Latest news with #JensenHuang
Time of India
an hour ago
- Business
- Time of India
Nvidia, Foxconn in talks to deploy humanoid robots at Houston AI server making plant
Live Events Taiwan's Foxconn and US artificial intelligence chips maker Nvidia are in talks to deploy humanoid robots at a new Foxconn factory in Houston that will produce Nvidia AI servers, two sources familiar with the matter would be the first time that an Nvidia product will be made with the assistance of humanoid robots and would be Foxconn's first AI server factory to use them on a production line, the sources said.A deployment, expected to be finalised in the coming months, would mark a milestone in the adoption of the human-like robots that promises to transform manufacturing is developing its own humanoid robots with Nvidia and has also trialed humanoids made by China's UBTech. The sources said it was not clear what type of humanoid robots are being planned for use in the Houston factory, what they will look like or how many will be deployed said the two companies are aiming to have the humanoid robots at work by the first quarter of next year when Foxconn's new Houston factory will begin production of Nvidia's GB300 AI while it was not clear what exactly the robots will be doing at the factory, Foxconn has been training them to pick and place objects, insert cables and do assembly work, according to a company presentation in Houston factory was ideally suited to deploy humanoid robots because it will be new and have more space than other existing AI server manufacturing sites, one of the sources and Foxconn declined to sources did not wish to be identified as they are not authorised to speak to the Guo, general manager of the robotics business unit at Foxconn Industrial Internet, a subsidiary of Foxconn that is in charge of the group's AI server business, said last month at an industry event in Taipei that Foxconn plans to showcase at the company's annual technology event in November two versions of humanoid robots that it has of those will be with legs and the other will use a wheeled autonomous mobile robot (AMR) base, which would cost less than the version with legs, he said, without disclosing announced in April that it planned to build AI supercomputer manufacturing factories in Texas, partnering with Foxconn in Houston and Wistron in Dallas. Both sites are expected to ramp up production within 12 to 15 Nvidia, using humanoid robots in the manufacturing of its AI servers represents a further push into the technology as it already supplies humanoid makers with a platform they can use to build such CEO Jensen Huang predicted in March that their wide use in manufacturing facilities was less than five years such as Germany's Mercedes-Benz and BMW have tested the use of humanoids on production lines, while Tesla is developing its own. China has also thrown its weight behind humanoids, betting that many factory tasks will eventually be performed by such robots.
Business Insider
6 hours ago
- Business
- Business Insider
‘Don't Bet the Farm,' Says Analyst About Quantum Computing Stock (QUBT)
Just months after suggesting that the widespread adoption of quantum computing was still '15 to 20 years away,' Nvidia CEO Jensen Huang offered a much more optimistic outlook, sparking a rally in speculative quantum stocks, such as Quantum Computing, Inc. (QUBT). The tech pioneer is up 8.5% so far this week, with bullish sentiment at its peak. Confident Investing Starts Here: However, a deeper look reveals significant concerns about QUBT's financial position. And while the industry is making progress, scaling quantum systems to tackle real-world problems remains a massive challenge, particularly for a company of QUBT's size. Despite the broader enthusiasm for 'lifting all boats' in the sector, I remain bearish on QUBT. The Nvidia Effect: A CEO's Shifting Narrative Being the CEO of a major tech company comes with significant influence—something Nvidia's Jensen Huang demonstrated at the GTC Paris developer conference when he declared that 'quantum computing is reaching an inflection point.' While his remarks centered on Nvidia's own innovations—like CUDA-Q, which aims to integrate quantum capabilities with classical systems—his optimism could have ripple effects across the sector. Nvidia backed its words with action in March 2025 by launching a new quantum computing research lab in Boston, reinforcing its leadership in the space. Huang's bullish tone may inspire increased venture capital and R&D investment across the quantum ecosystem. However, skepticism persists. Many still view practical quantum applications as decades away, with the industry struggling to define clear, real-world use cases that outperform traditional supercomputers. Without a breakthrough and tangible return on investment (ROI), quantum computing remains a tough sell to potential customers seeking immediate, measurable benefits. Quantum Computing's Niche Technology Quantum Computing Inc. specializes in photonic, or light-based, quantum solutions, developing Quantum Processing Units (QPUs) designed to operate at room temperature and low power, features that could make the technology more accessible and cost-effective. However, the company's focus remains on niche applications, such as remote sensing and computational chemistry, which limits its current market reach. While progress is being made in identifying use cases where quantum systems may outperform classical supercomputers, practical, scalable, and commercially viable applications are still emerging. The technology faces persistent challenges, including qubit fragility, high error rates, and scalability limitations. These machines are highly specialized and complex, suited for addressing targeted, advanced problems, but are not yet ready for broad commercial deployment. Financials Tell A Different Story Quantum Computing's first-quarter 2025 earnings highlight just how early-stage its business remains. The company reported revenue of only $39,000—roughly equivalent to the median U.S. individual income—while operating expenses climbed to $8.3 million. A $23.6 million non-cash gain from the mark-to-market revaluation of its warrant liability resulted in a reported net income of $17 million. However, this masks the company's ongoing operational losses. On the operational front, the company completed construction of its Quantum Photonic Chip Foundry. It announced new partnerships, including a contract with NASA's Langley Research Center—a sign of growing institutional interest despite modest commercial traction so far. QUBT's Speculative Valuation Quantum Computing's ~$3 billion market cap, despite minimal revenue, highlights an apparent disconnect from fundamentals and suggests the stock is driven largely by speculation. While the company holds $166 million in cash and cash equivalents, providing it with some runway to develop its technology, its R&D budget is modest compared to that of deep-pocketed rivals like IBM, Google, Microsoft, and Nvidia. Importantly, this cash position was built primarily through dilutive stock offerings and private placements, underscoring its heavy reliance on external funding. Given these constraints, it's difficult to envision a near-term path where Quantum Computing scales its niche technology into a broadly commercial product in a way that meaningfully rewards shareholders. Is QUBT Stock a Buy, Hold, or Sell? Reflecting its speculative nature, Quantum Computing's analyst coverage is limited. Its Moderate Buy consensus rating is based on one Buy recommendation in the past three months. Its average price target of $14.00 implies a downside potential of ~27% over the next 12 months. Meanwhile, TipRanks AI assigns QUBT a Neutral rating and a price target of $22. It notes that Quantum Computing's strong balance sheet and Qatalyst software positions it favorably amid hardware advances and increasing demand. However, it also points out that QUBT sports a high valuation, especially in light of ongoing losses and minimal revenues. QUBT Remains a High-Risk Bet in a Competitive Field While quantum computing as a whole may be approaching an 'inflection point,' the outlook for pure-play firms like Quantum Computing Inc. remains highly speculative. With minimal revenue, the company is still far from its own inflection point, where its products gain broad commercial viability. Reaching that stage will likely require scientific breakthroughs and significant R&D investment, which Quantum Computing may struggle to match relative to well-funded giants like IBM. That said, growing industry momentum is a clear tailwind. Rising interest in the sector could lead to increased funding, larger contracts, and a stronger push toward practical applications. Quantum Computing's unique focus on room-temperature, low-power photonic quantum systems, along with its early, albeit modest, commercial traction, may appeal to risk-tolerant, long-term investors. Personally, I remain highly cautious. The company's weak financial performance, lofty valuation, and limited ability to compete with larger players make its long-term investment case difficult to justify at this stage.
Yahoo
10 hours ago
- Business
- Yahoo
QUBT Rockets 3,144% on Quantum Hype, as Valuation Leaves No Room for Error
Quantum Computing Inc. (QUBT) has experienced extreme volatility, recently surging over 25% in a single week following a public endorsement from Nvidia CEO Jensen Huang, fueling a staggering 3,144% gain over the past year. Investor excitement around a potential inflection point in quantum computing is palpable, though whether that enthusiasm is grounded in near-term reality remains to be seen. Easily unpack a company's performance with TipRanks' new KPI Data for smart investment decisions Receive undervalued, market resilient stocks right to your inbox with TipRanks' Smart Value Newsletter While I'm bullish on the broader quantum technology narrative, QUBT's current valuation seems to price in near-flawless execution and rapid industry expansion—expectations that leave little room for error. The stock's sharp price swings may appeal to short-term traders and speculators, but as a long-term investor, I'm taking a wait-and-see Neutral approach, preferring to let the sector mature and the company's fundamentals catch up to its hype. QUBT is positioning itself as an emerging contender in the quantum technology space, with a focus on thin-film lithium niobate (TFLN) chips—a key component in photonic quantum computing, which could represent a major breakthrough in the field. The company recently completed its Photonic Chip Foundry in Tempe, Arizona, a strategic move designed to give it an edge in producing specialized chips for quantum applications. By targeting this niche early, QUBT aims to establish a leadership position before larger, better-funded competitors scale up similar capabilities. QUBT has also secured notable partnerships, including contracts with NASA, the Delft University of Technology, and a major automotive manufacturer, signaling growing interest in its technology, despite current revenues remaining modest. That said, the quantum computing race is still in its early stages. Success is far from guaranteed, especially as QUBT faces fierce competition from tech giants and deep-pocketed startups. While the company's strategy is compelling, the path to long-term dominance remains uncertain. Quantum Computing posted surprising numbers for the first quarter of 2025. The company reported a net income of $17 million, or $0.13 per share, representing a remarkable turnaround from the $6.4 million loss it posted in the same quarter last year. However, the impressive change in profit wasn't from selling more products or services. Instead, it came from a $23.6 million non-cash accounting gain related to the valuation of specific financial instruments. Strip away this one-time boost, and Quantum actually lost $8.3 million from operations, an increase from the $6.3 million operating loss they had the year before. The company's gross margins also took a hit, falling from 41% to 33%. Management has attributed this to growing pains that come with operating at such low revenue levels, but it remains a red flag worth watching. On the bright side, the company's financial position is solid. It reported a $166.4 million cash position (boosted by a recent $93.6 million investment), virtually no debt, and a strong balance sheet. This gives it plenty of runway to fund operations and growth initiatives without worrying about burning through its cash anytime soon. While overall market sentiment remains cautious, QUBT has emerged as a favorite among momentum traders and quantum computing enthusiasts. This has created a dynamic where the stock's movements are often fueled more by headlines and sector hype than by underlying business fundamentals. For instance, when Nvidia's CEO made favorable comments about quantum computing, QUBT surged 25% in a single day. However, the recent rally has pushed QUBT's valuation to over 4,500 times its annual revenue—a level that should give even the most bullish growth investor reason to pause. The real test will come when the next headline isn't so favorable. On Wall Street, QUBT stock carries a Moderate Buy consensus rating based on one buy rating provided by Ascendiant. The firm has set QUBT's stock price target at $14, implying approximately 30% downside potential over the next twelve months. QUBT's future success hinges on several factors largely outside its direct control. The quantum computing industry remains in its early stages, with widespread commercial adoption still years away. Key drivers—such as government funding, enterprise investment in advanced computing, and broader tech sector capital flows—will heavily influence whether companies like QUBT can thrive or falter. The stock is also susceptible to shifts in market sentiment. A turn toward prioritizing profitability over growth, or rising interest rates that dampen the appetite for speculative investments, could present serious challenges. Conversely, stronger government backing for quantum innovation, technological breakthroughs, or high-profile commercial partnerships could serve as powerful catalysts for QUBT's growth trajectory. Quantum Computing's strong financial position, traction with potential customers, and strategic positioning in a potentially transformative industry are attractive characteristics. Yet, the stock is priced for perfection, leaving little room for disappointment. While I am bullish on the potential opportunities of quantum computing, the recent run-up in QUBT's price has me inclined to wait for evidence of sustained revenue growth and a clear path to profitability before investing. 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Globe and Mail
16 hours ago
- Business
- Globe and Mail
The Week in AI: "All incumbents are gonna get nuked."
Welcome back to The Week in AI. I'm Kevin Cook, your field guide and storyteller for the fascinating arena of artificial intelligence. On Friday, my colleague Ethan Feller and I ran through a dozen developments that are transforming the economy right before our eyes. Here were 7 of the highlights... 1) Jensen at NVIDIA GTC Paris: "We are going to sell hundreds of billions worth of GB200/300." CEO Jensen Huang has forecast spending on AI-enabled data centers will double to $2 trillion over the next four to five years. As Grace Blackwell systems deploy, with 208 billion transistors per GPU -- or nearly 15 trillion per GB200 NVL72 rack system -- NVIDIA NVDA engineers are building the roadmap for Rubin and Feynman systems with likely orders of magnitude greater power. This is something I've talked about repeatedly for the past year: Wall Street analysts and investors are vastly underestimating the potential of the AI economy and the upgrades in infrastructure that need to occur to support self-driving cars, humanoid robots, and other autonomous machines. And this doesn't include sovereign nation-states that need to build their own AI infrastructure for security and growth. If you ever need clarity about the AI Revolution, or just to recalibrate your expectations and convictions, there is one place you need to visit: the NVIDIA Newsroom -- especially around a GPU Tech Conference (GTC). (I show you where in the video.) For last week's Paris GTC, they rolled out 6 press releases and 19 blogs covering as many new innovations and partnerships across industry, enterprise, science and healthcare. Nobody Wanted AI GPUs in 2016 Jensen also retells the story of the first DGX-1 in 2016. It was the mini supercomputer about the size of a college dorm fridge and it held 8 Volta GPUs with 21 billion transistors each. And nobody wanted it. Except a little startup called OpenAI. I like to use this story as an example of how NVIDIA has been in a very unique position ever since. They don't have to find "product-market fit" like most companies. Instead, they have been inventing a stack that developers didn't know they needed. Get the whole story in the replay of last Friday's The Week in AI: The Reasoning Wars, Sam's Love Letter, Zuck's Land Grab. Even if you don't have time for the 60-minute replay, at least do a quick scroll of the comments where I post all the relevant links to the topics we discussed. With over 25 links, you are guaranteed to find something that answers your top questions about the AI revolution! 2) The New Civil War In AI: Not Safety, But Efficacy There are many exciting debates going on in "the revolution" right now. A recent hot conflict is over whether or not the LLMs (large language models) are doing real reasoning, and even thinking. This one heated up after Apple AAPL researchers released their paper "The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models." We are amazed by the research, writing, pattern-finding and puzzle-solving of these models. But Apple researchers found some limitations where the models "give up" on large problems without enough context. And it's worth pondering if they are simply "token prediction" machines that eventually get wrapped around their own axles. I've experienced this with some of the "vibe-coding" app developer tools like Replit and Bolt. But then other analysts and papers quickly responded and surfaced with the "limitations" of the Apple research, suggesting that the imposed cost expenditure limits imposed were the defining factor in the models giving up. One of the rebuttal papers was titled "The Illusion of the Illusion of Thinking." Again, all these links are in the comments section of The Week in AI. 3) Google Offers Buyouts: AI Headcount Crunch Beginning? My third topic was once again about the employment impact from generative AI and agentic AI being adopted in corporations. I ran a query on ChatGPT for the "top 100 jobs most likely to be disrupted" in the next 3 years. You can find the link in the comments of the X Space. Another tangible angle on job displacement was the revolutionary ad during the NBA finals by the prediction market platform Kalshi. It was created using the new Veo 3 graphics creator from Google by a filmmaker named PJ Ace. Ethan and I discussed how this innovation is certain to disrupt advertising, marketing, and film as the machines can do in minutes what it used to take a team of people weeks. And wait until you see the new Veo 3 ad from a Los Angeles dentist that is taking social media by storm. We'll talk about that in this Friday's Space. Welcome to the Machine But the most eye-opening news flash for me was the story on a company called Mechanize. While lots of job displacement will happen organically, this outfit is like a mercenary going after headcount. The New York Times titled their article "This A.I. Company Wants to Take Your Job." And here's how an X post described the piece about the startup that wants to automate white-collar work "as fast as possible"... "Mechanize wants to abolish all jobs. They make no secret of this. They are developing an AI program that is extremely promising and is being financed by everyone from Google to Stripe." Then there is Anthropic co-founder Ben Mann saying we'll know AI is transformative when it passes the "Economic Turing Test: Give an AI agent a job for a month. Let the hiring manager choose: human or machine? When they pick the machine more often than not, we've crossed the threshold." I have several posts in the comments of the "The Week in AI" X Space on the employment wars. Plus, just about every post is from a particular source of AI insight or expertise whose account you should be following on X. 4) Marc Andreessen: "All incumbents are gonna get nuked. Everything gets rebuilt." Translation: AI isn't an economic upgrade. It's a total reset. Which brings me to my favorite part of our Friday X Space... Cooker's RANT of the WEEK: "The Magical AI Transformation Won't Be So Gentle." Here I take the other side of Sam Altman's blog post from last week titled "The Gentle Singularity." I call it his "love letter" not to make fun of him, but to highlight his optimism in the face of brewing storms. A few weeks ago it was Anthropic CEO Dario Amodei warning us about the rapid disruption of work and its impacts on citizens and families, not just the economy. Then the old wise-man of AI, Geoffrey Hinton, shared these sentiments in a recent interview... The best-case future is a "symbiosis between people and AI" -- where machines handle the mundane, and humans live more interesting lives. But in the kind of society we have now, he warns, AI won't free most people. It will concentrate power, and as massive productivity increases create joblessness, it will mostly benefit the rich. This sober view instantly made me think of the 2016 book by Yuval Noah Harari Homo Deus in which the historian described how technology usually gets concentrated in the hands of the rich and powerful. It's just how economics works, no matter the political flavor. In this way, AI can move quickly beyond issues of personal safety, to those of economic security. In the X Space replay and the comments below it, I discuss the implications of "post-labor economics" as well as share more expert resources on these topics. Be sure to catch the replay of The Week in AI to hear my sense of the "not-so-gentle" transition we are headed into. 5) Apple WWDC: The Non-Event of the Week in AI For what to expect (or not) from Apple in AI innovation, I always turn to Robert Scoble on X @Scobleizer. Here were some of his summary posts... Cynical take on Apple's WWDC: just doing things Microsoft did back in 2003. Liquid glass. Menus on tablets. Dark take on it: it's way behind in AI, and didn't demonstrate any attempt to catch up. Light take: Lots of new AI features, like your phone will wait on hold for you now. Hopeful take: the new design joins Apple Vision Pro into its ecosystem, showing that the Apple Vision Pro is the future of Apple. Scoble adds: I really hate the recorded product demos and the old people showing new features and attempting to be "hip." On a more Apple-positive note, Scoble is looking forward to the next devices which should be coming in the AR space... Later this year both Apple and Google are introducing heavyweight category wearables. Lighter than the first Vision Pro. We will judge them by who has the best AI inside. That is more important than resolution. Google, today, looks like it is way ahead and pulling further away because this is a game of exponents. I will buy both anyway. :-) (end of @Scobleizer rants) Many experts are sensing that Alphabet GOOGL is "firing on all cylinders across AI" as we've discussed previously. From Gemini 2.5 Pro and the astonishing new Veo 3 to building AI capabilities with their own with TPUs (instead of relying on NVIDIA GPUs), they're the only vertically-integrated player across all realms of tech. Google will probably also figure out the shift from classic search to generative search, as Daniel Newman of the Futurum technology research group says. Reports of Google's demise have been greatly exaggerated according to @DanielNewmanUV and I wish I was listening before I sold my shares on the last "search is dead" scare. 6) Zuck Splashes the Pot with $14.3 Billion Meta Platforms META plunked down that amount for only 49% of a private company called Scale AI. But the price tag made it the biggest pure-AI acquisition, following OpenAI's $6 billion purchase of Jony Ive's company. Just like Sam wasn't waiting around to find out what AI-native device Apple will build, so too Zuck isn't waiting around for permission to have access to the premier company in the data supply chain -- what some are calling the oil refinery of the AI economy. What does that mean? Well if you think about data as various grades of crude oil, it needs to be cleaned and prepped in a number of ways before it can be "mined and modeled" for quality results. That's where Scale AI comes in with data prep and labeling because major AI models need structured and labeled training data to generate knowledge tokens, insights, and deep learning. Scale AI is a San Francisco-based artificial intelligence company founded in 2016 by Alexandr Wang and Lucy Guo. The company specializes in providing high-quality data labeling, annotation, and model evaluation services that are essential for training advanced AI models, including large language models (LLMs) and generative AI systems. Scale AI is known for its robust data engine, which powers AI development for leading tech firms, government agencies, and startups worldwide. Its research division, the Safety, Evaluation and Alignment Lab (SEAL), focuses on evaluating and aligning AI models for safety and reliability 7) AMD Unveils AI Server Rack, Sam on Stage with Lisa I am still shaking my head at all the stuff that happened last week! As if all of the above wasn't enough, Advanced Micro Devices AMD held its annual Advancing AI conference last Thursday with a product roadmap for hyperscale inferencing that caught investor attention. In addition to leaps forward in performance for the existing Instinct MI350 Series GPU systems, AMD CEO Lisa Su unveiled the Helios AI Rack-scale architecture supporting up to 72 MI400 GPUs, with 432GB of HBM4 memory per GPU and 19.6 TB/sec bandwidth. Available in 2026, this is clearly an answer to NVIDIA's GB200/300 series rack systems. AI Market Growth: CEO Lisa Su projected an 80% increase in AI inference demand by 2026, driven by the rapid adoption and expansion of AI applications in enterprise and cloud environments. Roadmap: AMD reaffirmed its commitment to an annual cadence of AI chip releases, with the MI400 and MI450 series already in development and expected to challenge Nvidia's flagship offerings in 2026 and beyond. And then Sam Altman showed up during Lisa's keynote. Since he clearly can't get enough compute or GPUs, he's as tight with Lisa as he is with Jensen. Lisa welcomed the founder and CEO of OpenAI as a key design partner for AMD's upcoming MI450 GPU who will help shape the next generation of AMD's AI hardware. OpenAI will use AMD GPUs and Helios servers for advanced AI workloads, including ChatGPT. And AMD's other happy customers continue to come back for more with Meta deploying AMD Instinct MI300X GPUs for Llama 3/4 inference and collaborating on future MI350/MI400 platforms. Meanwhile Microsoft Azure runs proprietary and open-source models on AMD Instinct MI300X GPUs in production and Oracle Cloud Infrastructure will deploy zettascale AI clusters with up to 131,072 MI355X GPUs, offering massive AI compute capacity to customers. This event made AMD shares a clear buy last week -- and this week if you can still grab some under $130! OLD RANT: The Fundamental Difference Finally, did you hear what another OpenAI co-founder said at the University of Toronto commencement address? Ilya Sutskever, the OpenAI architect and deep learning pioneer who in 2024 started his own model firm, Safe Superintelligence, spoke these words to the new grads... "The day will come when AI will do all the things we can do. The reason is the brain is a biological computer, so why can't the digital computer do the same things? "It's funny that we are debating if AI can truly think or give the illusion of thinking, as if our biological brain is superior or fundamentally different from a digital brain." I had to dig out my old rant about the fundamental difference(s) between human brains and computer "thinking." If you haven't heard me on this, you owe it to yourself so you can easily explain the differences to other "intelligence experts" telling you how consciousness works. Bottom line: To stay informed in AI, listen to The Week in AI replay, or just go to that post to see all the links and sources. And be sure to follow me on X @KevinBCook so you see the announcement for the new live Space every Friday. Only $1 to See All Zacks' Buys and Sells We're not kidding. Several years ago, we shocked our members by offering them 30-day access to all our picks for the total sum of only $1. No obligation to spend another cent. Thousands have taken advantage of this opportunity. Thousands did not - they thought there must be a catch. Yes, we do have a reason. We want you to get acquainted with our portfolio services like Surprise Trader, Stocks Under $10, Technology Innovators, and more, that closed 256 positions with double- and triple-digit gains in 2024 alone. See Stocks Now >> Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free report Apple Inc. (AAPL): Free Stock Analysis Report Advanced Micro Devices, Inc. (AMD): Free Stock Analysis Report NVIDIA Corporation (NVDA): Free Stock Analysis Report Alphabet Inc. (GOOGL): Free Stock Analysis Report Meta Platforms, Inc. (META): Free Stock Analysis Report
Yahoo
17 hours ago
- Business
- Yahoo
NVDA: Oppenheimer Sees Trillion-Dollar AI Opportunity for Nvidia
June 19 - Nvidia (NASDAQ:NVDA) could benefit from rising global interest in sovereign artificial intelligence systems, according to a recent client note from Oppenheimer, following CEO Jensen Huang's high-profile tour across Europe. Warning! GuruFocus has detected 4 Warning Signs with NVDA. The firm said Nvidia is working closely with governments to help them build national AI infrastructure. Oppenheimer estimates the total addressable market for sovereign AI could reach $1.5 trillion, with Europe accounting for about $120 billion of that potential. Last week, Nvidia entered a new partnership with Deutsche Telekom to support Germany's push into sovereign AI. The deal aims to accelerate industrial use cases including robotics, simulation, and digital twins. Huang also announced a collaboration with the European Broadcasting Union during a keynote at the VivaTech conference in Paris. He later visited London for further engagements at London Tech Week, as Nvidia expands its sovereign AI strategy across key European markets. Shares of Nvidia have climbed around one-third since late April, as investors weigh the potential of sovereign AI alongside other growth drivers in its enterprise and data center businesses. This article first appeared on GuruFocus. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
