Jensen Huang, co-founder and CEO of Nvidia, during the Nvidia GPU Technology Conference in San Jose, California, on March 19, 2024.
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Five years ago, Nvidia CEO Jensen Huang owned a stake in his chipmaker worth roughly $3 billion. After Thursday’s rally, which pushed the stock to a record, his holdings now stand at more than $90 billion.
Nvidia late Wednesday reported first-quarter earnings that topped estimates, with sales jumping more than 200% for a third straight quarter, driven by demand for artificial intelligence processors.
Huang also delivered a better-than-expected forecast and indicated to investors that the company sees insatiable demand for its AI graphics processing units, or GPUs. The company signaled its customers, especially the big cloud companies, could get a strong return on their investment in the pricey chips.
“We are fundamentally changing how computing works and what computers can do,” Huang said.
Huang owns about 86.76 million shares of Nvidia, or more than 3.5% of the company’s outstanding shares. With the stock rising over 9% to close at a price of nearly $1,038 per share on Thursday, the value of his stake rose by about $7.7 billion.
Nvidia shares have more than doubled this year after tripling in 2023. They are up about 28-fold in the past five years. Huang added shares to his stake in 2022, when the stock hit relative lows before the AI boom.
Huang, 61, founded the Silicon Valley company in 1993 to build GPUs for 3D gaming. While gaming was the company’s biggest business for decades, Nvidia has dipped into other markets, including cloud gaming subscriptions, the metaverse and cryptocurrency mining chips.
But Nvidia’s fortunes shifted dramatically in late 2022, when OpenAI released ChatGPT, opening up the concept of generative AI to the broader public. The technology showcased a future in which computers won’t just retrieve new information from databases, but can also generate new content and answers to questions from large caches of unsorted data.
OpenAI does most of its AI development on Nvidia GPUs. As other companies such as Microsoft, Google and Meta bolstered their investments in AI research and development, they needed billions of dollars worth of the latest AI chips to build out their models.
Huang has been the face of Nvidia and its principal salesperson, constantly extolling the potential and power of using the company’s GPUs for building AI.
Nvidia, which has been developing AI software and tools for more than a decade, ended up in prime position to become the top supplier to the biggest technology companies. The company now has about 80% of the market for AI chips, and Huang is among the 20 richest people in the world.
Neptune and OpenAI have collaborated on a metrics dashboard to help teams that are building foundation models. The companies will work “even more closely together” because of the acquisition, Neptune CEO Piotr Niedźwiedź said in a blog.
The startup will wind down its external services in the coming months, Niedźwiedź said. The terms of the acquisition were not disclosed.
“Neptune has built a fast, precise system that allows researchers to analyze complex training workflows,” OpenAI’s Chief Scientist Jakub Pachocki said in a statement. “We plan to iterate with them to integrate their tools deep into our training stack to expand our visibility into how models learn.”
OpenAI has acquired several companies this year.
It purchased a small interface startup called Software Applications Incorporated for an undisclosed sum in October, product development startup Statsig for $1.1 billion in September and Jony Ive’s AI devices startup io for more than $6 billion in May.
Neptune had raised more than $18 million in funding from investors including Almaz Capital and TDJ Pitango Ventures, according to its website. Neptune’s deal with OpenAI is still subject to customary closing conditions.
“I am truly grateful to our customers, investors, co-founders, and colleagues who have made this journey possible,” Niedźwiedź said. “It was the ride of a lifetime already, yet still I believe this is only the beginning.”
A person walks by a sign for Micron Technology headquarters in San Jose, California, on June 25, 2025.
Justin Sullivan | Getty Images
Micron said on Wednesday that it plans to stop selling memory to consumers to focus on meeting demand for high-powered artificial intelligence chips.
“The AI-driven growth in the data center has led to a surge in demand for memory and storage,” Sumit Sadana, Micron business chief, said in a statement. “Micron has made the difficult decision to exit the Crucial consumer business in order to improve supply and support for our larger, strategic customers in faster-growing segments.”
Micron’s announcement is the latest sign that the AI infrastructure boom is creating shortages for inputs like memory as a handful of companies commit to spend hundreds of billions in the next few years to build massive data centers. Memory, which is used by computers to store data for short periods of time, is facing a global shortage.
Micron shares are up about 175% this year, though they slipped 3% on Wednesday to $232.25.
AI chips, like the GPUs made by Nvidia and AdvancedMicro Devices, use large amounts of the most advanced memory. For example, the current-generation Nvidia GB200 chip has 192GB of memory per graphics processor. Google’s latest AI chip, the Ironwood TPU, needs 192GB of high-bandwidth memory.
Memory is also used in phones and computers, but with lower specs, and much lower quantities — many laptops only come with 16GB of memory. Micron’s Crucial brand sold memory on sticks that tinkerers could use to build their own PCs or upgrade their laptops. Crucial also sold solid-state hard drives.
Micron competes against SK Hynix and Samsung in the market for high-bandwidth memory, but it’s the only U.S.-based memory supplier. Analysts have said that SK Hynix is Nvidia’s primary memory supplier.
Micron supplies AMD, which says its AI chips use more memory than others, providing them a performance advantage for running AI. AMD’s current AI chip, the MI350, comes with 288GB of high-bandwidth memory.
Micron’s Crucial business was not broken out in company earnings. However, its cloud memory business unit showed 213% year-over-year growth in the most recent quarter.
Analysts at Goldman on Tuesday raised their price target on Micron’s stock to $205 from $180, though they maintained their hold recommendation. The analysts wrote in a note to clients that due to “continued pricing momentum” in memory, they “expect healthy upside to Street estimates” when Micron reports quarterly results in two weeks.
A Micron spokesperson declined to comment on whether the move would result in layoffs.
“Micron intends to reduce impact on team members due to this business decision through redeployment opportunities into existing open positions within the company,” the company said in its release.
Microsoft pushed back on a report Wednesday that the company lowered growth targets for artificial intelligence software sales after many of its salespeople missed those goals in the last fiscal year.
The company’s stock sank more than 2% on The Information report.
A Microsoft spokesperson said the company has not lowered sales quotas or targets for its salespeople.
The sales lag occurred for Microsoft’s Foundry product, an Azure enterprise platform where companies can build and manage AI agents, according to The Information, which cited two salespeople in Azure’s cloud unit.
AI agents can carry out a series of actions for a user or organization autonomously.
Less than a fifth of salespeople in one U.S. Azure unit met the Foundry sales growth target of 50%, according to The Information.
In another unit, the quota was set to double Foundry sales, The Information reported. The quota was dropped to 50% after most salespeople didn’t meet it.
In a statement, the company said the news outlet inaccurately combined the concepts of growth and quotas.
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“Aggregate sales quotas for AI products have not been lowered, as we informed them prior to publication,” a Microsoft Spokesperson said.
The AI boom has presented opportunities for businesses to add efficiencies and streamline tasks, with the companies that build these agents touting the power of the tools to take on work and allow workers to do more.
OpenAI, Google, Anthropic, Salesforce, Amazon and others all have their own tools to create and manage these AI assistants.
But the adoption of these tools by traditional businesses hasn’t seen the same surge as other parts of the AI ecosystem.
The Information noted AI adoption struggles at private equity firm Carlyle last year, in which the tools wouldn’t reliably connect data from other places. The company later reduced how much it spent on the tools.