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Tag: NVIDIA

  • Age verification comes to Apple’s UK users, Nvidia reports record revenue – Tech Digest

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    Apple is bringing age verification to the UK    , as the latest iOS 26.4 beta prompts users to verify that they’re over 18 following installation. As shown in screenshots posted to Reddit, Apple says users who don’t confirm their age “will not be able to download and purchase apps or make in-app purchases.” In one of the screenshots, Apple notes that it may automatically confirm that users are over 18 using the payment method connected to their account, or the age of their account. Otherwise, Apple may ask users to scan their credit cards to confirm their age. The Verge 

    In a sprawling 20,000-word essay published last month, Dario Amodei, the chief executive of Anthropic, warned that advances in artificial intelligence could pave the way for a wave of killer robots. “A swarm of millions or billions of fully automated armed drones, locally controlled by powerful AI and strategically coordinated across the world by an even more powerful AI, could be an unbeatable army,” he wrote. He was not just worried about this threat coming from China or Russia but from Western democracies too. Telegraph 

    Mumsnet has launched a campaign to introduce a ban on social media for under-16s featuring health warnings in the style of those on cigarette packets. The deliberately provocative national advertising campaign calls for all social media to be banned for children under the age of 16. The images on billboards and social media make a number of stark statements related to health. They claim that “three hours or more social media a day makes teens more likely to self-harm.” Guardian 

    Nvidia boss Jensen Huang

    Chip giant Nvidia has reported record annual revenue of $215.9bn (£159.1bn), despite a wave of investor scepticism about the massive amounts of money being spent on artificial intelligence (AI) technology. The firm also beat analyst’s forecasts as sales for the last three months of its financial year jumped by 73% compared to 12 months earlier. “Computing demand is growing exponentially,” boss Jensen Huang said. “Our customers are racing to invest in AI compute – the factories powering the AI industrial revolution and their future growth.” BBC

    SpaceX has revealed that its “greatly enhanced” second generation (GEN2) of Direct to Cell (DtC) capable Starlink broadband satellites, which are due to launch in 2027, will aim to support 5G connectivity and deliver peak data speeds of 150Mbps (Megabits per second) per user. Starlink currently has around 9,800 satellites in Low Earth Orbit (LEO) – mostly at altitudes of between c.340-525km. Residential customers in the UK usually pay from £35 a month for the ‘Residential 100Mbps’ unlimited data plan (kit price may vary due to different offers), which also promises uploads of c.15-35Mbps and low latency connectivity. ISPreview

    The iPhone 18 Pro and Pro Max will have a smaller Dynamic Island, according to Bloomberg. Over the past year, there have been mixed rumors about whether the ‌iPhone 18‌ Pro models will continue to feature a ‌Dynamic Island‌ or have a hole punch camera with under screen Face ID and no ‌Dynamic Island‌, but the latest information suggests we’re not getting rid of the ‌Dynamic Island‌ just yet.

    Dynamic Island iPhone 18 Pro Feature
    Along with Bloomberg, several prominent leakers on Weibo and other social media sites have said Apple will make the Dynamic Island smaller, but won’t eliminate it. MacRumors 

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    Chris Price

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  • ‘Compute Equals Revenues’: Nvidia Needs Jensen Huang’s New Catchphrase to Be True

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    Nvidia reported earnings on Wednesday, and as expected, the numbers were good. Really good. The company gets more than 91% of its sales from its data center unit, which generated revenue of $193,737 billion, up 68% year-over-year.

    “We have now scaled our data center business by nearly 13x since the emergence of ChatGPT in fiscal 2023,” Nvidia CFO Colette Kress said in the company’s earnings call on Wednesday.

    While very impressive, the number is not all that surprising given that global AI spending is expected to reach $2.5 trillion this year, and Nvidia’s largest customers, the major AI hyperscalers Amazon, Alphabet, Meta, and Microsoft, all reported record capex figures earlier this month.

    The hyperscalers also made eyewatering financial commitments for 2026 totaling nearly $700 billion, which came to the dismay of many investors who have been growing wary of AI spending.

    Earlier this month, Evercore analysts warned that the huge capex could turn the hyperscalers’ cash flow negative.

    And despite the record after record multibillion-dollar commitment made to scale AI infrastructure and grow the technology’s adoption across the American economy, the results are yet to fully materialize. A Goldman Sachs analyst recently said that AI contributed “basically zero” to U.S. GDP in 2025.

    Nvidia CEO Jensen Huang spent most of his time in the investor call trying to justify that capex growth.

    “I am confident in their cash flow growing, and the reason for that is very simple: we have now seen the inflection of agentic AI and the usefulness of agents across the world in enterprises everywhere,” Huang said.

    AI adoption by enterprises beyond the tech world, and whether these companies actually see real productivity gains and revenue returns from AI integration, is really important to Nvidia, because that’s a major thing that the AI industry is currently lacking to quell worries over an AI bubble.

    A recent survey found that despite 70% of firms employing AI, over 80% reported no impact on employment or productivity.

    Last week, OpenAI COO Brad Lightcap told TechCrunch that his company had “not really seen enterprise AI penetrate enterprise business process.”

    Some experts believe that Anthropic’s Claude Cowork unveiled earlier this month is going to be a turning point in AI’s penetration into the workforce, so much so that they believe it will lead to a mass extinction-level event for software companies, and maybe even white-collar work. Huang gave a special shout-out to Claude Cowork in the call as well.

    Huang also had a technical explanation to justify the capex commitments.

    “In this new world of AI, compute equals revenues,” Huang said, a phrase that he repeated many times throughout the call. Huang argues that tokens, aka the chunks of data that AI models process, are the most important part of a new AI economy. The more tokens a model uses, the more computing power and time it requires. So, as models are getting more complex, the demand for computing is also going up “exponentially,” Huang said. He argued that the capex commitments will go towards building this compute capacity, which will thus power higher-level models and translate to revenue.

    “The amount of token generation capability that the world needs is a lot, more than $700 billion, and I’m fairly confident that we’re going to continue to generate tokens…fundamentally because every single company depends on software, every software will depend on AI, and so every company will produce tokens,” Huang said. “If the new software requires tokens to be generated and the tokens are monetized, then it stands to reason that their data center build-out directly drives their revenues.”

    Huang’s justifications may not have immediately convinced the market. Even though shares rose at first in response to the report, after the call, gains eventually pulled back to less than 1%. That’s despite revenue that exceeded market expectations.

    OpenAI and China are still blind spots

    Throughout the call, Huang also tried to address rumors of a falling out with OpenAI, first spurred after a $100 billion Nvidia investment announced back in September 2025 reportedly failed to progress beyond the early stages after months. Then, two back-to-back reports claimed that Huang was privately criticizing OpenAI’s business approach while OpenAI was unhappy with the inference speed of Nvidia’s chips.

    In the call on Wednesday, Huang repeatedly praised the AI giant’s offerings, but revealed that the investment was still not finalized.

    “We continue to work with OpenAI toward a partnership agreement, and believe we are close,” Huang said on the call. The filing also refuses to give any assurance that “a transaction will be completed.”

    Another piece of uncertainty weighing on Nvidia is China. The company shared that, as of this month, the Trump administration has finally allowed it to start shipping small amounts of its H200 chips to China, where it once held 95% of the market share before Trump first banned the chipmaker’s sales to China, sparking a saga of dizzying trade tit-for-tat between the two global superpowers. But executives still don’t know if the imports will be allowed in, and are not factoring it into the revenue they expect this year.

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    Ece Yildirim

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  • In Nvidia we trust — ‘The agentic AI inflection point has arrived’ says CEO Jensen Huang | Fortune

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    Once again, Nvidia CEO Jensen Huang had a simple response for investors who are worried that the AI spending race might be overblown.

    During the $4.8-trillion-valuation chip supplier’s earnings call on Wednesday, analysts pressed Huang on whether major cloud customers—whose capital expenditures are nearing $700 billion a year—could keep up the pace. According to Huang, it’s a no-brainer. In the new AI-based economy, compute and revenue are essentially the same thing. Without the capacity to generate AI tokens, which are the small chunks of chatbot outputs in the form of words and text, cloud providers don’t have way a to meaningfully grow.

    “I am confident in their cash flow growing,” said Huang, in response to a question. “And the reason for that is very simple.”

    “We have now seen the inflection of agentic AI and the usefulness of agents across the world and enterprises everywhere, and you’re seeing incredible compute demand because of it,” Huang continued. “In this new world of AI, compute is revenues. Without compute, there’s no way to generate tokens. Without tokens, there’s no way to grow revenues.”

    So, the hundreds of billions worth of capital expenditures now flow into AI, which eventually translates into growth, which translates “directly to revenues,” said Huang.

    Nvidia offered AI investors a glimpse of a hairpin-turn recovery with its results for the fourth quarter and the full year of fiscal 2026, with results showing record revenue of $68.1 billion for the quarter, beating guidance by about $3 billion. Those numbers were up 20% from the third quarter and a whopping 73% from a year ago. 

    Notably, the company released guidance for the first quarter of fiscal 2027 of $78 billion. Total supply-related commitments rose from $50.3 billion at the end of the third quarter to $95.2 billion at the end of the fourth quarter. In a statement, Nvidia said it has “strategically secured inventory and capacity to meet demand beyond the next several quarters.”

    Going into results, investors were primed for any sign—a sigh, a hesitation, anything—that might indicate that its gross margins might be slipping further. Previous guidance had called for 74.8% GAAP gross margin, which would signal a partial recovery, and Huang and chief financial officer Colette Kress have said the goal going into fiscal year 2027 is to hold margins “in the mid-70s.” 

    On cue, investors kept a gimlet-eyed focus on those figures on Wednesday. And Nvidia did not disappoint. The company’s GAAP gross margin rose to 75%, beating guidance and up from 73.4% in Q3, and non-GAAP gross margin clocked in at 75.2%. Nvidia’s stock rose more than 2% in the first phase of after-hours trading, though it quickly gave back much of those gains.

    In all, GAAP net income was up 35% quarter-over-quarter and 94% year-over-year to roughly $43 billion. GAAP diluted earnings-per-share came in up 35% at $1.76 for the quarter and nearly double compared to fiscal 2025. Net income also saw a bump related to Nvidia’s investment in Intel stock. Non-GAAP income, which doesn’t include the Intel investment gains, came in at $39.6 billion. 

    The Nvidia earnings results come amid a high-stakes backdrop of fears about AI over-investment, in the form of eye-popping capital expenditures among hyperscalers including Amazon, Meta, Microsoft, Oracle, and Alphabet that are locked in a frenzied AI race. A recent report from Moody’s flagged that some $662 billion in future data center lease commitments that have not yet begun remain off those companies’ balance sheets. 

    “Computing demand is growing exponentially,” said Huang in a statement. “Enterprise adoption of agents is skyrocketing. Our customers are racing to invest in AI compute—the factories powering the AI industrial revolution and their future growth.”

    For Nvidia, of course, a portion of that capex spending winds up in the company’s coffers to pay for its highly coveted—and premium-priced—chips. 

    Full-year revenue also soars

    For the full year, Nvidia revenues hit $215.9 billion, up 65% from last year; GAAP operating income was $130.4 billion and net income was $120.1 billion. In comparison, in fiscal year 2025, which ended in January 2025, Nvidia posted $130.5 billion in revenue, more than doubling the year prior’s $60.9 billion. Net income for that year was $72.9 billion and operating income more than doubled over the year before to $81.5 billion. Data center revenues for fiscal 2026 were $197.3 billion, up from $115.2 billion the previous year. 

    Across fiscal year 2026, revenues rose each quarter, from $44.1 billion in Q1, to $46.7 billion in Q2, to $57 billion in Q3, and now to $68.1 billion in Q4.

    Last quarter, CEO Jensen Huang directly attempted to quash fears about frothiness in the market on the Q3 call with analysts. 

    “There’s been a lot of talk about an AI bubble,” said Huang last quarter. “From our vantage point, we see something very different.”

    He said the industry has undergone three structural platform shifts: from traditional CPUs to GPU-driven computing, from traditional machine learning to generative AI, and from generative AI to agentic AI. Each transition, on its own, justifies massive investments. Huang said the first two shifts were fully funded through cost reductions and revenue growth, while the agentic AI is a new layer on top that will require investment. 

    CFO Kress said last quarter that Nvidia had “visibility” to $500 billion in revenue from its Blackwell and Rubin offerings from the start of the 2025 calendar year through the end of the 2026 calendar year. Kress also said that Nvidia believes total AI infrastructure investment could reach $3 trillion to $4 trillion annually by 2029 or 2030. 

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    Amanda Gerut

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  • BYD triples European sales, Gucci faces backlash over AI slop – Tech Digest

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    Wayve, the self-driving car firm set to launch robotaxis on UK roads, has raised 1.5 billion US dollars (£1.1 billion) from investors including Uber, Microsoft and chip giant Nvidia. It has secured 1.2 billion dollars (£890 million) through a funding round backed by the major tech firms, institutional investors and car makers, with Uber investing extra funds to help deliver its driverless taxi plans. The Series D funding round, which is one of the largest ever for a British start-up, values the London-based business at around 8.6 billion dollars (£6.4 billion). Standard 

    Gucci is facing a backlash after using AI to generate images to promote its forthcoming show at Milan Fashion Week. The images have been posted on social media – where users have questioned how using AI instead of human models and photographers is in keeping with the fashion house’s claim that it celebrates “creativity and Italian craftsmanship.” “Bleak days when Gucci can’t find a real human Milanese grandmother to wear an outfit from 1976,” said one in response to an AI-generated image of a glamourous older Italian woman in a classic Gucci outfit. BBC 

    Analyst firm Gartner thinks talk of placing datacenters in space has reached “peak insanity,” because orbiting facilities can’t be run economically or satisfy demand for compute power on Earth. “Datacenters in space won’t analyze data on Earth for Earth applications for decades, if ever,” states a report published this week titled “Orbital Datacenters Won’t Serve Terrestrial Needs, So Focus on Earth,” penned by distinguished VP analyst Bill Ray.“Companies are wasting money by pouring funds into the orbital data center ‘bubble’ because the economics do not work,” the analyst wrote. Register

    The Dark Sky weather app, with its ultra regional forecasts and rain-stopping predictions, was the best I’ve ever used – until Apple acquired it, integrated into Apple Weather app for iPhone and then shut it down. At the time, the team behind the app joined Apple to ease the transition. Now they’re back on the scene hoping to fill the void left behind by the standalone Dark Sky app. The new iPhone app (which will come to Android eventually) is called Acme Weather. The major unique selling point is the “alternate predictions”. Stuff 

    For years, the conversation around online safety centred on the “stranger danger” of chat rooms. However, a new risk has now emerged: the AI chatbot’s simulated empathy. New research from Vodafone reveals the scale of this shift. According to its study of 11-16-year-olds, a staggering 81% are now using AI chatbots. Most concerning to experts, however, is the emotional weight these interactions carry. Nearly a third (31%) of these young users feel the bot is an actual friend and 33% have shared secrets with an AI that they wouldn’t tell their parents, teachers, or even their closest human peers. ShinyShiny 


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    Chris Price

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  • Freeform raises $67M Series B to scale up laser AI manufacturing  | TechCrunch

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    Tech investors haven’t given up on the dream of making physical products with the same speed and ease as coding software. 

    Executives at Freeform, a startup developing a novel 3D printing system for metal components, told TechCrunch that the company raised a $67 million Series B to expand its manufacturing platform. 

    Investors include Apandion, AE Ventures, Founders Fund, Linse Capital, NVidia’s NVentures , Threshold Ventures, and Two Sigma Ventures. FreeForm declined to disclose the company’s post-financing valuation, which Pitchbook cites as $179 million.

    CEO and cofounder Erik Palitsch said the funding would allow the company to upgrade its current GoldenEye printing system, which uses 18 lasers to fuse metal powders into precision components, to a new version. Dubbed Skyfall, the next iteration of the platform would use hundreds of lasers to produce thousands of kilograms of metal parts each day. 

    That’s the culmination of a vision Palitsch and co-founder/president Thomas Ronacher launched in 2018. The two met while developing rocket engines at SpaceX, where they found that industrial machines for printing metal components are expensive, finicky, and not well designed for mass manufacturing. 

    Their new company would build its platform from the ground up to achieve higher throughput and flexibility, with an emphasis on active software controls. Palitsch says Freeform’s platform is “AI native,” noting a partnership with Nvidia that allows the company to access advanced GPUs.

    “I think we’re the only quote-unquote manufacturing company out there that has H200 clusters in a data center on site,” Paltisch told TechCrunch. “What are they doing? We’re running real-time physics-based simulations and learning all the different aspects of the end to end manufacturing workflow.”

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    The data collected by sensors in the company’s manufacturing platform and during the simulations allows Freeform to rapidly improve production quality and quantity. 

    “We have more meaningful data on the physics of the metal-printing process than any company in the world,” head of talent Cameron Kay said. 

    While Palitsch said he could not disclose any customers, he said the company is already delivering hundreds of “mission-critical” parts to buyers. Now, the company wants to hire as many as 100 new employees and expand its facility to start executing on its contract backlog. 

    Manufacturing-as-a-service has grown as a category as venture investors have taken a greater interest in building vehicles, robots, and energy production systems. For example, Hadrian recently earned a $1.6B valuation from its investors while developing automated production for defense, and VulcanForms and Divergent have raised hundreds of millions to develop metal-printing services of their own.

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    Tim Fernholz

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  • Humain CEO Tareq Amin Injects $3B Into Elon Musk’s xAI to Power Saudi A.I. Ambitions

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    Humain CEO Tareq Amin’s $3 billion investment in xAI positions Saudi Arabia at the center of a rapidly shifting global A.I. power structure. Photo by Amal Alhasan/Getty Images for Fortune Media

    Tareq Amin, CEO of Saudi Arabia’s largest A.I. company, Humain, has been on a dealmaking blitz since taking the helm of the Kingdom’s national A.I. initiative last year. His latest move: a $3 billion investment in Elon Musk’s xAI. The investment was made during xAI’s $20 billion fundraising round in January, Humain announced today (Feb. 18). The raise came just weeks before xAI merged with Musk’s SpaceX earlier this month, as Musk consolidates his A.I., communications and space ambitions ahead of a widely anticipated IPO.

    Founded in 2025 by Crown Prince Mohammed Bin Salman and backed by Saudi Arabia’s massive sovereign wealth fund, the Public Investment Fund. Humain sits at the center of the Kingdom’s push to diversify its economy beyond oil. A core part of that mandate: building sovereign A.I. infrastructure at home.

    The xAI stake is the latest example of Humain’s ability to “deploy meaningful capital behind exceptional opportunities where long-term vision, technical excellence and execution converge,” said Amin in a statement. Amin, who previously led Aramco Digital and Japan’s Rakuten Mobile, has spent the past several months striking blockbuster partnerships with U.S. tech heavyweights, including Nvidia, AMD, Cisco, Amazon Web Services and Groq (not xAI’s chatbot Grok).

    Humain did not respond to requests for comment from Observer.

    Most of the partnerships are focused on expanding Saudi Arabia’s data center footprint and compute capacity. A joint venture with AMD and Cisco, for example, aims to build domestic A.I. infrastructure capable of powering up to one gigawatt.

    xAI’s relationship with Humain dates back to November, when the companies unveiled plans for a 500-megawatt data center in Saudi Arabia. The facility—xAI’s first outside the U.S.—will run on Nvidia chips and deploy the company’s Grok models across the Kingdom.

    Humain’s deepening ties to xAI underscore a broader realignment in global A.I. alliances, with Gulf states emerging as critical capital providers and infrastructure hubs for American developers. In November, Humain and the United Arab Emirates’ A.I. company, G42, received U.S. approval to acquire up to 35,000 advanced A.I. chips each, marking a sharp reversal from earlier semiconductor export restrictions.

    Other regional players are also forging closer links with U.S. firms. G42 secured a $1.5 billion investment from Microsoft and is set to help develop Stargate UAE, an A.I. compute cluster in Abu Dhabi to be operated by OpenAI and Oracle.

    The Emirati-backed MGX has participated in large fundraising rounds for xAI, OpenAI and Anthropic, while Qatar’s sovereign wealth fund earlier this week joined Anthropic’s new $380 billion Series G financing—further cementing the Middle East’s growing influence over the future of A.I.

    Humain CEO Tareq Amin Injects $3B Into Elon Musk’s xAI to Power Saudi A.I. Ambitions

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    Alexandra Tremayne-Pengelly

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  • Fei-Fei Li and Andrej Karpathy Back a New A.I. Use Case: Simulating Human Behavior

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    A.I. pioneer Fei-Fei Li is lending her support to Simile’s effort to simulate human behavior at scale. John Nacion/Variety via Getty Images

    Every three months, public companies brace for analyst questions during quarterly earnings calls. But what if firms could predict these queries in advance and rehearse their responses? That’s one of the capabilities touted by Simile, a new A.I. startup spun out of Stanford and backed by acclaimed researcher Fei-Fei Li and OpenAI co-founder Andrej Karpathy.

    Simile emerged from stealth yesterday (Feb. 12) with $100 million in funding from a round led by Index Ventures. Alongside Li and Karpathy, the startup—which hasn’t disclosed its valuation—also counts investors including Quora co-founder Adam D’Angelo and Scott Belsky, a partner at A24 Films.

    Li and Karpathy both have close ties to Simile’s founding team, which includes Stanford researchers Joon Park, Percy Liang and Michael Bernstein. Li is the co-director of Stanford’s Human-Centered A.I. Institute and advised Karpathy during his Ph.D. study at the university. She is widely known for foundational work such as ImageNet, a large-scale image database that helped drive major breakthroughs in computer vision. Karpathy and Bernstein also contributed to that project.

    Simile’s mission of using A.I. to reflect and model societal behavior taps into an underexplored research area, according to Karpathy, who previously worked at OpenAI and Tesla before launching his own education-focused A.I. startup. While large language models typically present a single, cohesive personality, Karpathy argues they are actually trained on data drawn from vast numbers of people. “Why not lean into that statistical power: Why simulate one ‘person’ when you could try to simulate a population?” he wrote in a post on X.

    That idea underpins Simile’s broader goal. The Palo Alto-based startup aims to simulate the real-world effects of major decisions, from public policy to product launches, across virtual populations that mirror human behavior. The team has already tested this concept on a smaller scale through projects like Smallville, a 2023 Stanford experiment in which 25 autonomous A.I. agents interacted in a virtual environment.

    Now, Simile is scaling the approach for business use. After spending the past seven months developing its model, the company is already working with clients on applications ranging from product development to litigation forecasting. CVS Health Corporation, for example, uses Simile to create simulated focus groups, while Gallup uses the platform to build digital polling panels. For earning calls, Simile can predict about 80 percent of the questions that analysts ultimately ask, said Park, the startup’s CEO, during a recent appearance on TBPN.

    At present, Simile’s models are based on data from hundreds of thousands of people who have signed up for its studies. Over time, the company hopes to expand that to simulations representing the world’s entire population of roughly 8 billion people.

    Simile joins a growing wave of A.I. companies focused on using simulation to model real-world scenarios. Much of the existing research in this space has centered on physical systems, such as robotics and autonomous vehicles, through “world model” platforms developed by firms like Google and Nvidia.

    One of the most prominent figures in world models is Li herself. In 2024, she took a leave of absence from Stanford to launch World Labs, a startup that builds 3D digital environments from image and text prompts. The company has raised $230 million to date and is valued at more than $1 billion.

    Fei-Fei Li and Andrej Karpathy Back a New A.I. Use Case: Simulating Human Behavior

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    Alexandra Tremayne-Pengelly

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  • Goldman Sachs’ Information Chief Marco Argenti Deepens A.I. Push with Anthropic

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    Marco Argenti says A.I. agents are becoming “digital co-workers” across Goldman’s operations. Courtesy Goldman Sachs

    Marco Argenti, chief information officer at Goldman Sachs, is leading one of Wall Street’s most aggressive integrations of A.I. He has made a name for himself as an early adoptor of A.I. in finance through initiatives like the GS AI Assistant platform, which is offered to Goldman Sachs employees for tasks such as coding and translation, and last year’s pilot of A.I. software engineer Devin, made by Cognition Labs. More recently, the investment bank has been collaborating with Anthropic, using its Claude model primarily in its accounting and compliance departments, Argenti said in an interview with CNBC published today (Feb. 6).

    The goal is to speed up tasks that involve massive amounts of data without investing in more manpower. “Think of it as a digital co-worker for many of the professions within the firm that are scaled, complex and very process-intensive,” Argenti said.

    Argenti spent much of his career in the tech and cloud computing industries before joining Goldman Sachs in 2019. He previously served as vice president of technology at Amazon Web Services, overseeing serverless computing and virtual reality. Earlier in his career, he led developer experiences at Nokia.

    Anthropic is known for its A.I. coding assistant, which is widely used by engineers. Goldman Sachs quickly realized that the traits that make a good coder—such as applying logic and working with large volumes of complex data—could be applied to tasks across accounting and compliance, Argenti said. Outside those departments, Claude agents could also be used for employee surveillance and creating investment banking pitchbooks for clients, he revealed.

    Goldman Sachs and Anthropic did not respond to requests from Observer to comment on those efforts.

    A collaboration with Goldman Sachs is the latest win for Anthropic, which has positioned itself as an enterprise-focused A.I. company. Earlier this week, the startup’s release of coworking software with various industry plug-ins triggered a panic selloff in enterprise software stocks, as investors worried such tools could make existing products obsolete.

    Other Wall Street giants are also embracing A.I. agents. JPMorgan Chase currently has more than 500 A.I. use cases, ranging from customer service to idea generation and marketing, and draws upon models from both Anthropic and OpenAI to power its internal LLM Suite program. Morgan Stanley was an early client of OpenAI, using its tech to distill meeting notes, aid financial research and boost coding productivity.

    A.I.’s use in financial services has grown each year since 2022, according to a recent Nvidia survey, in which 100 percent of industry professionals said A.I. spending will either stay the same or increase in 2026. A.I. agents, in particular, are being used or assessed by 42 percent of respondents. Top workflows include knowledge management and retrieval, internal process optimization and customer support automation.

    Such widespread adoption will inevitably lead to industry-wide labor shifts. A.I. leaders and studies alike have warned that the technology could reshape or eliminate entry-level white-collar roles. It’s unclear how the use of A.I. would affect Goldman Sachs’ employees. But Argenti conceded that A.I.’s advancements could eliminate the need for third-party providers.

    Goldman Sachs’ Information Chief Marco Argenti Deepens A.I. Push with Anthropic

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    Alexandra Tremayne-Pengelly

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  • Forget AI Stocks: This REIT Could Be Your Ticket to AI Profits

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    AI stocks have been the hot trade over the past year. Companies like Nvidia have made a mint by developing GPUs and other chips for data centers training AI models. The semiconductor’s data center revenue has exploded 66% over the past year. That has helped drive a nearly 50% surge in Nvidia’s stock price in the last 12 months.

    However, the Nvidias of the world aren’t the only ticket to AI profits. AI companies need physical real estate to house all their Nvidia Blackwell GPUs and other tech hardware to support their AI ambitions. That’s opening the doors to a generational value-creation opportunity for Prologis (NYSE: PLD) to leverage its expertise in constructing powered building shells to cash in on the AI megatrend.

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    Image source: Getty Images.

    Prologis is one of the world’s largest real estate investment trusts (REITs). It has a nearly irreplaceable portfolio of roughly 5,900 buildings totaling 1.3 billion square feet across 20 countries. Prologis has developed many of these buildings from the ground up.

    The leading industrial REIT‘s development experience has led it to build a vast land bank to support its future growth. It has enough land to support $42.6 billion in total future investments. Prologis has also become a leader in installing solar and battery storage systems at its sites to provide for its customers’ power needs, installing over 1 gigawatt (GW) across its portfolio.

    Prologis’s experience in constructing powered building shells has led it to start investing developing data centers. It’s building these facilities on some of its land bank.

    The world needs to invest a staggering $7 trillion in data centers by 2030 to keep pace with the growth in compute power, according to McKinsey Research. Prologis is working to secure a slice of this massive opportunity. It has started developing modern AI-enabled buildings to suit the needs of large-scale data center operators. It will build facilities from the ground up or convert existing warehouses to data centers.

    Prologis believes that it can build up to 10 GW of data center capacity over the next decade. That would require an investment of $30 billion to $50 billion. The company estimates that this investment has the potential to create $7.5 billion to $25 billion in value for its shareholders. That’s due to the very lucrative economics of data center development projects. While each project costs $150 million to $500 million (much higher than a warehouse, which costs between $25 million and $75 million), the development yields are also much higher at 7.5% to 10% compared to 6%-7% for a warehouse development.

    Companies need physical space in data centers with secure power sources to support their AI operations. That has opened the doors to a very lucrative opportunity for Prologis to leverage its development experience, power expertise, and land bank to build data centers. These investments should be highly profitable for the REIT, making it a great way to grab some AI profits without chasing high-flying AI stocks like Nvidia.

    Before you buy stock in Prologis, consider this:

    The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Prologis wasn’t one of them. The 10 stocks that made the cut could produce monster returns in the coming years.

    Consider when Netflix made this list on December 17, 2004… if you invested $1,000 at the time of our recommendation, you’d have $450,256!* Or when Nvidia made this list on April 15, 2005… if you invested $1,000 at the time of our recommendation, you’d have $1,171,666!*

    Now, it’s worth noting Stock Advisor’s total average return is 942% — a market-crushing outperformance compared to 196% for the S&P 500. Don’t miss the latest top 10 list, available with Stock Advisor, and join an investing community built by individual investors for individual investors.

    See the 10 stocks »

    *Stock Advisor returns as of February 1, 2026.

    Matt DiLallo has positions in Prologis. The Motley Fool has positions in and recommends Nvidia and Prologis. The Motley Fool has a disclosure policy.

    Forget AI Stocks: This REIT Could Be Your Ticket to AI Profits was originally published by The Motley Fool

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  • NVIDIA is still planning to make a ‘huge’ investment in OpenAI, CEO says

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    NVIDIA CEO Jensen Huang told reporters that the company will “invest a great deal of money” in OpenAI’s latest funding round, according to Bloomberg, after The Wall Street Journal on Friday reported that the two companies were rethinking a previous $100 billion deal that hasn’t “progressed beyond the early stages” of negotiations. Speaking to reporters in Taipei this weekend, Huang reportedly said it could be “the largest investment we’ve ever made.”

    NVIDIA and OpenAI jointly announced in September that NVIDIA would be investing up to $100 billion in OpenAI to build 10 gigawatts of AI data centers. The companies said then that they were targeting the second half of 2026 for the first phase of the project to go online. Citing sources familiar with the discussions, The Wall Street Journal reported that Huang has highlighted privately that the agreement was nonbinding and has criticized OpenAI’s business approach as lacking discipline.

    According to Bloomberg, however, Huang called the report’s claims “nonsense,” and told reporters on Saturday, “I believe in OpenAI. The work that they do is incredible. They’re one of the most consequential companies of our time.” But, Bloomberg reports, he said NVIDIA’s investment in this funding round wouldn’t come near $100 billion.

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  • Nvidia CEO pushes back against report that his company’s $100B OpenAI investment has stalled | TechCrunch

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    Nvidia CEO Jensen Huang said Saturday that a recent report of friction between his company and OpenAI was “nonsense.”

    Huang’s comments came after The Wall Street Journal published a story late Friday claiming that Nvidia was looking to scale back its investment in OpenAI. The two companies announced a plan in September in which Nvidia would invest up to $100 billion in OpenAI and also build 10 gigawatts of computing infrastructure for the AI company.

    However, the WSJ said Huang has begun emphasizing that the deal is nonbinding, and that he’s also privately criticized OpenAI’s business strategy and expressed concerns about competitors like Anthropic and Google.

    The WSJ also reported that the two companies are rethinking their relationship — though that doesn’t mean cutting things off entirely, with recent discussions reportedly focusing on an equity investment of a mere tens of billions of dollars from Nvidia.

    An OpenAI spokesperson told the WSJ that the companies are “actively working through the details of our partnership,” adding that Nvidia “has underpinned our breakthroughs from the start, powers our systems today, and will remain central as we scale what comes next.”

    According to Bloomberg, reporters asked Huang about the report during a visit to Taipei. In response, he insisted that Nvidia will “definitely participate” in OpenAI’s latest funding round “because it’s such a good investment,” according to Bloomberg. 

    “We will invest a great deal of money,” Huang said. “I believe in OpenAI. The work that they do is incredible. They’re one of the most consequential companies of our time.”

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    He apparently declined to specify how much Nvidia would be investing, instead saying, “Let [OpenAI CEO Sam Altman] announce how much he’s going to raise — it’s for him to decide.”

    The WSJ reported in December that OpenAI is looking to raise a $100 billion funding round, while The New York Times said this week that Nvidia, Amazon, Microsoft, and SoftBank are all discussing potential investments.

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  • Redwood attracts Google for its $425M Series E as AI power needs rise | TechCrunch

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    Google is the latest investor to back Redwood Materials as the battery recycling and cathode production startup scales a new energy storage venture to power AI data centers and other industrial sites.

    Redwood Materials, founded by former Tesla CTO JB Straubel, last October raised $350 million in a Series E round led by venture firm Eclipse. The round included a new strategic investment by Nvidia’s venture capital arm, NVentures.

    More investors, including newcomer Google, have piled in since, pushing the Series E to $425 million, the company said. Existing investors Capricorn and Goldman Sachs have also returned with fresh investments.

    The company’s valuation was not publicly disclosed, but a source familiar with the round told TechCrunch its post-money valuation was north of $6 billion, more than a billion higher than its previous valuation. This latest investment pushes Redwood’s total capital raised to $4.9 billion.

    The attraction for Google, Nvidia, and others in this latest round appears to be energy storage — and its ability to power data centers — a newer business venture within Redwood.  

    Redwood Materials was founded in 2017 to create a circular supply chain for batteries. It initially focused on recycling scrap from battery production and consumer electronics like cell phone batteries and laptop computers. Redwood processes that scrap and extracts materials that are traditionally mined, like nickel and lithium. The newly processed materials are then sold to customers such as Panasonic, which use them to make batteries.

    Redwood has continued to expand its business beyond recycling. The Carson City, Nevada-based company added cathode production several years ago, and last summer, launched an energy-storage business that repurposes EV batteries that aren’t quite ready to be recycled and turns them into micro-grids that can supply power to AI data centers and large-scale industrial sites.

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    That new business, called Redwood Energy, got its start as the demand for data centers skyrocketed.

    “As electricity demand surges — driven by AI, data centers, manufacturing and electrification — energy storage is no longer optional; it is essential infrastructure,” the company said in a blog post announcing the new funding.

    And Redwood seems to have the means to power at least some of those data centers. The company said in June it recovers more than 70% of all used or discarded battery packs in North America, many of which can have a second life as energy storage.

    Redwood said last year it had more than 1 gigawatt-hour worth in its inventory and expected to receive another 4 gigawatt-hours over the coming months. The company expects to deploy 20 gigawatt-hours of grid-scale storage by 2028.

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    Kirsten Korosec

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  • Nvidia’s new AI weather models probably saw this storm coming weeks ago | TechCrunch

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    In the run-up to the winter storm currently pummeling much of the U.S., weather forecasts for some regions were all over the map, with snowfall predictions varying wildly. 

    Nvidia couldn’t have timed the release of its new Earth-2 weather forecasting models any better. Or, given how accurate the company claims the new models are, maybe it knew something we didn’t?

    The new AI models promise to make weather forecasting faster and more accurate. Nvidia claims that one model in particular, Earth-2 Medium Range, beats Google DeepMind’s AI weather model, GenCast, on more than 70 variables. GenCast, which Google released in December 2024, was itself significantly more accurate than existing weather models that were capable of generating forecasts up to 15 days out.

    Nvidia announced the new tools Monday at the American Meteorological Society meeting in Houston.

    “Philosophically, scientifically, it’s a return to simplicity,” Mike Pritchard, director of climate simulation at Nvidia, told reporters on a call before the meeting. “We’re moving away from hand-tailored niche AI architectures and leaning into the future of simple, scalable, transformer architectures.”

    Traditionally, most weather forecasts rely on simulations of physics as observed in the real world. AI models are a relatively recent addition. The Earth-2 Medium Range model is based on a new Nvidia architecture called Atlas, about which the company said it would release more details on Monday. 

    Alongside Medium Range, Nvidia’s Earth-2 suite includes a Nowcasting model and Global Data Assimilation model.

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    Nowcasting produces short-term predictions from zero to six hours into the future, and it’s aimed at helping meteorologists forecast the impacts of storms and other hazardous weather. 

    “Because this model is trained directly on globally available geostationary satellite observations, rather than region-specific physics model outputs, Nowcasting’s approach can be adapted anywhere on the planet with good satellite coverage,” Pritchard said. That should help governments of states and smaller countries understand how severe weather systems might affect their territories.

    The Global Data Assimilation model uses data from sources like weather stations and balloons to produce continuous snapshots of weather conditions at thousands of locations around the world. Those snapshots are then used as launching points for weather models to make their predictions. 

    Traditionally, those snapshots have required tremendous amounts of computing power before the forecasting work could begin. “It consumes roughly 50% of the total supercomputing loads of traditional weather [forecasting],” Pritchard said. “This model can do that in minutes on GPUs instead of hours on supercomputers.”

    The three new models join two existing ones: CorrDiff, which uses coarse-grained forecasts to generate speedy, high-resolution predictions, and FourCastNet3, which models individual weather variables like temperature, wind, and humidity.

    Pritchard said that the new models should give more users access to powerful weather forecasting tools, which have historically been the domain of wealthier countries and large corporations, which have the funds to pay for costly supercomputer time.

    “This provides the fundamental building blocks used by everyone in the ecosystem — national meteorological services, financial service firms, energy companies — anyone who wants to build and refine weather forecasting models,” Pritchard said. Some of the tools are already in use. Meteorologists in Israel and Taiwan have been using Earth-2 CorrDiff, for example, while The Weather Company and Total Energies are evaluating Nowcasting, Nvidia said.

    “For some users, it makes sense to subscribe to an enterprise centralized weather forecasting system. But for others like countries, sovereignty matters,” Pritchard said. “Weather is a national security issue, and sovereignty and weather are inseparable.”

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  • Invested Advisors Invests $1.38 Million in NVIDIA Corporation $NVDA

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    Invested Advisors purchased a new stake in NVIDIA Corporation (NASDAQ:NVDA – Free Report) in the 3rd quarter, according to the company in its most recent 13F filing with the Securities and Exchange Commission. The institutional investor purchased 7,417 shares of the computer hardware maker’s stock, valued at approximately $1,384,000. NVIDIA makes up about 1.9% of Invested Advisors’ portfolio, making the stock its 12th biggest position.

    Several other institutional investors and hedge funds have also recently added to or reduced their stakes in NVDA. Brighton Jones LLC increased its stake in NVIDIA by 12.4% in the 4th quarter. Brighton Jones LLC now owns 324,901 shares of the computer hardware maker’s stock valued at $43,631,000 after buying an additional 35,815 shares during the period. Bank Pictet & Cie Europe AG grew its holdings in shares of NVIDIA by 1.0% during the 4th quarter. Bank Pictet & Cie Europe AG now owns 2,346,417 shares of the computer hardware maker’s stock valued at $315,100,000 after acquiring an additional 22,929 shares in the last quarter. Highview Capital Management LLC DE increased its stake in shares of NVIDIA by 6.7% in the fourth quarter. Highview Capital Management LLC DE now owns 58,396 shares of the computer hardware maker’s stock worth $7,842,000 after acquiring an additional 3,653 shares during the last quarter. Hudson Value Partners LLC boosted its position in NVIDIA by 30.7% during the fourth quarter. Hudson Value Partners LLC now owns 50,658 shares of the computer hardware maker’s stock valued at $6,805,000 after purchasing an additional 11,900 shares during the last quarter. Finally, Wealth Group Ltd. grew its stake in NVIDIA by 15.7% in the first quarter. Wealth Group Ltd. now owns 6,598 shares of the computer hardware maker’s stock valued at $715,000 after purchasing an additional 896 shares in the last quarter. 65.27% of the stock is currently owned by hedge funds and other institutional investors.

    Insider Activity at NVIDIA

    In related news, Director Mark A. Stevens sold 350,000 shares of the company’s stock in a transaction on Friday, December 5th. The shares were sold at an average price of $181.73, for a total transaction of $63,605,500.00. Following the completion of the transaction, the director directly owned 7,049,803 shares in the company, valued at $1,281,160,699.19. This represents a 4.73% decrease in their position. The transaction was disclosed in a document filed with the Securities & Exchange Commission, which is available through this link. Also, EVP Debora Shoquist sold 80,000 shares of the stock in a transaction on Thursday, December 11th. The shares were sold at an average price of $178.90, for a total transaction of $14,312,000.00. Following the completion of the sale, the executive vice president directly owned 1,494,443 shares of the company’s stock, valued at approximately $267,355,852.70. This trade represents a 5.08% decrease in their ownership of the stock. Additional details regarding this sale are available in the official SEC disclosure. Over the last quarter, insiders sold 1,661,474 shares of company stock valued at $303,251,232. 4.17% of the stock is owned by corporate insiders.

    NVIDIA Stock Up 1.6%

    NVIDIA stock opened at $187.81 on Friday. The firm has a market cap of $4.56 trillion, a price-to-earnings ratio of 46.60, a P/E/G ratio of 0.92 and a beta of 2.31. The company has a debt-to-equity ratio of 0.06, a current ratio of 4.47 and a quick ratio of 3.71. NVIDIA Corporation has a fifty-two week low of $86.62 and a fifty-two week high of $212.19. The firm has a fifty day moving average price of $183.38 and a two-hundred day moving average price of $181.68.

    NVIDIA (NASDAQ:NVDA – Get Free Report) last issued its quarterly earnings results on Wednesday, November 19th. The computer hardware maker reported $1.30 earnings per share (EPS) for the quarter, beating the consensus estimate of $1.23 by $0.07. NVIDIA had a return on equity of 99.24% and a net margin of 53.01%.The company had revenue of $57.01 billion for the quarter, compared to the consensus estimate of $54.66 billion. During the same period last year, the business posted $0.81 earnings per share. The firm’s revenue was up 62.5% compared to the same quarter last year. As a group, analysts forecast that NVIDIA Corporation will post 2.77 earnings per share for the current year.

    NVIDIA Announces Dividend

    The firm also recently declared a quarterly dividend, which was paid on Friday, December 26th. Shareholders of record on Thursday, December 4th were given a $0.01 dividend. This represents a $0.04 annualized dividend and a yield of 0.0%. The ex-dividend date of this dividend was Thursday, December 4th. NVIDIA’s payout ratio is currently 0.99%.

    Wall Street Analysts Forecast Growth

    NVDA has been the subject of several research reports. Cantor Fitzgerald reiterated an “overweight” rating and set a $300.00 price target on shares of NVIDIA in a report on Thursday, November 20th. Stifel Nicolaus set a $250.00 price objective on shares of NVIDIA in a research report on Thursday, January 8th. Susquehanna boosted their target price on shares of NVIDIA from $230.00 to $250.00 and gave the stock a “positive” rating in a research report on Thursday, November 20th. Oppenheimer restated an “outperform” rating and set a $265.00 price target on shares of NVIDIA in a research note on Thursday, November 20th. Finally, The Goldman Sachs Group reaffirmed a “buy” rating and issued a $240.00 price objective (up previously from $210.00) on shares of NVIDIA in a research note on Friday, October 31st. Four research analysts have rated the stock with a Strong Buy rating, forty-seven have issued a Buy rating and two have issued a Hold rating to the stock. Based on data from MarketBeat.com, the company currently has a consensus rating of “Buy” and an average price target of $263.41.

    Get Our Latest Report on NVIDIA

    Key NVIDIA News

    Here are the key news stories impacting NVIDIA this week:

    NVIDIA Company Profile

    (Free Report)

    NVIDIA Corporation, founded in 1993 and headquartered in Santa Clara, California, is a global technology company that designs and develops graphics processing units (GPUs) and system-on-chip (SoC) technologies. Co-founded by Jensen Huang, who serves as president and chief executive officer, along with Chris Malachowsky and Curtis Priem, NVIDIA has grown from a graphics-focused chipmaker into a broad provider of accelerated computing hardware and software for multiple industries.

    The company’s product portfolio spans discrete GPUs for gaming and professional visualization (marketed under the GeForce and NVIDIA RTX lines), high-performance data center accelerators used for AI training and inference (including widely adopted platforms such as the A100 and H100 series), and Tegra SoCs for automotive and edge applications.

    Read More

    Institutional Ownership by Quarter for NVIDIA (NASDAQ:NVDA)



    Receive News & Ratings for NVIDIA Daily – Enter your email address below to receive a concise daily summary of the latest news and analysts’ ratings for NVIDIA and related companies with MarketBeat.com’s FREE daily email newsletter.

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  • Tech CEOs boast and bicker about AI at Davos | TechCrunch

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    There were times at this week’s meeting of the World Economic Forum when Davos seemed transformed into a high-powered tech conference, with on-stage appearances by Tesla CEO Elon Musk, Nvidia CEO Jensen Huang, Anthropic CEO Dario Amodei, Microsoft CEO Satya Nadella, and even more industry executives.

    The big topic, unsurprisingly, was AI, with CEOs laying a vision for the technology’s transformative potential while also acknowledging ongoing concerns that they’re inflating a massive bubble. Amidst all that big-picture prognostication, they also found time to take swipes at their competitors, and even at their ostensible partners.

    On the latest episode of TechCrunch’s Equity podcast, I discussed all things Davos with TechCrunch’s Kirsten Korosec and Sean O’Kane.

    Kirsten noted that the conference seemed transformed from past years, with tech companies like Meta and Salesforce taking over the main promenade, while important topics like climate change failed to draw crowds. And Sean said that even if AI execs weren’t quite “panhandling for usage and more customers,” it could sometimes feel that way.

    Read a preview of our full conversation, edited for length and clarity, below.

    Kirsten: Some of the discussions around, let’s say, climate change or poverty and big global problems, [are] not really attracting the crowds. Meanwhile, on the main promenade in Davos, Switzerland, some of the biggest storefronts have been converted and taken over by companies like Meta and Salesforce, Tata, also a lot of Middle East countries. And I think the largest was the USA House, which was sponsored by McKinsey and Microsoft. It really felt visually different.

    And then Elon Musk being there — Sean, you and I both listened to it. There wasn’t a lot of there there, but I will say that it was interesting that he showed up, because in the past he has avoided Davos.

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    Anthony: We were trying to pull out the tech content of Davos, [and] there are absolutely things that worth highlighting here, but it’s also striking how, especially as AI has become such a big business story, it’s hard to fully separate that from all the other threads going on in terms of bigger questions about international trade, about world politics.

    One of the big headlines coming out of [Davos], for us at least, was the remarks by the CEO of Anthropic, where he basically attacked this Trump administration decision to allow Nvidia to send chips to China. It’s a story that is a tech story, but it’s also a trade story, it’s a politics story.

    I think in terms of the substance of what he said, it felt consistent to me in the sense that he’s generally comfortable shooting his mouth off, and also that it’s this interesting line [in AI discourse] where there’s an element of criticism, but it also ties into this really intense AI hype. One of the phrases he used was that an AI data center is like a country full of geniuses. I have questions about that — but he’s like, “How could we possibly send all these chips to China if we’re worried about China? Because essentially we’re sending a country full of geniuses over to China and letting them control it.”

    Sean: You could probably fill a notebook with all the different weird phrases that these CEOs use this week. The other one that has been stuck in my mind is that Satya Nadella kept calling the data centers token factories, which is a wonderful abstraction of what he thinks they’re there for.

    You know, there were two things that really stuck out to me about all the different things that were said by these CEOs in different parts of the week. One is that they are definitely all sort of sniping at each other — not just Anthropic with Nvidia, which is interesting in its own right, because Anthropic is a huge Nvidia customer and uses Nvidia GPUs, and there’s an interesting tension there. But also just seeing them sitting them next to each other and really kind of pulling, know, putting the knives out a little bit more than we’re used to seeing.

    We know that they’re all jockeying to be the lead and that they’re also trying to hold on to talent without overspending themselves to death. And this was one of the first times where it really felt like that tension was palpable and that they were present for it. Those two things are not often true at the same time.

    The other thing, to your point about a lot of the geopolitics of it and the business of it — this was the most blatant that I feel like we’ve gotten these CEOs on record as far as what they think they need to continue succeeding.

    Satya Nadella — I think you could maybe unfavorably read it this way, but I don’t think it’s that unfavorable — more or less was like, “More people need to be using this or else it’s going to be a bubble and a popped bubble.” He took a much different position in some ways from Dario Amadei of Anthropic, because Nadella’s focus is really about trying to broadly scoop up as much usage as possible [and] how do we make sure that AI is equitable across all these different communities and throughout the globe, versus concentrated in one place, like only the wealthy places, which I thought was an interesting tension. But there is an element of him giving away the game of not really panhandling for usage and more customers … but kind of.

    And to that point, Jensen Huang of Nvidia did something similar, where he was more or less saying, “We’re not investing enough in this and we need more investment to be able to make this work.”

    Kirsten: Jensen’s comments were interesting because he really talked about it in terms of job creation, and one could give the counterpoint of, there will be a moment where the build out slows, but no one’s really talking about that right now.

    The other thing, I think, was a good point that you made, which is we’ve never really seen them all sort of together in a room sniping at each other. Oftentimes you’ll have like Sam Altman at a conference or Satya [Nadella], but here they are all together. So you’re hearing it in real time.

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  • A.I.’s Data Center Rush Will Create Six-Figure Trade Jobs, Jensen Huang Predicts

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    Jensen Huang speaks during the World Economic Forum in Davos on Jan. 21, 2026. Photo by Fabrice Coffrini/AFP via Getty Images

    Much has been said about A.I.’s potential to replace jobs. But Nvidia CEO Jensen Huang is more concerned about A.I. creating a labor shortage—at least in the short term. As tech companies race to build data centers across the U.S. and around the world, they will need tradespeople such as plumbers, electricians and construction workers to make it happen. “This is the largest infrastructure buildout in human history. That’s going to create a lot of jobs,” said Huang during an interview with BlackRock CEO Larry Fink at the World Economic Forum in Davos, Switzerland on Jan. 21.

    New labor opportunities will be especially concentrated in the trades, where Huang claims pay has already nearly doubled. Those who help build semiconductor plants, computer factories and data centers will soon be making “six-figure salaries,” according to the executive.

    “Everyone should be able to make a great living,” said Huang. “You don’t need a Ph.D. in computer science to do so.”

    The median annual pay for electricians in 2024 was around $62,000, according to the U.S. Bureau of Labor Statistics. It was roughly $46,000 for construction laborers and nearly $63,000 for plumbers, pipefitters and steamfitters. Growth for all three professions from 2024 to 2034 is expected to outpace the average occupational growth rate of 3 percent, with demand for electricians in particular surging. The field is projected to expand by 9 percent over the next decade, with about 81,000 openings projected annually on average.

    The U.S. is already seeing a “significant boom” in these areas, according to Huang—so much so that it has led to a “great shortage” in tradecraft roles. The A.I. boom is expected to worsen a worker deficit the industry was already facing. In December 2022, some 490,000 construction positions went unfilled, according to a McKinsey report, the highest level recorded this century.

    Huang isn’t the only CEO who believes A.I. will be a boon for trade jobs. Alex Karp, CEO of Palantir, described vocational skills as “very valuable, if not irreplaceable,” while speaking in Davos earlier this week. Ford CEO Jim Farley has made similar arguments on behalf of the blue-collar community, saying the country does not yet have a large enough workforce to support its data center ambitions. “I think the intent is there, but there’s nothing to backfill the ambition,” he told Axios in August.

    The opportunity for A.I.-driven manual labor jobs won’t be limited to the U.S., Huang added, but will extend around the world as data center construction accelerates. “There is not one country in the world I can imagine where you [don’t] need to have A.I. as part of your infrastructure.”

    A.I.’s Data Center Rush Will Create Six-Figure Trade Jobs, Jensen Huang Predicts

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  • A timeline of the US semiconductor market in 2025 | TechCrunch

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    Last year was a tumultuous one for the U.S. semiconductor industry.  

    From leadership changes at legacy companies to continuously changing dialogue around AI chip export controls, a lot has happened. If the first few weeks of 2026, which saw new chip tariffs and international semiconductor deals, are any indicator — this year will be as unexpected as the last.  

    But before we get too deep into 2026, here is a final look at everything that happened in the U.S. semiconductor industry in 2025:  

    December

    Nvidia finds gold with Groq 

    December 24: Nvidia announced that it struck a non-exclusive licensing deal with chip maker Groq. While this wasn’t an acquisition, Nvidia hired Groq’s founder and president, in addition to other employees. The company also bought $20 billion worth of Groq’s assets.  

    Chips to China 

    December 8: The U.S. Department of Commerce decided that Nvidia and AMD can send AI chips to China after all, a stark reversal to past messaging. The U.S. government specifically said Nvidia could sell its H200 chips, which are much more advanced than its H20 chips, to approved customers.  

    November 

    Nvidia keeps climbing 

    November 19: Nvidia reported record results in its third-quarter earnings report. The company racked up $57 billion in revenue in Q3, a 66% increase over the same quarter in 2024. A large portion of that revenue came from Nvidia’s data center business.  

    October

    Intel makes processor progress 

    October 9: Intel announced a new processor, dubbed Panther Lake, that is part of the company’s Intel Core Ultra processor family. This will be the first one built on the company’s 18A semiconductor process and will be exclusively made at Intel’s Arizona fab factory.  

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    September

    A taste of tariffs 

    September 26: We got the first inkling of what the Trump administration’s semiconductor tariffs could look like at the end of September. Rumors started swirling that the administration would require semiconductor companies to produce the same volume of chips domestically as they do internationally, or they would otherwise be subject to tariffs.  

    China shuts out Nvidia 

    September 17: China’s campaign against Nvidia continued when the country told its domestic companies not to buy Nvidia’s chips. The Cyberspace Administration of China banned local companies from buying Nvidia’s chips in an effort to boost domestic chip sales.  

    China calls out Nvidia

    September 15: Despite being given a loose green light to start selling chips again in China, the process was not going to be smooth sailing for Nvidia. China’s State Administration for Market Regulation ruled that Nvidia violated the country’s antitrust regulations regarding the company’s 2020 acquisition of Mellanox Technologies.  

    A leadership shakeup

    September 9: Just a few short weeks after the U.S. government took an equity stake in Intel, the company made some notable leadership changes. Michelle Johnston Holthaus, the chief executive officer of Intel products, departed after three decades. The company also created a central engineering group.  

    August

    Nvidia reports record quarter

    August 27: The turmoil in the semiconductor market over the year had clearly not hurt Nvidia. On August 27, the company reported that it had record sales in the second quarter. The highlights were the growth of its data center business, which saw its revenue grow 56% year over year.

    U.S. Government takes equity stake in Intel

    August 22: The U.S. government announced it was converting existing government grants into a 10% stake in Intel. The deal was structured to penalize Intel if the company’s ownership in its foundry program dropped below 50%.

    SoftBank takes a stake in Intel

    August 18: Japanese conglomerate SoftBank announced it was taking a $2 billion stake in Intel. SoftBank CEO Masayoshi Son called the deal “strategic.” The transaction was announced as rumors were swirling that the U.S. was going to take a stake in the company.

    Chip companies strike a deal to sell in China

    August 12: Nvidia and AMD announced that they struck a deal with the U.S. government to gain the necessary license to sell their AI chips in China. Both companies agreed to pay the U.S. government 15% of revenue from their chip sales in China.

    Trump and Lip-Bu Tan meet

    August 11: Intel CEO Lip-Bu Tan went to the White House to meet with President Trump. The pair talked about Tan’s past and how Intel can help the U.S. with its goal of bringing semiconductor manufacturing back to the U.S. Both called the conversation productive.

    Trump comes for Lip-Bu Tan

    August 7: President Donald Trump demanded that Intel CEO Lip-Bu Tan “resign immediately” due to “conflicts of interest” in a Truth Social post. While Trump didn’t clarify what the conflicts of interest were, this came the day after Republican Senator Tom Cotton sent a letter to Intel’s board of directors inquiring about Tan’s ties to China.

    Trump says tariffs are coming for the industry

    August 5: President Donald Trump told CNBC’s Squawk Box that he was planning to announce tariffs on the semiconductor industry as soon as the following week. At the time, he didn’t mention specifics on what these tariffs could look like. As of September 5, no tariffs have been announced for this industry.

    July

    Intel spins out business unit

    July 25: Just one day after its second-quarter earnings call, Intel confirmed that it was spinning out its Network and Edge group, which is responsible for making chips for the telecom industry. The business unit produced $5.8 billion in revenue for the semiconductor company in 2024.

    Intel continues to look for efficiency

    July 24: Intel announced that it was pulling back on some of its manufacturing operations. The company said it will longer pursue its previously announced projects in Germany and Poland and that it was consolidating its test operations. Intel also announced it plans to end this year with around 75,000 employees.

    Trump’s AI Action Plan

    July 23: The Trump administration unveiled its much-anticipated AI Action Plan alongside multiple related executive orders. While the plan included a lot regarding the need for U.S. chip export controls and for the U.S. to coordinate with its allies on this effort, it didn’t provide concrete information on what those restrictions would look like.

    Groundbreaking UAE AI deal reportedly on hold

    July 17: The Trump administration helped foster a groundbreaking deal in May that resulted in a commitment from the United Arab Emirates to buy billions of dollars’ worth of AI chips from Nvidia. But now that deal was reportedly on hold as the U.S. worked through national security concerns and fears that those chips could be smuggled from the Middle East to China.

    Nvidia is a bargaining chip

    July 16: A day after semiconductor firms like Nvidia and AMD got the green light to resume selling certain AI chips to China, we found out why. U.S. Commerce Security Howard Lutnick said the plans to allow U.S. companies to start selling AI chips in China are tied to ongoing trade discussions between the U.S. and China regarding rare earth elements.

    U.S. chips head back to China

    July 14: Nvidia said it was filing an application to restart sales of H20 AI chips in China, confirming rumors from a few weeks prior. The company also announced that it would be selling a new chip, the RTX Pro, which was designed specifically for the Chinese market.

    Malaysia fights chip smuggling

    July 14: Malaysia announced that it was launching trade permits for U.S.-made AI chips. Under this new restriction, any individual or business would need to give the Malaysian government 30 days’ notice before exporting any U.S. AI chips.

    June

    Intel appoints new leadership

    June 18: Intel announced four new leadership appointments that Intel said will help it move toward its goal of becoming an engineering-first company again. Intel announced a new chief revenue officer in addition to multiple high-profile engineering hires.

    Intel began layoffs

    June 17: Intel began laying off a significant chunk of its Intel Foundry staff in July, according to various media reports. The company later confirmed it was restructuring. Reports said it planned to eliminate 15% to 20%, of workers in that business unit. These layoffs weren’t a shock: Layoffs were rumored back in April, and Intel’s CEO Lip-Bu Tan had said he wants to flatten the organization.

    Nvidia won’t report on China

    June 13: Nvidia wasn’t counting on the U.S. backing off from its AI chip export restrictions. After the company took a financial hit from the newly imposed licensing requirements on its H20 AI chips, Nvidia CEO Jensen Huang said the company will no longer include the Chinese market in future revenue and profit forecasts.

    AMD acquired the team behind Untether AI

    June 6: AMD made another acquisition — this time focused on talent. The company acqui-hired the team behind Untether AI, which develops AI inference chips, as the semiconductor giant continues to round out its AI offerings.

    AMD is coming for Nvidia’s AI hardware dominance

    June 4: AMD continued its shopping spree. The company acquired AI software optimization startup Brium, which helps companies retrofit AI software to work with different AI hardware. With a lot of AI software being designed with Nvidia hardware in mind, this acquisition isn’t surprising.

    May

    Nvidia laid out the impact of chip export restrictions

    May 28: Nvidia reported that U.S. licensing requirements on its H20 AI chips cost the company $4.5 billion in charges during Q1. The company expected these requirements to result in an $8 billion hit to Nvidia’s revenue in Q2.

    AMD acquired Enosemi

    May 28: AMD kicked off its acquisition spree. The semiconductor company announced that it acquired Enosemi, a silicon photonics startup. Enosemi’s tech, which uses light photons to transmit data, is becoming an increasing area of interest for semiconductor companies.

    Tensions started to flare between China and the U.S.

    May 21: China’s Commerce Secretary didn’t like the U.S. guidance, issued on May 13, that warned U.S. companies that using Huawei’s AI chips “anywhere in the world” was a U.S. chip export violation. The commerce secretary issued a statement that threatened legal action against anyone caught enforcing that export restriction.

    Intel began the process to offload units

    May 20: Intel CEO Lip-Bu Tan seemingly got right to work on his plan to spin out Intel’s non-core business units. Back in May, the semiconductor giant was reportedly looking to offload its Networking and Edge units, which make chips for telecom equipment, and was responsible for $5.4 billion of the company’s 2024 revenue.

    The Biden administration’s AI Diffusion rule was officially dead

    May 13: Just days before the Biden administration’s Artificial Intelligence Diffusion Rule was set to go into place, the U.S. Department of Commerce formally rescinded it. The DOC said that it plans to issue new guidance in the future, and in the meantime, companies should remember that using Huawei’s Ascend AI chips anywhere in the world is a violation of U.S. export rules.

    A last-minute reversal

    May 7: Just a week before the “Framework for Artificial Intelligence Diffusion” was set to go into place, the Trump administration planned on taking a different path. According to multiple media outlets, including Axios and Bloomberg, the administration wouldn’t enforce the restrictions when they were supposed to start on May 15 and is instead working on its own framework. 

    April

    Anthropic doubles down on its support of chip export restrictions

    April 30: Anthropic doubled down on its support for restricting U.S.-made chip exports, including some tweaks to the Framework for Artificial Intelligence Diffusion, like imposing further restrictions on Tier 2 countries and dedicating resources to enforcement. An Nvidia spokesperson shot back, saying, “American firms should focus on innovation and rise to the challenge, rather than tell tall tales that large, heavy, and sensitive electronics are somehow smuggled in ‘baby bumps’ or ‘alongside live lobsters.’” 

    Planned layoffs at Intel

    April 22: Ahead of its Q1 earnings call, Intel said it was planning to lay off more than 21,000 employees. The layoffs were meant to streamline management, something CEO Lip-Bu Tan has long said Intel needed to do, and help rebuild the company’s engineering focus. 

    The Trump administration further restricts chip exports

    April 15: Nvidia’s H20 AI chip got hit with an export licensing requirement, the company disclosed in an SEC filing. The company added that it expected $5.5 billion in charges related to this new requirement in the first quarter of its 2026 fiscal year. The H20 was the most advanced AI chip Nvidia can still export to China in some fashion. TSMC and Intel reported similar expenses the same week. 

    Nvidia appears to talk its way out of further chip exports

    April 9: Nvidia’s CEO Jensen Huang was spotted attending dinner at Donald Trump’s Mar-a-Lago resort, according to reports. At the time, NPR reported Huang may have been able to spare Nvidia’s H20 AI chips from export restrictions upon agreeing to invest in AI data centers in the U.S. 

    An alleged agreement between Intel and TSMC

    April 3: Intel and TSMC allegedly reached a tentative agreement to launch a joint chipmaking venture. This joint venture would operate Intel’s chipmaking facilities, and TSMC would have a 20% stake in the new venture. Both companies declined to comment or confirm. If this deal doesn’t come to fruition, this is likely a decent preview of potential deals in the industry to come. 

    Intel warned it will spin off non-core assets

    April 1: CEO Lip-Bu Tan got to work right away. Just weeks after he joined Intel, the company announced that it was going to spin off non-core assets so it could focus. He also said the company would launch new products, including custom semiconductors for customers. 

    March

    Intel names a new CEO 

    March 12:  Intel announced that industry veteran and former board member Lip-Bu Tan would return to the company as CEO on March 18. At the time of his appointment, Tan said Intel would be an “engineering-focused company” under his leadership. 

    February

    Intel’s Ohio chip plant gets delayed again

    February 28: Intel was supposed to start operating its first chip fabrication plant in Ohio this year. Instead, the company slowed down construction on the plant for the second time in February. Now the $28 billion semiconductor project won’t wrap up construction until 2030 and may not even open until 2031.

    Senators call for more chip export restrictions

    February 3: U.S. senators, including Elizabeth Warren (D-Mass) and Josh Hawley (R-Mo), wrote a letter to Commerce Secretary Nominee-Designate Howard Lutnick, urging the Trump administration to further restrict AI chip exports. The letter specifically referred to Nvidia’s H20 AI chips, which were used in the training of DeepSeek’s R1 “reasoning” model. 

    January 

    DeepSeek releases its open “reasoning” model

    January 27: Chinese AI startup DeepSeek caused quite the stir in Silicon Valley when it released the open version of its R1 “reasoning” model. While this isn’t semiconductor news specifically, the sheer alarm in the AI and semiconductor industries DeepSeek caused continues to have ripple effects on the chip industry. 

    Joe Biden’s executive order on chip exports

    January 13: With just a week left in office, former president Joe Biden proposed sweeping new export restrictions on U.S.-made AI chips. This order created a three-tier structure that determined how many U.S. chips can be exported to each country. Under this proposal, Tier 1 countries faced no restrictions; Tier 2 countries had a chip purchase limit for the first time; and Tier 3 countries got additional restrictions. 

    Anthropic’s Dario Amodei weighs in on chip export restrictions

    January 6: Anthropic co-founder and CEO Dario Amodei co-wrote an op-ed in The Wall Street Journal endorsing existing AI chip export controls and pointing to them as a reason why China’s AI market was behind the U.S. He also called on incoming president Donald Trump to impose further restrictions and to close loopholes that have allowed AI companies in China to still get their hands on these chips.

    This story was originally published on May 9, 2025, and is regularly updated with new information.

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    Rebecca Szkutak

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  • Royal Bank Of Canada Reaffirms “Buy” Rating for NVIDIA (NASDAQ:NVDA)

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    NVIDIA (NASDAQ:NVDA – Get Free Report)‘s stock had its “buy” rating restated by stock analysts at Royal Bank Of Canada in a research report issued to clients and investors on Thursday, Marketbeat.com reports.

    Other equities analysts also recently issued research reports about the company. Deutsche Bank Aktiengesellschaft upped their target price on NVIDIA from $180.00 to $215.00 and gave the company a “hold” rating in a report on Thursday, November 20th. Citigroup reaffirmed a “buy” rating on shares of NVIDIA in a research report on Monday, December 29th. Zacks Research cut shares of NVIDIA from a “strong-buy” rating to a “hold” rating in a research report on Monday, January 12th. Wolfe Research raised their price objective on shares of NVIDIA from $230.00 to $250.00 and gave the stock an “outperform” rating in a report on Thursday, November 20th. Finally, Oppenheimer reissued an “outperform” rating and issued a $265.00 target price on shares of NVIDIA in a research report on Thursday, November 20th. Four research analysts have rated the stock with a Strong Buy rating, forty-seven have issued a Buy rating, three have issued a Hold rating and one has issued a Sell rating to the company’s stock. Based on data from MarketBeat.com, NVIDIA has a consensus rating of “Moderate Buy” and an average target price of $263.41.

    Check Out Our Latest Analysis on NVDA

    NVIDIA Trading Down 0.3%

    Shares of NVDA opened at $186.54 on Thursday. The firm has a fifty day simple moving average of $184.23 and a two-hundred day simple moving average of $180.61. NVIDIA has a twelve month low of $86.62 and a twelve month high of $212.19. The stock has a market capitalization of $4.53 trillion, a P/E ratio of 46.29, a PEG ratio of 0.91 and a beta of 2.31. The company has a quick ratio of 3.71, a current ratio of 4.47 and a debt-to-equity ratio of 0.06.

    NVIDIA (NASDAQ:NVDA – Get Free Report) last posted its earnings results on Wednesday, November 19th. The computer hardware maker reported $1.30 earnings per share for the quarter, topping analysts’ consensus estimates of $1.23 by $0.07. NVIDIA had a net margin of 53.01% and a return on equity of 99.24%. The company had revenue of $57.01 billion during the quarter, compared to analyst estimates of $54.66 billion. During the same period in the prior year, the business posted $0.81 earnings per share. NVIDIA’s revenue for the quarter was up 62.5% on a year-over-year basis. On average, research analysts anticipate that NVIDIA will post 2.77 EPS for the current year.

    Insiders Place Their Bets

    In related news, Director Mark A. Stevens sold 222,500 shares of the stock in a transaction dated Friday, December 19th. The shares were sold at an average price of $180.17, for a total transaction of $40,087,825.00. Following the sale, the director directly owned 7,621,453 shares of the company’s stock, valued at approximately $1,373,157,187.01. This represents a 2.84% decrease in their position. The sale was disclosed in a document filed with the SEC, which can be accessed through this hyperlink. Also, EVP Ajay K. Puri sold 200,000 shares of NVIDIA stock in a transaction dated Wednesday, January 7th. The stock was sold at an average price of $187.82, for a total transaction of $37,564,000.00. Following the completion of the transaction, the executive vice president directly owned 3,818,547 shares of the company’s stock, valued at $717,199,497.54. This trade represents a 4.98% decrease in their ownership of the stock. Additional details regarding this sale are available in the official SEC disclosure. In the last ninety days, insiders sold 1,734,114 shares of company stock valued at $317,034,081. Company insiders own 4.17% of the company’s stock.

    Hedge Funds Weigh In On NVIDIA

    Several hedge funds and other institutional investors have recently added to or reduced their stakes in NVDA. State Street Corp raised its position in NVIDIA by 1.0% in the 2nd quarter. State Street Corp now owns 978,208,862 shares of the computer hardware maker’s stock worth $154,556,803,000 after buying an additional 9,554,857 shares during the last quarter. Geode Capital Management LLC raised its holdings in shares of NVIDIA by 1.5% during the second quarter. Geode Capital Management LLC now owns 579,213,497 shares of the computer hardware maker’s stock valued at $91,150,170,000 after purchasing an additional 8,521,936 shares during the last quarter. Kingstone Capital Partners Texas LLC lifted its position in NVIDIA by 267,959.7% during the second quarter. Kingstone Capital Partners Texas LLC now owns 382,373,765 shares of the computer hardware maker’s stock valued at $64,976,521,000 after purchasing an additional 382,231,120 shares during the period. Norges Bank purchased a new stake in NVIDIA in the second quarter worth approximately $51,386,863,000. Finally, Legal & General Group Plc grew its position in NVIDIA by 1.5% in the 3rd quarter. Legal & General Group Plc now owns 181,203,035 shares of the computer hardware maker’s stock worth $33,808,862,000 after purchasing an additional 2,609,560 shares during the period. 65.27% of the stock is owned by institutional investors.

    Key Stories Impacting NVIDIA

    Here are the key news stories impacting NVIDIA this week:

    About NVIDIA

    (Get Free Report)

    NVIDIA Corporation, founded in 1993 and headquartered in Santa Clara, California, is a global technology company that designs and develops graphics processing units (GPUs) and system-on-chip (SoC) technologies. Co-founded by Jensen Huang, who serves as president and chief executive officer, along with Chris Malachowsky and Curtis Priem, NVIDIA has grown from a graphics-focused chipmaker into a broad provider of accelerated computing hardware and software for multiple industries.

    The company’s product portfolio spans discrete GPUs for gaming and professional visualization (marketed under the GeForce and NVIDIA RTX lines), high-performance data center accelerators used for AI training and inference (including widely adopted platforms such as the A100 and H100 series), and Tegra SoCs for automotive and edge applications.

    Featured Stories

    Analyst Recommendations for NVIDIA (NASDAQ:NVDA)



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    ABMN Staff

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  • ASUS has stopped producing the NVIDIA RTX 5070 Ti and 5060 Ti 16GB, saying they’ve reached ‘end of life’

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    YouTube channel Hardware Unboxed is reporting that ASUS has stopped producing the RTX 5070 Ti and 5060 Ti 16GB due to the ongoing memory crunch. In its most recent video, the channel states ASUS “explicitly” told it the RTX 5070 Ti is “currently facing a supply shortage.” As a result, the company has “placed the model into end of life status,” and no longer plans to produce it.

    Hardware Unboxed also spoke to retailers in Australia, who told the channel the 5070 Ti is “no longer available to purchase from partners and distributors,” adding they expect that to be the case throughout at least the first quarter of the year. The 5060 Ti 16GB “is almost done as well,” with ASUS stating it no longer plans to produce that model going forward either. Both GPUs are 16GB models, making them more expensive to manufacture in the current economic climate. And while there might be some hope of the 5070 Ti and 5060 Ti 16GB returning later this year, the channel suggests both are unlikely to make a comeback.

    “Demand for GeForce RTX GPUs is strong, and memory supply is constrained. We continue to ship all GeForce SKUs and are working closely with our suppliers to maximize memory availability,” a NVIDIA spokesperson told Engadget. ASUS did not immediately respond to Engadget’s comment request.

    After uploading its video, Hardware Unboxed published a clarification. “ASUS did not tell us that NVIDIA said the RTX 5070 Ti has been discontinued. ASUS told us there is very little supply of the 5070 Ti, so their own 5070 Ti products (e.g, the Prime and TUF Gaming) have been put into end of life status,” the channel said. “With retailers also unable to source 5070 Ti SKUs from any AIB, this effectively makes it a dead product.”

    The AI boom has created an insatiable demand for RAM and other computer components from data center infrastructure companies. In response, many memory manufacturers have shifted their production lines to focus on high bandwidth memory for those clients at the expense of their regular offerings, leading to dramatically increased prices among consumer RAM kits, GPUs and SSDs. In December, Micron Technology announced it would wind down its consumer-facing Crucial brand to focus exclusively on providing components to the AI industry.

    ASUS is the first of NVIDIA’s add-in board (AIB) partners to comment on the memory crunch. AIBs are the companies that produce the majority of GPUs you can buy from NVIDIA and AMD. Historically, NVIDIA has provided its board partners with both the die and memory needed to make a graphics cards. However, a recent rumor suggested the company had told it partners they would need to start sourcing memory on their own.

    Update 12:55PM ET: Added more context.

    Update 2:06PM ET: Added comment from NVIDIA.

    Update 6:31PM ET: Added additional comment from Hardware Unboxed.

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    Igor Bonifacic

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  • How AMD Stock Beat the Market (and Nvidia) in 2025

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    • AMD stock rose 77.3% in 2025, nearly doubling the S&P 500’s return and outpacing Nvidia in the last three months.

    • OpenAI signed a multi-year deal to buy 6 gigawatts of AMD Instinct AI accelerators, representing a $120 billion revenue opportunity over the next 5 years.

    • The deal signals that AMD can compete with Nvidia for high-end AI workloads.

    • 10 stocks we like better than Advanced Micro Devices ›

    Shares of AMD (NASDAQ: AMD) rose 77.3% in 2025, according to data from S&P Global Market Intelligence. In the same period, the S&P 500 (SNPINDEX: ^GSPC) market index gained 16.4% and AMD rival Nvidia (NASDAQ: NVDA) jumped 38.9% higher.

    Prediction Market powered by

    AMD’s price chart stayed close to Nvidia’s (and far above the broader market’s) through the first 9 months of last year, indicating continued investor interest in the artificial intelligence (AI) boom that started in November of 2022. But AMD took a solid year-to-date lead in October as a key AI player committed to buying a lot of AMD’s Instinct chips over the next few years.

    On Oct. 6, ChatGPT developer OpenAI unveiled a multi-year contract that will put 6 gigawatts of AMD Instinct AI accelerators in OpenAI’s data centers over the next five years. The deal could also make OpenAI a major owner of AMD stock, as it includes stock warrants for up to 160 million AMD shares that will vest (convert into common shares) as AMD delivers its gigawatts of number-crunching hardware. That would be approximately 10% of AMD’s stock.

    The shipments will start in the second half of 2026 and ramp up to larger volumes and next-generation Instinct chips in 2027. AMD CEO Lisa Su called the agreement “a true win-win,” and OpenAI CEO Sam Altman highlighted AMD’s high-performance products.

    AMD’s stock skyrocketed 26% that fine Monday, rising 41% in one week. OpenAI’s hardware deals have market-moving power.

    Image source: Advanced Micro Devices.

    There are a few important quirks in AMD’s OpenAI deal.

    One AMD Instinct card draws roughly 1,000 watts of power. Thus, 6 gigawatts’ worth of these AI accelerators should involve approximately 6 million processors. The current generation of Instinct MI350 cards is priced in the neighborhood of $20,000 per card, and the improved MI 450 series that OpenAI is buying (and later generations in a 5-year deal) may carry a higher price. So AMD’s revenue opportunity works out to $120 billion or more. Again, it’s over 5 years but still a significant growth driver.

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