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Tag: NVIDIA

  • SoftBank’s Nvidia sale rattles market, raises questions | TechCrunch

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    Masayoshi Son isn’t known for half measures. The SoftBank founder’s career has been studded with eyebrow-raising bets, each one seemingly more outrageous than the last.

    His latest move is to cash out his entire $5.8 billion Nvidia stake to go all-in on AI. And while it surprised the business world on Tuesday, it maybe should not. At this point, it’s almost more surprising when the 68-year-old Son doesn’t push his chips to the center of the table.

    Consider that during the late 1990s dot-com bubble, Son’s net worth soared to about $78 billion by February 2000, briefly making him the richest person in the world. Then came the ugly dot-com implosion months later. He lost $70 billion personally – which, at the time, was the largest financial loss by any individual in history — as SoftBank’s market cap plummeted 98% from $180 billion to just $2.5 billion. 

    Amid that terribleness, Son made what would become his most legendary bet: a $20 million investment in Alibaba in 2000, one decided (the story goes) after just a six-minute meeting with Jack Ma. That stake would eventually grow to be worth $150 billion by 2020, transforming him into one of the venture industry’s most celebrated figures and funding his comeback.

    That Alibaba success has often made it harder to see when Son has stayed too long at the table. When Son needed capital to launch his first Vision Fund in 2017, he didn’t hesitate to seek $45 billion from Saudi Arabia’s Public Investment Fund – long before taking Saudi money became acceptable in Silicon Valley.

    After journalist Jamal Khashoggi was murdered in October 2018, Son condemned the killing as “horrific and deeply regrettable” but insisted SoftBank couldn’t “turn our backs on the Saudi people,” maintaining the firm’s commitment to managing the kingdom’s capital. In fact, the Vision Fund actually ramped up dealmaking soon after.

    That didn’t turn out so well.

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    A big bet on Uber generated paper losses for years. Then came WeWork. Son overrode his lieutenants’ objections, fell “in love” with founder Adam Neumann, and assigned the co-working company a dizzying valuation of $47 billion in early 2019 after making several previous investments in the company. But WeWork’s IPO plans collapsed after it published a famously troubling S-1 filing. The company never quite recovered – even after pushing out Neumann and instituting a series of belt-tightening measures – ultimately costing SoftBank $11.5 billion in equity losses and another $2.2 billion in debt. (Son reportedly later called it “a stain on my life.”)

    Son has been mounting another comeback for years, and Tuesday will undoubtedly be remembered as an important moment in his turnaround tale. Indeed, it will likely be recalled as the day SoftBank revealed it had sold all 32.1 million of its Nvidia shares – not to diversify its bets but instead to double down elsewhere, including on a planned $30 billion commitment to OpenAI and to participate (it reportedly hopes) in a $1 trillion AI manufacturing hub in Arizona. 

    If selling that position still gives Son some heartburn, that’s understandable. At about $181.58 per share, SoftBank exited just 14% below Nvidia’s all-time high of $212.19, which is a strong look. That’s remarkably close to peak valuation for such a huge position. Still, the move marks SoftBank’s second complete exit from Nvidia, and the first one was exceedingly costly. (In 2019, SoftBank sold a $4 billion stake in the company for $3.6 billion, shares that would now be worth more than $150 billion.)

    The move also rattled the market. As of this writing, Nvidia shares are down nearly 3% following the disclosure, even as analysts emphasize that the sale “should not be seen as a cautious or negative stance on Nvidia,” but rather reflects SoftBank needing capital for its AI ambitions.

    Wall Street can’t help but wonder: does Son see something right now that others do not? Judging by his track record, maybe — and that ambiguity is all investors have to go on.

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    Connie Loizos

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  • Michael Burry of ‘The Big Short’ Made a Huge Bet Against These Two AI Giants

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    Michael Burry is betting that AI is more likely a bubble than a revolutionary movement. His fund, Scion Asset Management, revealed November 3 that it invested in the fall of Palantir and Nvidia’s stocks.

    Burry made a fortune when he predicted the 2008 financial crisis and bet against the U.S. housing market collapse. His instinct led to the creation of “The Big Short” book and movie, and carved out his position as an iconic investor.

    Now, he’s taking a controversial stand on the AI boom. On October 30, Burry posted on X, “Sometimes, we see bubbles. Sometimes, there is something to do about it. Sometimes, the only winning move is not to play.” His words stood alongside a still from “The Big Short.”

    Four days later, Scion Asset Management disclosed that it bought around $912 million in put options on Palantir and $187.6 million on Nvidia. 

    Tech and AI stocks have been top of the market recently. But On November 4 Nasdaq reported its worst day since August, falling 2.04 percent, while the S&P 500 sank 1.17 percent. Both indexes encapsulate majority tech companies. 

    Burry’s move is catching eyes amid growing concerns from investors that the market is overly concentrated on a few large companies. But his calls haven’t always been right. In 2023 he posted on X, “Sell,” and then two months later, “I was wrong to say sell.”

    Palantir’s shares are up 152 percent this year, but on November 4 they fell 7.95 percent. Nvidia’s tumbled 3.96 percent, though its shares are still up 48 percent this year. 

    Burry’s public position could have an impact, said Angelo Zino, a tech analyst at CFRA Research.

    “Despite the great results, when you coincide that with the comments that Michael burry made and everybody already talking about concerns about an AI bubble, I think the combination of those factors really helped drive a pullback in the shares, the broader tech index and as a result the broader markets,” Zino said. “We’re not overly concerned about the pullback, but I would say it’s one of those situations where you’ve got to keep an eye on it.” 

    On the other hand, Palantir CEO Alex Karp called him “crazy,” and his behavior “crazy motivating.” 

    “When I hear short sellers attacking what I believe is clearly the most important software company in America, therefore in the world, in terms of our impact,… it just is super triggering,” Karp said in a CNBC interview. “Every time they short us, we are just like tripling down on getting the better numbers, in part honestly, to make them poorer.” 

    The early-rate deadline for the 2026 Inc. Regionals Awards is Friday, November 14, at 11:59 p.m. PT. Apply now.

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    Ava Levinson

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  • How Twelve Labs Teaches A.I. to ‘See’ and Transform Video Understanding: Interview

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    Soyoung Lee, co-founder and head of GTM at Twelve Labs, pictured at Web Summit Vancouver 2025. Photo by Vaughn Ridley/Web Summit via Sportsfile via Getty Images

    Sure, the score of a football game is important. But sporting events can also foster cultural moments that slip under the radar—such as Travis Kelce signing a heart to Taylor Swift in the stands. While such footage could be social-media gold, it’s easily missed by traditional content tagging systems. That’s where Twelve Labs comes in.

    “Every sports team or sports league has decades of footage that they’ve captured in-game, around the stadium, about players,” Soyoung Lee, co-founder and head of GTM at Twelve Labs, told Observer. However, these archives are often underutilized due to inconsistent and outdated content management. “To date, most of the processes for tagging content have been manual.”

    Twelve Labs, a San Francisco-based startup specializing in video-understanding A.I., wants to unlock the value of video content by offering models that can search vast archives, generate text summaries and create short-form clips from long-form footage. Its work extends far beyond sports, touching industries from entertainment and advertising to security.

    “Large language models can read and write really well,” said Lee. “But we want to move on to create a world in which A.I. can also see.”

    Is Twelve Labs related to Eleven Labs?

    Founded in 2021, Twelve Labs isn’t to be confused with ElevenLabs, an A.I. startup that specializes in audio. “We started a year earlier,” Lee joked, adding that Twelve Labs—which named itself after the initial size of its founding team—often partners with ElevenLabs for hackathons, including one dubbed “23Labs.”

    The startup’s ambitious vision has drawn interest from deep-pocketed backers. It has raised more than $100 million from investors such as Nvidia, Intel, and Firstman Studio, the studio of Squid Game creator Hwang Dong-hyuk. Its advisory bench is equally star-studded, featuring Fei-Fei Li, Jeffrey Katzenberg and Alexandr Wang.

    Twelve Labs counts thousands of developers and hundreds of enterprise customers. Demand is highest in entertainment and media, spanning Hollywood studios, sports leagues, social media influencers and advertising firms that rely on Twelve Labs tools to automate clip generation, assist with scene selection or enable contextual ad placements.

    Government agencies also use the startup’s technology for video search and event retrieval. Beyond its work with the U.S. and other nations, Lee said that Twelve Labs has a deployment in South Korea’s Sejong City to help CCTV operators monitor thousands of camera feeds and locate specific incidents. To reduce security risks, the company has removed capabilities for facial and biometric recognition, she added.

    Will video-native A.I. come for human jobs?

    Many of the industries Twelve Labs serves are already debating whether A.I. threatens humans jobs—a concern Lee argues is only partly warranted. “I don’t know if jobs will be lost, per se, but jobs will have to transition,” she said, comparing the shift to how tools like Photoshop reshaped creative roles.

    If anything, Lee believes systems like Twelve Labs’ will democratize creative work traditionally limited to companies with big budgets. “You are now able to do things with less, which means you have more stories that can be created from independent creatives who do not have that same capital,” she said. “It actually allows for the scaling of content creation and personalizing distribution.”

    Twelve Labs is not the only A.I. player eyeing video, but the company insists it serves a different need than its much larger competitors. “We’re excited that video is now starting to get more attention, but the way we’re seeing it is a lot of innovation in large language models, a lot of innovation in video generation models and image generation models like Sora—but not in video understanding,” said Lee, referencing OpenAI’s text-to-video A.I. model and app.

    For now, Twelve Labs offers video search, video analysis and video-to-text capabilities. The company plans to expand into agentic platforms that can not only understand video but also build narratives from it. Such models could be useful beyond creative fields, Lee said, pointing to examples like retailers identifying peak foot-traffic hours or security clients mapping the sequence of events surrounding an accident.

    While A.I. might help a Hollywood director assemble a movie, Lee believes it won’t ever be the director. Even if the technology can provide narrative options, humans still decide which story is most compelling, identify gaps and supply the footage. “At the end of the day, I think there’s nothing that can replace human creative intent.”

    How Twelve Labs Teaches A.I. to ‘See’ and Transform Video Understanding: Interview

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    Alexandra Tremayne-Pengelly

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  • Nvidia and Palantir Stocks Are Falling Today. Here’s Why

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    Shares in two closely watched AI-adjacent companies, Nvidia Corporation and Palantir Technologies, are falling this morning. Currently, Nvidia shares are down more than 2.2% and Palantir shares are down more than 6%.

    The share price drops of two of the most prominent AI companies come as investors seem increasingly worried that the AI boom is starting to look more like an AI bubble, reminiscent of the dotcom bubble of the late ’90s and early 2000s.

    In part due to these concerns, an increasing number of investors have recently begun betting against the stocks of companies benefitting from the artificial intelligence boom—including Michael Burry, the investor who became famous for betting against the housing market before the 2008 financial crash. Here’s what you need to know.

    “Big Short” investor bets against Nvidia and Palantir

    In the years leading up to the 2008 housing market crash, investor Michael Burry made a killing by shorting housing-related stocks after seeing signs of the then-upcoming housing market crash that few others noticed.

    In 2015, Burry was immortalized in The Big Short, the Oscar-winning film about the 2008 financial crash, in which he was played by Christian Bale.

    Burry has since gained a substantial following among some investors, and so his investment moves often gain widespread attention. Recently, his move has been to bet against the stock prices of Nvidia (Nasdaq: NVDA) and Palantir (Nasdaq: PLTR).

    As noted by Bloomberg, Bury’s Scion Asset Management recently revealed in a 13F regulatory filing that it bought put options on NVDA and PLTR.

    The news of Scion’s puts followed a Halloween post from Burry on X in which the hedge fund manager issued a cryptic post reading “Sometimes, we see bubbles. Sometimes, there is something to do about it. Sometimes, the only winning move is not to play,” along with an image of his Big Short character played by Bale.

    Burry’s puts seem to have struck a nerve with Palantir CEO Alex Karp, who on Tuesday told CNBC’s Squawk Box that the companies Burry is betting against “are the ones making all the money, which is super weird.”

    Karp added that “The idea that chips and ontology is what you want to short is batshit crazy.”

    Then again, plenty of people thought Burry was crazy for shorting housing stocks in the years ahead of the 2008 crash.

    Palantir’s Tuesday share slide comes after the company reported Q3 earnings yesterday, in which it saw revenue climb 63%. The software company has been among the highest-growth stocks of 2025.

    Fears of an AI bubble loom large

    Regardless of whether Burry’s puts against Nvidia and Palantir end up being the right move, his move seems to have spurred at least some investors to offload NVDA and PLTR shares, as of the time of this writing.

    It should also be noted that Burry is far from the only one who sees signs of an AI bubble. Many investors and industry experts have begun to question whether the industry is in a bubble—and what would happen if that bubble pops. 

    For instance, an October Bank of America Global Research survey found that 54% of investors believe AI stocks are in a bubble, as Reuters recently reported.

    Even so, today’s share price drops in NVDA and PLTR are minuscule compared to their surging stock prices in recent years. Year-to-date, Nvidia has seen its stock price surge more than 50% and PLTR is up more than 150%.

    Over the past 12 months, NVDA has risen more than 48% and PLTR has risen more than 350%. 

    By Michael Grothaus

    This article originally appeared in Inc.’s sister publication, Fast Company.

    Fast Company is the world’s leading business media brand, with an editorial focus on innovation in technology, leadership, world changing ideas, creativity, and design. Written for and about the most progressive business leaders, Fast Company inspires readers to think expansively, lead with purpose, embrace change, and shape the future of business.

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    Fast Company

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  • Exclusive | Trump Officials Torpedoed Nvidia’s Push to Export AI Chips to China

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    Shortly before President Trump met Chinese leader Xi Jinping in South Korea, an urgent issue emerged. Trump wanted to discuss a request by Nvidia Chief Executive Jensen Huang to allow sales of a new generation of artificial-intelligence chips to China, current and former administration officials said.

    Greenlighting the export of Nvidia’s Blackwell chips would be a seismic policy shift potentially giving China, the U.S.’s biggest geopolitical competitor, a technological accelerant. Huang—who speaks to Trump often—has lobbied relentlessly to maintain access to the Chinese market.

    Copyright ©2025 Dow Jones & Company, Inc. All Rights Reserved. 87990cbe856818d5eddac44c7b1cdeb8

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    Lingling Wei

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  • Sequoia’s Roelof Botha warns founders about chasing sky-high valuations as the firm doubles down on its selective approach | TechCrunch

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    The Trump administration has begun taking direct equity stakes in American companies, not as temporary crisis measures, as in 2008, but as permanent fixtures of industrial policy.

    The moves raise interesting questions, including what happens when the White House appears on a cap table.

    At TechCrunch Disrupt in San Francisco last week, Sequoia Capital’s global steward Roelof Botha fielded exactly that query, and his response drew knowing laughter from the packed house: “[Some] of the most dangerous words in the world are: ‘I’m from the government, and I’m here to help.’”

    Botha, who describes himself as “sort of libertarian, free market thinker by nature,” said that industrial policy has its place when national interests demand it. “The only reason the U.S. is resorting to this is because we have other nation states with whom we compete who are using industrial policy to further their industries that are strategic and maybe adverse to the U.S. in long term interests.” In other words, China’s playing the game, so the U.S. has to play along.

    Still, his discomfort with government as co-investor was unmistakable during his appearance. And that wariness extends beyond Washington. In fact, Botha sees troubling echoes of the pandemic-era funding circus in today’s market, though he stopped short of using the word “bubble” on stage. “I think we’re in a period of incredible acceleration,” he offered more diplomatically, while also warning about valuation inflation.

    He told the audience that, on the very morning of his appearance, Sequoia had debriefed about a portfolio company whose valuation soared from $150 million to $6 billion in twelve months during 2021, only to come crashing back down to Earth. “The challenge you have inside the company for the founders and the team, [is] you feel as though you’re on this trajectory, and then you end up being successful, but it’s not quite as good as you hoped at one point.”

    It’s tempting to keep raising money to maintain momentum, he continued, but the faster a valuation climbs, the harder it can fall, and nothing demoralizes a team quite like watching a paper fortune evaporate.

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    His advice for founders navigating these frothy waters was two-pronged: if you don’t need to raise for at least twelve months, don’t. “You’re probably better off building because your company will be worth so much more 12 months from now,” he said. On the other hand, he added, if you’re six months from needing capital, raise now while the money’s flowing, because markets like the one we’re in can sour quickly.

    Being the sort of person who studied Latin in high school (his words), Botha reached for classical mythology to drive the point home. “I did read the story of Daedalus and Icarus in Latin. And that stuck with me, this idea that if you fly too hard, too fast, your wings may melt.”

    When founders hear Botha opine on the market, they pay attention, and understandably so. The firm’s portfolio includes early bets on Nvidia, Apple, Google, and Palo Alto Networks. Botha also kicked off his Disrupt appearance with news about Sequoia’s two newest investment vehicles: new seed and venture funds that give the firm $950 million more to invest and are “essentially the same size as the funds we launched six, seven years ago,” said Botha onstage.

    Though Sequoia changed its fund structure in 2021 in order to hold public stock for longer periods, Botha made clear it is still very much an early-stage shop at its core. He said that over the last twelve months, Sequoia has invested in 20 seed-stage companies, nine of them at incorporation. “There’s nothing more thrilling than partnering with founders right at the beginning.” Sequoia is “more mammalian than reptilian,” he continued. “We don’t lay 100 eggs and see what happens. We have a small number of offspring, like mammals, and then you need to give them a lot of attention.”

    It’s a strategy rooted in experience, he said. “In the last 20-25 years, 50% of the time we’ve made a seed or venture investment, we fail to fully recover capital, which is humbling.” After his own first complete write-off, Botha said he cried at a partner meeting out of shame and embarrassment. “But unfortunately, that is part of what we have to do to achieve outliers.”

    What accounts for Sequoia’s success? After all, a lot of firms invest in seed-stage companies. Botha partly credited a decision-making process that even surprised him when he joined two decades ago: every investment requires partnership consensus, with each partner’s vote carrying equal weight regardless of tenure or title.

    Each Monday, he explained, the firm kicks off partner meetings with an anonymous poll to surface the range of opinions about materials the partners are asked to digest over the weekend. Side conversations are verboten. “The last thing you want is alliances to form,” Botha said. “Our goal is great investment decisions.”

    The process can test patience — Botha once spent six months lobbying partners on a single growth investment — but he’s convinced it’s essential. “No one, not even me, can force an investment through our partnership.”

    Despite Sequoia’s success, or perhaps because of it, Botha’s most provocative position is that venture capital isn’t really an asset class or, at least, it shouldn’t be treated as one. “If you take out the top 20 or so venture firms out of the industry’s results, we [as an industry] actually underperformed investing in an index fund,” he said flatly onstage. He pointed to the 3,000 venture firms now operating in America alone, which is triple the number when Botha joined Sequoia. “Throwing more money into Silicon Valley doesn’t yield more great companies,” he said. “It actually dilutes that. It actually makes it harder for us to get the small number of special companies to flourish.”

    The solution, in his view, is: stay small, stay focused, and remember that “there are only so many companies that matter.” It’s a philosophy that has served Sequoia for decades. And in a moment when Uncle Sam wants on your cap table and VCs are throwing money at anything that moves, it might be the most contrarian advice of all.

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    Connie Loizos

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  • NVDA: Nvidia Stock Rises as Amazon Unleashes Massive AI Spending Wave

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    This article first appeared on GuruFocus.

    Nvidia (NASDAQ:NVDA) shares ticked higher after investors cheered fresh signs of sustained hyperscaler and national-level AI spending. The stock rose about 1% on Friday to roughly $205, rebounding from a pullback the day before.

    The move followed Amazon’s signal that it will keep accelerating AI infrastructure investments, with capital spending plans running into the tens of billions and a large portion earmarked for AI hardware, news that underpins cloud demand for Nvidia chips.

    At the same time Nvidia said it will supply more than 260,000 of its Blackwell AI chips to South Korea’s government and major companies, including large allocations for Samsung, SK Group, Hyundai and Naver. Samsung alone plans to deploy about 50,000 units for a new megafactory, giving Nvidia multi-year revenue visibility from big national projects.

    Analysts say the combination of hyperscaler purchasing and large corporate/government orders supports a durable demand backdrop for AI GPUs, though investors should watch supply dynamics and pricing as the buildouts progress.

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  • Samsung is using NVIDIA chips to build its new AI chip factory

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    NVIDIA has teamed up with with South Korea’s biggest companies and the country itself, as they build out their AI infrastructure. One of those companies is Samsung, which is building a new AI factory that will use 50,000 NVIDIA Blackwell server GPUs and other NVIDIA technologies to make its own chips. This “AI-driven semiconductor manufacturing,” as the companies call it, will help Samsung improve its processes, better predict maintenance needs and improve the efficiency of its autonomous operations. NVIDIA will help Samsung adapt its chipmaking lithography platform to work with its GPUs, and it will apparently result in 20 times greater performance for Samsung.

    Korean carmaker Hyundai will also use 50,000 NVIDIA Blackwell GPUs to develop its AI models for manufacturing and autonomous driving. Meanwhile, the SK Group conglomerate, which includes SK Telecom and DRAM and flash memory chip supplier SK Hynix, will use 50,000 NVIDIA Blackwell server chips to launch an industrial AI cloud. The facility, NVIDIA says, will power the “next generation of memory, robotics, digital twins and intelligent AI agents.” As Bloomberg reports, NVIDIA CEO Jensen Huang, who’s in South Korea for the Asia-Pacific Economic Cooperation CEO Summit, was recently photographed with Samsung’s Jay Y. Lee and Hyundai’s Chung Euisun in a local restaurant.

    Finally, NVIDIA is working with the South Korean government for its sovereign AI infrastructure, or AI it will have control over. The Korean government will deploy 50,000 NVIDIA GPUs to the National AI Computing Center it’s establishing, as well to facilities owned by local companies that include Kakao and Naver.

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    Mariella Moon

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  • Nvidia is reportedly investing up to $1B in Poolside  | TechCrunch

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    Nvidia is an existing investor in the AI company and participated in its $500 million Series A round in 2024.

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    Rebecca Szkutak

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  • Nvidia Has Started the $5 Trillion Club. Here’s a Look at Its Rise, by the Numbers

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    Nvidia on Wednesday became the first public company to reach a market capitalization of $5 trillion.

    The ravenous appetite for the Silicon Valley company’s chips is the main reason that the company’s stock price has increased so rapidly since early 2023.

    Nvidia carved out an early lead in tailoring its chipsets known as graphics processing units, or GPUs, from use in powering video games to helping to train powerful AI systems, like the technology behind ChatGPT and image generators. Demand skyrocketed as more people began using AI chatbots. Tech companies scrambled for more chips to build and run them.

    Nvidia’s journey to be one of the world’s most prominent companies has produced some eye-popping numbers. Here’s a look.

    23 percent

    The percentage of stock-focused mutual funds and exchange traded funds tracked by Morningstar Direct with exposure to Nvidia. That’s 1,435 out of 6,198, and the exposure totaled about $1.3 trillion in market value across all the funds.

    $5.03 trillion

    Nvidia’s total market capitalization as of the close of trading Wednesday, tops in the S&P 500.

    Microsoft at $4.025 trillion and Apple at $4 trillion were next among the most valuable companies in the S&P 500. In all, nine companies in the index have market cap’s above $1 trillion.

    79

    The number of trading days it took for Nvidia’s market cap to grow from $4 trillion to $5 trillion. The market cap had jumped from $3 trillion on May 13, to $4 trillion on July 9 (41 trading days), although Nvidia had crossed and fallen back below the $3 trillion threshold a number of times between June 2024 and May 2025 before making the run to $4 trillion.

    18.6 percent

    The company’s contribution to the gain in the S&:P 500 this year as of Sept. 30, according to S&P Dow Jones Indices. Nvidia shares gained 39 percent in the first nine months of the year.

    $179.6 billion

    The net worth of Nvidia CEO Jensen Huang, according to Forbes, putting him eighth on its Real-Time Billionaires List. Elon Musk is No. 1 at $500.2 billion.

    $4.28 trillion

    The gross domestic product of Japan, the world’s fourth largest economy, according to the International Monetary Fund.

    $24.2 billion

    The amount of money Nvidia said it returned to shareholders in the form of stock buybacks and dividends in the first half of fiscal 2026.

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    Associated Press

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  • Nvidia CEO Jensen Huang Makes His Case for China Trade

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    Nvidia’s first ever GTC to be hosted in Washington D.C.—a conference that’s been deemed the “Super Bowl of AI”—was a rare occasion that brought together both government officials and the tech industry under one roof.

    It was an opportunity for the tech executives in attendance to advocate for industry friendly policies straight to the government. Unsurprisingly, CEO Jensen Huang was first to take advantage of that opportunity to the fullest.

    “America needs to be the most aggressive in adopting AI technology of any country in the world, bar none, and that is an imperative. We can’t regulate our way out of this, we can’t fear-monger our way out of this,” Huang said in a press and industry briefing. “We have to encourage every single company, every single student, to use AI.”

    The leather jacket-clad executive spent most of his crowd-facing time repeating Trump administration talking points on bringing back manufacturing or lauding the President. He also spent time trying to make the case for the normalization of trade ties with China.

    “As it turns out, the best benefit to United States is for American technology to be available in China to win the hearts and minds of their developers,” Huang said. “A policy that causes America to lose half of the world’s AI developers is not beneficial long term, it hurts us more. It hurts America more than it hurts them.”

    Huang also argued that because China is a huge creator of open source software, if Americans retreat completely from China they might risk being “ill-prepared” for when Chinese software “permeates the world.”

    The U.S.-China trade war has impacted so many parts of the global economy, but the tech industry has been at the forefront, with Nvidia right in the bullseye.

    The Biden administration was first to enforce export restrictions on Nvidia’s chips sales to China, due to national security concerns and competitive fears. The restrictions got even stricter under Trump after Beijing landed a big blow to American AI confidence earlier this year with DeepSeek’s R1, a model that rivaled some of the best American AI offerings despite using lower cost chips. It showed the U.S. that Chinese developers did not need access to the highest tech Nvidia chips to make models that outperform expectations.

    The few months of the Trump imposed blanket exports ban was a big hit to Nvidia: executives shared in a May earnings call that they were revising revenue expectations for the quarter down by about $8 billion because of it.

    After a months-long noteworthy lobbying effort by Huang, Trump decided to relax the rule in July, but then demanded a 15% cut from China sales in return.

    Now, Huang reveals there’s not yet a signed document for that arrangement.

    “The administration is working on that, and until then, we don’t really have to confront it, because, you know, obviously China hasn’t decided to allow our chips to go back to China,” Huang said.

    After Trump okayed the sale of Nvidia’s chips to China, it was now Beijing’s turn to take a hard stance on the chipmaker.

    Chinese authorities have started discouraging local industry titans from purchasing Nvidia chips.

    The reason for that could be because Beijing has decided to decouple its AI industry from American tech.

    Chinese AI industry is currently dependent on American chipmakers like Nvidia, and that gives Americans an edge, especially when the only chips they allow in are lower-model ones. In the absence of Nvidia chips, China will have to develop their own high-tech chips that can rival, and perhaps even surpass, the quality of Nvidia chips. If that happens, the United States can be at jeopardy to lose its hold on the global chips market to China.

    After Trump’s blanket ban earlier this year choked off flow of Nvidia chips, Chinese chip development ramped up. China chip stocks are now experiencing a major boom, so big that Cambricon had to warn investors recently that things might be getting a little too hot.

    In its latest earnings call, Nvidia executives conceded that they were facing disappointing numbers from the region still because H20 chip shipments were yet to begin. Now, Huang is working hard to turn those numbers back up.

    Huang took to the stage at the press briefing with secretary of energy Chris Wright, in light of the tech giant’s announcement that it would be building seven giant AI supercomputers for the Department of Energy. Wright shared that he is optimistic that the two global superpowers would soon have a trade agreement.

    “China is an economic, scientific powerhouse, so we have some differences across the nations, but we have a lot of common ground,” Wright said.

    Trump is currently in South Korea, where he is scheduled to meet Chinese President Xi Jinping in a couple of hours. Huang said on Tuesday that he was flying out very soon to meet the President in South Korea, and he was notably missing from GTC on Wednesday.

    While Huang refused to answer questions on whether or not he would be joining the meeting between Trump and Xi Jinping, he did say that he had “a lot of announcements to make there.”

    While aboard Air Force One to South Korea, Trump told reporters that he might talk about the sale of Nvidia’s Blackwell model chips to China in his meeting with the President. He called the chips “super-duper.”

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  • Nvidia becomes the world’s first $5 trillion company, buoyed by AI boom

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    Nvidia on Wednesday became the first publicly listed company to be valued at $5 trillion, driven by investor confidence in the growth of artificial intelligence.

    Nvidia’s shares rose $9.08, or 4.5%, to $210.11 in early morning trading, lifting its market capitalization to $5.1 trillion. The company crossed the new threshold less than four months after it had reached a market value of $4 trillion in July. 

    The Santa Clara, California-based company has been buoyed by growing demand for its graphics processing units, or GPUs, which are used in AI applications as well as video gaming. Its shares have surged 51% this year amid plans to roll out new products such as an updated quantum computing platform, as well as partnerships with businesses including AI leaders such as OpenAI and Palantir. 

    “Nvidia’s chips remain the new oil or gold in this world for the tech ecosystem as there is only one chip in the world fueling this AI revolution … and it’s Nvidia,” Wedbush analyst Dan Ives said in an Oct. 28 research note. 

    Hitting the new market benchmark underscores the upheaval caused by AI, a development widely viewed as the biggest shift in tech since Apple co-founder Steve Jobs unveiled the first iPhone 18 years ago. Apple rode the iPhone’s success to become the first publicly traded company to be valued at $1 trillion, $2 trillion and, eventually, $3 trillion.

    But some on Wall Street are voicing concerns about a possible AI bubble, with officials at the Bank of England earlier this month cautioning about the growing risk that tech stock prices pumped up by the AI boom could burst. The surge in AI-related stocks has lifted the stock market as a whole, with the S&P 500 hitting a record high on Tuesday. 

    “The rally, led by technology stocks riding the artificial intelligence wave, has caused many market-watchers to question whether the stock market is in a bubble and if dotcom crash 2.0 might be coming,” said Jeff Buchbinder, chief equity strategist for LPL Financial, in an email, referring to the 2001 crash in internet-based companies.

    But, he added, some differences make the comparison less apt, including that companies spending on AI investments today are cash-rich with strong business models generating “massive cash flow.” 

    “[W]e don’t think technology’s run is necessarily over,” he noted.

    Edited by

    Alain Sherter

    The Associated Press

    contributed to this report.

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  • Nvidia and Oracle Are Planning the ‘Largest Supercomputer’ in America for Trump

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    Nvidia and Oracle will build the Department of Energy’s largest AI supercomputer, Nvidia CEO Jensen Huang announced on Tuesday, at the company’s first ever GTC AI conference to be held in Washington D.C.

    Huang, at one point during the reception, even asserted from Nvidia’s booth in the expo that he is planning “the largest supercomputer—AI supercomputer—in America for DOE.”

    Along with the federally-funded Argonne National Laboratory, the two tech giants will build a total of seven new AI supercomputers.

    “The majority of that computational power will be used for commercial applications to drive American business,” secretary of energy Chris Wright said in a press briefing following Huang’s keynote event, adding that “a significant minority” will be used towards science and national security.

    Construction will begin immediately, with computing power starting to flow into the Department as early as next week, according to Wright. The first of the seven supercomputers is expected to be delivered in 2026, with the largest one coming later.

    “I’m like a kid in a candy store,” the secretary said.

    Wright said that he was the one that reached out to “the players in the industry” to ink partnerships to “supercharge” the Department’s scientific and national defense efforts.

    The announcement is the latest in a string of collaborations between Nvidia and the government, showing an ever-growing connection between the AI industry and the Trump administration.

    Trump, although missing from the conference, was practically everywhere on Tuesday.

    “The original plan was Trump was going to be here,” Huang told attendees ahead of his keynote speech. Trump is instead in a whirlwind diplomacy tour across Asia.

    Huang shared that he will be joining the President on the South Korea leg of the tour, where Trump is supposed to have a key meeting with China’s Xi Jinping. The meeting will be decisive for trade relations between the two countries, which has an undeniably large impact on Nvidia’s business.

    Huang thanked the Trump administration repeatedly in his keynote speech on Tuesday, and ended it by shouting “Thank you for making America great again!” to the crowd of tech enthusiasts, GPU fanboys and government officials.

    In a press briefing following the keynote, he thanked secretary Wright and President Trump for their energy policies.

    “I’m so grateful that President Trump is pro-energy,” Huang said. “With administrations and others vilifying the use of energy, it was very difficult for the United States to win the AI race or to win any industrial race.”

    AI has monstrous energy demands and gulps up insane amounts of water, often putting a strain on communities local to data centers. These AI data centers also have a massive carbon footprint, with the energy demand causing increasing greenhouse gas emissions and contributing further to climate change.

    In a departure from the Biden administration, Trump is very okay with carbon-intensive energy and doesn’t necessarily believe in climate change. In fact, he has canceled billions of dollars in funding for clean energy projects, and reportedly is eyeing even more cuts.

    In the briefing, Huang also repeatedly promised an all-American assembly line, something that the administration has put significant pressure on the tech giant and other Silicon Valley companies about.

    “Everything from the beginning, from idea, silicon, all the way to the generation of intelligence will be here in the United States,” Huang said.

    When asked about his donation to the construction of Trump’s new White House ballroom, Huang said that he was “incredibly proud and delighted to help contribute in a small way to what will clearly be a historic national monument for our country.”

    Ironically though, Trump is now demolishing an actual historic American treasure, the East Wing of the White House, to make room for the ballroom.

    Even the fact that Nvidia decided to start organizing a second GTC in D.C. is testament to the company’s close ties to the President and his administration. Nvidia’s GTC conference is usually held once a year in March at the heart of Silicon Valley in San Jose, California. The event is considered the “Super Bowl” of AI, so Silicon Valley is an arguably more well-suited place for it to be held than the nation’s capital, and even Huang himself was aware of the incongruity.

    “This has got to be the most technical conference in Washington D.C.,” Huang said.

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  • Nvidia Bets the Future on a Robot Workforce

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    Nvidia is betting on an AI-driven robot workforce to shape the future of the country.

    “It is very likely that you might know robots, and my friend Elon is also working on this, [are] likely going to be one of the largest new consumer electronics markets, and surely one of the largest industrial equipment markets,” CEO Jensen Huang said at his keynote speech at Nvidia’s first-ever Washington D.C. edition of the GTC AI conference.

    Huang’s “friend” Elon Musk is working to build a “robot army” for Tesla, but one that he supposedly only feels comfortable to build if he is granted an unprecedented $1 trillion pay package in an upcoming vote next week. In an earnings call last week, Musk also made some bold claims about the potential of a robot workforce, claiming that Tesla’s Optimus robots could achieve “probably 5x the productivity of a person per year.”

    Nvidia executives see a robot workforce as a core part of America’s re-industrialization, something that has also been a part of the Trump administration‘s talking points. Nvidia’s vice president of Omniverse and simulation technology Rev Lebaredian thinks robots could account for over half a million open manufacturing jobs.

    “We have this standing problem pretty much in every country and in many different sectors and industries where there are jobs that are open but nobody wants to fill them, and they tend to be jobs that have one or more of the three D’s: dull, dirty, or dangerous jobs,” Lebaredian told Gizmodo. One example he gives is mining.

    When you combine that with a population that is gradually getting older, Lebaredian claims, “the only real solution” to continue global production at its current scale “is to shift some of that labor over to automation and robotics.”

    “We’re hard at work trying to build a good robot brain. Once we build a good robot brain, combined with the advancements we’re making in robot bodies that you’re seeing across the world, pretty soon, we’re going to have a  robotic workforce that could fill those job openings I was talking about,” Lebaredian said.

    That raises numerous questions on where humans would stand in this system ran by robots. The Nvidia executive thinks humans will still be involved in the managerial and creative level while those whose jobs get automated would be shifted over to new work.

    “Throughout human history, there’s always been this fear that if you increase the population, that you’re going to run out of jobs and there will be less work to go around. But we’ve always figured out how to create more work for ourselves,” he said.

    Nvidia made numerous partnership announcements on Tuesday to build out this vision.

    The tech giant says it will automate warehouses with Agility, while building hospital logistics and delivery robots with Diligent Robotics, surgical robots with Johnson & Johnson, and a large-scale, advanced humanoid robot fleet with Figure AI that is supposed to help with everything from industrial support to household chores.

    In this mission to scale the robot workforce, Nvidia also announced expansions to the Omniverse Blueprint, which helps companies train and test robot fleets with real-world simulations, via a technology called digital twins.

    “Largely, the AI we’ve been building for the past 10 years or so has been restricted to the knowledge world,” Lebaredian said, but with AI going into the physical world, the industry needs to give AI “a body, like a robot, a humanoid, or a self-driving car.” To do that, you need to train and test these robots, but doing so in real world settings is not feasible and often dangerous.

    Instead of risking real life testing debacles, Lebaredian says that digital twins can generate data to be fed into these robots’ AI brains. The simulations can also be a place to train and test robots safely, for example by having surgical robots conduct millions of hours of surgery in-simulation rather than in real life.

    Siemens is currently beta testing this technology to help engineers design and operate digital twins of factories, chief technology officer Peter Koerte told Gizmodo.

    Although AI chips are still Nvidia’s bread and butter, the tech giant’s big bet on robotics has been noticeably growing recently.

    In the company’s annual shareholder meeting earlier this year, Huang said that he expects robotics and AI to provide the largest growth for the company, and that the two represent a “multi-trillion-dollar growth opportunity.”

    Humanoid robots are advancing, but the technology (at least what the public has seen so far) is still showing significant limitations in its capabilities, as well as bottlenecks to widespread adoption like the intensive energy demand.

    First came ‘Agentic AI’

    According to Nvidia’s vice president of generative AI software for enterprise Kari Briski, physical AI is what comes after agentic AI.

    Although Nvidia is already looking ahead to the next stage, the jury is still out on whether agentic AI truly works or can work or will ever realize executive’s lofty productivity promises on a larger scale.

    Companies around the world are scaling AI in their operations but a viral report from MIT researchers found that fewer than one in ten AI pilot programs in the corporate world have generated real revenue gains. A group of researchers from BetterUp Labs and Stanford think the reason behind this is “workslop,” aka low-quality, AI-generated work documents. And in a high profile case earlier this year, Replit’s AI agent went rogue during a vibecoding session and wiped out the company’s codebase.

    Underlying all of this is also industry fears that improvements in AI capabilities are plateauing. Those fears were sparked after OpenAI’s highly anticipated GPT-5 announcement earlier this year was considered to largely be a letdown for fans. But the investments continue to flow, and AI companies are betting on a new leap to physical AI to reinvigorate any downturning sentiment in the industry.

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  • NVIDIA’s next move in autonomous driving is a partnership with Uber, Stellantis, Lucid and Mercedes-Benz

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    NVIDIA has entered a partnership with Uber to equip more of the rideshare company’s vehicles with its autonomous driving infrastructure. The deal centers on NVIDIA’s Drive AGX Hyperion 10 autonomous vehicle development platform, a computer and sensor system that can make any vehicle capable of level 4 self-driving, as well as its Drive software. According to the press release, this partnership will see Uber’s global fleet of autonomous vehicles growing to 100,000 vehicles over time, beginning in 2027.

    Several notable auto brands are also collaborating with NVIDIA on the push toward developing truly autonomous vehicles. Stellantis, Lucid and Mercedes-Benz are working on vehicles that would support NVIDIA’s L4 technology. Aurora, Volvo Autonomous Solutions and Waabi are pursuing work on implementing Drive AGX Hyperion 10 into long-haul freight vehicles.

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  • Qualcomm announces new AI chips in data center push, shares surge

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    By Harshita Mary Varghese

    (Reuters) -Qualcomm on Monday unveiled two artificial intelligence chips for data centers that will be available next year, diversifying beyond a stagnant smartphones market and sending its shares up 20%.

    The share gain following the news underscores strong enthusiasm for the company’s AI bets while the smartphone chipmaker geared up to compete against Nvidia‘s AI data center heft.

    The new chips, called AI200 and AI250, are designed for improved memory capacity and running AI applications, or inference, and will be commercially available in 2026 and 2027, respectively.

    Global investment in AI chips has soared as cloud providers, chipmakers and enterprises rush to build infrastructure capable of supporting complex, large language models, chatbots and other generative AI tools.

    Qualcomm said the new chips support common AI frameworks and tools and played up cost-savings for enterprises. The company also unveiled racks based on the new chips, as Nvidia and AMD move from selling chips to providing larger data center systems.

    Though competition against Nvidia has been heating up, the high costs of switching chip providers and superior performance of Nvidia processors has made it difficult for new entrants to gain traction.

    Qualcomm said Humain, an AI startup launched by Saudi Arabia’s sovereign wealth fund, will deploy 200 megawatts of its new AI racks starting in 2026.

    “Qualcomm’s entry and major deal in Saudi Arabia prove the ecosystem is fragmenting because no single company can meet the global, decentralized need for high-efficiency AI compute,” said Joe Tigay, portfolio manager of the Rational Equity Armor Fund.

    QUALCOMM DIVERSIFIES

    Qualcomm is the world’s largest supplier of modem chips that enable smartphones to connect to wireless data networks.

    But it has been diversifying its business to reduce dependence on the smartphone market, which makes up a majority of its sales after losing Huawei as a major customer and client Apple‘s efforts to develop in-house chips.

    Over the last two years, it has entered the personal computer market, competing against Intel and AMD to sell chips that power Windows-based laptops.

    (Reporting by Harshita Mary Varghese in Bengaluru; additional reporting by Arsheeya Bajwa; Editing by Vijay Kishore and Maju Samuel)

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  • Anthropic Strikes Major Compute Deal With Google, Echoing OpenAI’s Chip Alliances

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    Dario Amodei, a former OpenAI executive, founded Anthropic in 2021. Photo by Chance Yeh/Getty Images for HubSpot

    The latest sign of the A.I. industry’s unrelenting hunt for computing power comes from an expanded agreement between Anthropic and Google—a deal that, like several others struck in recent months, underscores the rise of circular arrangements across Silicon Valley. Under the new agreement, Google will provide Anthropic with well over one gigawatt of computing capacity by 2026, the companies announced yesterday (Oct. 23).

    Anthropic noted that the deal is worth “tens of billions of dollars” but didn’t provide an exact figure. The partnership further deepens the startup’s ties with Google, which has already invested about $3 billion in Anthropic and is expected to supply the company with up to 1 million of its custom A.I. chips, called tensor processing units (TPUs).

    Such partnerships are increasingly essential as leading A.I. startups scale at a breakneck pace. Anthropic, which now serves over 300,000 business customers, said the number of clients generating more than $100,000 in annual revenue has grown nearly sevenfold in the past year. “Anthropic and Google have a longstanding partnership, and this latest expansion will help us continue to grow the compute we need to define the frontier of A.I.,” said Krishna Rao, Anthropic’s chief financial officer, in a statement.

    Founded in 2021 by CEO Dario Amodei and several former OpenAI employees, Anthropic positioned itself as a safety-focused alternative to early A.I. players. Best known for its chatbot Claude, the company recently hit a $183 billion valuation and is reportedly on track to generate $9 billion in annual revenue.

    Despite its closer ties with Google, Anthropic emphasized that it remains committed to its “primary training partner,” Amazon, which has invested $8 billion in exchange for providing compute through its chips and A.I. cluster Project Rainier. The company also continues to rely on Nvidia’s GPUs as part of what it calls a “multi-platform approach.” Anthropic said it will keep investing in additional compute capacity as demand grows.

    Anthropic’s mutually beneficial partnerships with Google and Amazon reflect a broader trend: a broader industry trend: a growing web of interconnected A.I. partnerships between model developers and compute providers, each investing in and purchasing one another’s technology. OpenAI has been at the forefront of this shift, announcing a flurry of major deals in recent months, including an agreement with AMD to access six gigawatts of computing power, a deal with Nvidia to access 10 gigawatts of compute, and a $300 billion, five-year partnership with Oracle.

    The growing prevalence of such circular arrangements has raised some eyebrows in Silicon Valley, recalling the speculative interdependencies of the dot-com bubble and its eventual crash. But unlike that era, today’s A.I. spending is bolstered by stronger capitalization and clearer monetization potential, said Stephanie Aliaga, global market strategist for JPMorgan Chase, in a blog post earlier this month.

    Still, Aliaga cautioned that the concern isn’t misplaced. “The scale of spending is enormous, the pace unprecedented, and some assumptions around ROI, like the useful lives of assets, remain open questions,” she said. “History reminds us that enthusiasm can run ahead of reality,” she wrote.

    Anthropic Strikes Major Compute Deal With Google, Echoing OpenAI’s Chip Alliances

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  • With an Intel recovery underway, all eyes turn to its foundry business | TechCrunch

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    Intel’s third-quarter earnings beat Wall Street expectations Thursday, results buoyed by a bump in revenue combined with larger cuts, and multiple, sizable investments over the last two months as CEO Lip-Bu Tan looks to turn around the struggling semiconductor giant.

    Intel’s revenue results and its $4.1 billion in net income provides a far rosier view than its string of quarterly losses. But the company’s recovery story deserves several chapters dedicated to cost cutting via layoffs and other reductions as well as a series of high-profile investments from Softbank, Nvidia, and the U.S. government.

    Intel added $20 billion to its balance sheet during the third quarter, the company announced on its third-quarter earnings presentation on Thursday, sending its stock soaring. This growth was largely due to three sizable investments in the company over the last three months.

    In August, SoftBank invested $2 billion. A few days later, the U.S. Government took an unprecedented 10% equity stake in Intel. The company has received $5.7 billion of the planned $8.9 billion from the U.S. Government thus far. Nvidia also bought a $5 billion stake in Intel in September as part of a broader deal to develop chips together over time.

    “The actions we took to strengthen the balance sheet give us greater operational flexibility and position us well to continue to execute our strategy with confidence,” Tan said on the company’s earnings call. “In particular, I’m honored by the trust and confidence President Trump and Secretary [Howard] Lutnick have placed in me. Their support highlights Intel’s strategic role as the only U.S.-based semiconductor company with leading edge logic, [research and development] and manufacturing.”

    The company also received $5.2 billion from closing the sale of its ownership stake of Altera, a hardware company it had owned since 2015, on September 12. It also sold its stake in Mobileye, an autonomous driving tech company.

    Intel grew its quarterly revenue by $800 million in the third quarter to $13.7 billion, compared to $12.9 billion. Intel had net income of $4.1 billion in the third quarter, a steep reversal from the $16.6 billion loss it reported in the same year-ago period.

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    The foundry biz

    Despite the strong quarter, there weren’t many details on what will happen next with Intel’s foundry business, which makes custom chips for customers. The business has floundered from the start and has been a focus of Tan, who initiated significant layoffs in its foundry business this summer.

    The business appears to be a priority of the Trump administration; a key condition of the government’s investment in Intel includes language that it will penalize Intel if it divested from its foundry business over the next five years.

    Wall Street is keeping a close eye on foundry for signs of the company’s long-term growth. Intel analysts told TechCrunch in August that the company did not need cash to turn itself around but rather a strategy to get its foundry business on track.

    Tan said that Intel thinks its foundry business is “uniquely positioned” to capitalize on the swelling demand for chips but was light on the details — beyond saying that the company is actively engaging with potential foundry customers — and added that the growth of the foundry business would remain disciplined.

    “Building a world-class foundry is a long-term effort founded on trust,” Tan said. “As a foundry, we need to ensure that our process can be easily used by a variety of customers, each with their unique way of building their own products. We must learn to delight our customers as they count on us to build wafers, to meet all their needs for powerful performance, yield, cost, and schedule.”

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  • Apple, Trade Thaw Lift Stocks Toward New Highs

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    Easing trade tensions and a big gain in Apple shares helped drive stocks back toward records on Monday, the start of a heavy week of corporate earnings.

    Indexes opened with gains, with some investors saying sentiment was buoyed by President Trump saying he will soon meet with China’s leader, Xi Jinping, and Treasury Secretary Scott Bessent’s Friday comments that he will meet with his Chinese counterpart in person this week. 

    Copyright ©2025 Dow Jones & Company, Inc. All Rights Reserved. 87990cbe856818d5eddac44c7b1cdeb8

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  • NVIDIA shows off its first Blackwell wafer manufactured in the US

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    NVIDIA has taken a big step towards strengthening its domestic chip manufacturing, revealing the first Blackwell wafer made in the US. The hardware company assembled the wafer, which is the base material for NVIDIA’s AI chips, in TSMC’s semiconductor manufacturing facility in Phoenix, Arizona.

    NVIDIA revealed its Blackwell platform last year, boasting a goal of revolutionizing the AI industry through tech giants like Amazon, Google, OpenAI and others who already committed to adopting the next-gen architecture. NVIDIA said the latest platform was more powerful and translated to 25x less cost and energy consumption compared to its predecessor. Now that Blackwell wafers can be made at the TSMC plant, NVIDIA can better insulate itself from the ever-evolving tariff situation and geopolitical tensions.

    “It’s the very first time in recent American history that the single most important chip is being manufactured here in the United States by the most advanced fab, by TSMC, here in the United States,” Jensen Huang, NVIDIA’s founder and CEO, said at the celebration event.

    With NVIDIA’s Blackwell architecture ready for the volume production stage, the company is still working on expanding its manufacturing footprint across the US. Earlier this year, NVIDIA said it had plans to funnel half a trillion dollars towards building AI infrastructure in the US through partnerships with TSMC, Foxconn and other companies.

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