating trends that were already reshaping the way Americans shop.”
For James Reinhart, ThredUp’s CEO, the company is already seeing it play out.
“The business is free-cash-flow positive and growing double digits,” said Reinhart. “We feel really good about the economics, gross margins near 80% and operations built entirely within the U.S.”
ThredUp reported that revenue grew 34% year over year in the third quarter. The company also said it acquired more new customers in the quarter than at any other time in its history, with new buyer growth up 54% from the same period last year.
“If tariffs add 20% to 30% to retail prices, that’s a huge advantage for resale,” said Dylan Carden, research analyst at William Blair & Company. “Pre-owned items aren’t subject to those duties, so demand naturally shifts.”
Inside the ThredUp warehouse, where CNBC got a behind-the-scenes look. automation hums alongside human workers. AI systems photograph, categorize, and price thousands of garments per hour. For Reinhart, the technology is key to scaling resale like retail.
“AI has really accelerated adoption,” said Reinhart. “It’s helping us improve discovery, styling, and personalization for buyers.”
That tech wave extends beyond ThredUp. Fashion-tech startups Phia, co-founded by Phoebe Gates and Sophia Kianni, is using AI to scan thousands of listings across retail and resale in seconds.
“The fact that we’ve driven millions in transaction volume shows how big this need is,” Gates said. “People want smarter, cheaper ways to shop.”
ThredUp is betting that domestic infrastructure, automation, and AI will keep it ahead of the curve, and that tariffs meant to revive U.S. manufacturing could end up powering a new kind of American fashion economy.
“The future of fashion will be more sustainable than it is today,” said Reinhart. “And secondhand will be at the center of it.”
CNBC’s Deirdre Bosa asked those at the epicenter of the boom for their take, sitting down with the founders of two of the buzziest AI startups.
Amjad Masad, founder and CEO of AI coding startup Replit, admits there’s been a cooldown.
“Early on in the year, there was the vibe coding hype market, where everyone’s heard about vibe coding. Everyone wanted to go try it. The tools were not as good as they are today. So I think that burnt a lot of people,” Masad said. “So there’s a bit of a vibe coding, I would say, hype slow down, and a lot of companies that were making money are not making as much money.”
Masad added that a lot companies were publishing their annualized recurring revenue figures every week, and “now they’re not.”
Navrina Singh, founder and CEO of startup Credo AI, which helps enterprises with AI oversight and risk management, is seeing more excitement than fear.
“I don’t think we are in a bubble,” she said. “I really believe this is the new reality of the world that we are living in. As we know, AI is going to be and already is our biggest growth driver for businesses. So it just makes sense that there has to be more investment, not only on the capability side, governance side, but energy and infrastructure side as well.”