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Business Insider
23-05-2025
- Business
- Business Insider
Nvidia Stock (NVDA) Maintains Bullish Tempo as Earnings Day of Reckoning Looms
Nvidia (NVDA), the trailblazing AI-tech stock, has staged a remarkable comeback, surging 33% over the past month. While investor concerns around rising competition, escalating global tariffs, and macroeconomic uncertainties have weighed on NVDA's performance, the company's underlying growth trajectory, driven by AI innovation and data center expansion, remains robust. Given this foundation, NVDA presents an attractive buying opportunity at current levels. Confident Investing Starts Here: Moreover, with a keenly anticipated earnings day looming next week, NVDA is on course to register yet another earnings surprise, which could push the stock beyond its all-time highs of ~$150 per share. Data Center Revenue Continues to Mushroom Despite intensifying competition within the AI sector, Nvidia maintains an overwhelming market share—estimated at over 80%—in AI-related data center GPUs. Its data center segment has experienced exponential growth, expanding from modest levels five years ago to a staggering $115 billion in revenue over the trailing 12 months. Nvidia's pioneering GPUs continue to dominate, while its latest Blackwell chips are rapidly gaining traction. Currently, data center revenues account for a significant 90% of total company revenue, indicating a high level of dependency. Nevertheless, this segment remains well-positioned for sustained growth, as major tech companies continue to invest heavily in AI infrastructure. According to Statista, global data center revenues are projected to reach US$450 billion in 2025, with network infrastructure contributing $250 billion. The market is expected to expand at an 8.4% CAGR, reaching $625 billion by 2029. As the undisputed leader in AI data center solutions, Nvidia stands to benefit enormously. Underscoring this outlook, Nvidia CEO Jensen Huang emphasized at the GTC Conference in March 2025 that data center spending has reached an 'inflection point.' He projected that annual capital expenditures in this domain could surpass $1 trillion by 2028, primarily driven by the demand for high-performance computing needed to power reasoning-based AI models. Despite fears that macro headwinds and trade policies could dampen capital investment from NVDA's major clients, companies like Amazon (AMZN), Microsoft (MSFT), and Alphabet (GOOGL) have shown no signs of slowing down. On the contrary, Meta Platforms (META) recently raised its capital expenditure guidance to $64–$72 billion, up from $60–$65 billion previously. Blackwell Ultra, Rubin AI & Other Innovative Platforms Nvidia continues to maintain its innovation momentum, regularly unveiling industry-leading technologies. The Blackwell architecture, launched in late 2024, has already garnered significant adoption. Investors will be closely watching NVDA's updates on future products, including the Blackwell Ultra slated for release in the second half of 2025, the Rubin AI platform expected in 2026, followed by the launch of Feynman processors, expected in 2028. There is already strong excitement building for Blackwell Ultra, as it is expected to deliver 50 times enhanced performance than the initial H100 chips. In addition, Nvidia's newly announced NVLink Fusion initiative will enable customers and partners to integrate non-Nvidia CPUs and GPUs alongside Nvidia products to build semi-custom AI infrastructure. This new tech will enable the speedy connection of multiple AI chips together. Another Earnings Beat Expected for NVDA Nvidia is set to report its Q1 2025 earnings on May 28. The company is projected to post earnings per share (EPS) of $0.89, a remarkable 46% year-over-year increase on revenue of approximately $43 billion, implying a robust 65% YoY growth rate. This would mark the company's 10th consecutive earnings beat. Investors will closely scrutinize the forward guidance, particularly for Q2, as it will offer critical insight into how ongoing macroeconomic dynamics may impact near-term results. NVDA's Consistent Revenues and Earnings Growth Looking at the last five years, NVDA's revenues have grown more than 10x from $11 billion in FY2020 to $131 billion in FY2025. What's even more applaudable is that its earnings have grown 25-fold from $2.8 billion to $72 billion over the same period, thanks to consistently expanding profit margins. Despite headwinds such as declining China revenues due to export restrictions, Nvidia has consistently added $4–5 billion in quarterly revenues, thanks to its growing global presence and strategic pivots. Gross margins now exceed 70%, even as the company ramps up capital spending to sustain its leadership in AI. This data gives me a tremendous sense of comfort in the solid business fundamentals and growth trajectory NVDA has consistently maintained over the years, driven by its AI prowess and continuous innovations, thereby retaining its industry leadership. While declining China revenues due to export restrictions are a concern, NVDA is making up for the lost revenues by diversifying geographically and tapping into new markets, with the Middle East turning out to be a great potential source of future revenues. NVDA recently entered into a 5-year meaningful partnership with Humain, an AI company backed by Saudi Arabia's Public Investment Fund. Other collaborations in the future can be a potential driver for incremental revenues. Rare Discount for a Quality Compounder For the first time in quite a while, Nvidia appears attractively valued ahead of its upcoming earnings call. The stock currently trades at a forward P/E of about 30x based on FY2026 estimates—roughly a 35% discount to its five-year average of 48x. Given Nvidia's track record of consistent outperformance and the significant upside tied to its Blackwell AI platform, this valuation presents a compelling entry point. Any short-term weakness in the stock may offer a timely opportunity for long-term investors. Is Nvidia a Buy, Sell, or Hold? On Wall Street, NVDA stock carries a Strong Buy consensus rating based on 34 Buy, five Hold, and one Sell ratings over the past three months. NVDA's average price target of $164.51 implies approximately 24% upside potential over the next twelve months. Nvidia Set to Flourish as Stock Indices Recover With stock markets now recovering from a topsy-turvy first five months of 2025, NVDA is precisely the kind of stock astute investors buy the dip on. That ship may have sailed, but it doesn't mean NVDA stock doesn't have more in the tank for new shareholders. Next week's earnings report could be a considerable price catalyst for NVDA — as long as it delivers what market analysts expect. Nvidia's first half of 2025 has been marked by turbulence, driven by trade policy uncertainty, macroeconomic pressures, and declining sales in China. Despite these headwinds, the stock's recent rebound highlights the company's resilience and sustained investor confidence. With its dominant position in AI, robust innovation pipeline, and strong financial track record, Nvidia appears undervalued at current levels. For long-term investors looking to capitalize on AI's transformative growth, NVDA presents a compelling investment opportunity.
Business Insider
07-05-2025
- Business
- Business Insider
AT&T's switch from ChatGPT to open-source AI helped it hang on to thousands of customers
AT&T gets 40 million customer service calls annually. Some callers want to add phone lines, register new addresses, or reschedule appointments, but many have problems to report. Those calls contain valuable information, but extracting it isn't easy. A person listening to each of them would get a good idea of what new issues are arising and could catch small problems before they grow into big ones. But with thousands of calls coming in each day, that would be an arduous, virtually impossible task. Transcription has been automated for a while, so AT&T used to do the sorting by hand. But employees had to read millions of summaries and put each call into one of 80 categories to be analyzed for any follow-up actions that could be taken. The ultimate goal is to prevent what consumer-oriented companies call "churn." Essentially, they want to keep the customers from leaving. Hien Lam, a senior data scientist at AT&T, explained the process during a presentation at Nvidia's GTC Conference in March. Now, with large language models, AI can ingest the summaries and categorize the calls. The ChatGPT way It was pretty simple. AT&T used ChatGPT to read and sort the summaries. It did a good enough job, but Lam's team saw problems coming down the road. "While the GPT-4 model did produce very high-quality outputs, and we were able to save 50,000 customers annually, it was very expensive," Lam said. Plus, customers of ChatGPT sometimes have to wait for the powerful and expensive chips to run AI systems, called graphics processing units, to become available. Sorting the calls was a daily task. "If it takes you longer than you can run overnight, then it's not a reasonable workflow," said Ryan Chesler, a principal data scientist at the open-source AI platform who worked with Lam on the project. So they set out to create a more flexible system that AT&T could have more control over, but that also cost less. The open-source way Lam teamed up with Chesler, working under the theory that if they could stitch together several open-source AI models with different "skills," they could achieve similar results with dramatically lower cost while keeping the company's data private. First, they distilled GPT-4 into three smaller, open-source models. The most basic model was smart enough to sort roughly a quarter of the categories. A call that mentioned a competitor's name, for example, was easy for a model to identify. A call with a nuanced story about a store team member required a more sophisticated model. About half the calls could be handled by an open-source model called Danube, a small but powerful model created by Lam worked with Chesler to fine-tune it to AT&T's needs. The most complex calls went to Meta's Llama 70B model, which is larger and more costly to run. Open-source models are inherently cheaper, but they're not free to run since they still require computing power. But by only using the larger models when necessary, the team kept costs down. In fact, the open-source patchwork solution cost 35% of what AT&T was paying to use ChatGPT, with 91% relative accuracy, Lam said. It was also faster. "Using GPT-4, it took 15 hours to process one day's worth of summaries. In our new solution, it took a little under five hours," Lam said. Next, they're looking to speed things up even more. "Because it takes 4½ hours for a full day, we are looking to do it real time after you hang up with AT&T," Lam said. "We could get those outputs immediately."
Yahoo
08-04-2025
- Business
- Yahoo
Nvidia And Google Bet Big On Quantum AI With $150M Investment In SandboxAQ, Raising Series E Round To $450 Million
Quantum computing may still feel like science fiction to most, but for a handful of major players, the future is unfolding much faster than expected. Nvidia (NASDAQ:NVDA) and Alphabet (NASDAQ:GOOGL, GOOG)) are the latest to double down on that future, pouring a $150 million investment into SandboxAQ, a startup blending quantum tech with artificial intelligence. That latest funding boost brings the company's Series E total to $450 million and pushes its valuation to $5.75 billion. According to Reuters, SandboxAQ has now raised $950 million, with support from giants like T. Rowe Price Associates (NASDAQ:TROW) and Breyer Capital, further solidifying its rise. Don't Miss: Hasbro, MGM, and Skechers trust this AI marketing firm — .Nvidia and Google's interest in quantum AI is a big step forward for the startup and the industry as a whole. At Nvidia's GTC Conference, CEO Jensen Huang broke down the speed at which quantum is developing, saying it is faster than almost everyone in the industry expected. A lot of quantum research thus far has been confined to academic circles, but we're starting to see momentum build around real-world applications, especially ones requiring massive computing power. SandboxAQ CEO Jack Hidary recently discussed the company's trajectory with Reuters. 'We've proven ourselves from the first round in terms of delivering on our promises to a number of customers, and I think strategic investors were attracted to those breakthroughs,' he said. Trending: Spun out of Alphabet in 2022, SandboxAQ has focused on developing large quantitative models that consume vast datasets, perform complex mathematical tasks, and conduct complicated statistical analyses. These models are already available via Google Cloud, and the applications reach far out to real-world computing. From speeding up drug discovery to changing how financial institutions model risk, LQMs provide a real-world advantage in areas where speed and accuracy equal billions of dollars. The deal for SandboxAQ isn't Google's only play in this area. In December, the tech giant announced a new class of quantum processors that overcame an obstacle for the field that had been standing for many years. Only a few months earlier, Google had participated in QuEra Computing's $230 million round, indicating that the strategy is for the company to support in-house research and development. Nvidia, on the other hand, is going down a more corporeal path. Best known for its chips that ignited the generative AI boom, the company has begun to invest heavily in what it calls 'physical AI,' which links data to the real world. That encompasses the establishment of its own quantum research division, suggesting a far longer game at is based in Palo Alto, California, and employs around 200 people in various roles to accelerate quantum capabilities into the mainstream. With its newest cash infusion, the company intends to intensify research and development while growing partnerships in crucial domains including biopharma, chemicals, and energy. SandboxAQ distinguishes itself with the strategic partnerships it has secured. Furthermore, the company's LQMs are designed to scale, fine-tune, and adapt, which is particularly appealing in industries where innovation cycles are accelerating and regulatory environments demand precision. Now, with the transition from quantum computing theory to application in full swing, SandboxAQ is emerging as one of only a handful of companies that can command a leadership position in this space. Google's and Nvidia's backing only shows how serious that ambition is, and how soon we might see quantum AI reshape everything we know, from medicine to finance. Read Next:Deloitte's fastest-growing software company partners with Amazon, Walmart & Target – Up Next: Transform your trading with Benzinga Edge's one-of-a-kind market trade ideas and tools. Click now to access unique insights that can set you ahead in today's competitive market. Get the latest stock analysis from Benzinga? APPLE (AAPL): Free Stock Analysis Report TESLA (TSLA): Free Stock Analysis Report This article Nvidia And Google Bet Big On Quantum AI With $150M Investment In SandboxAQ, Raising Series E Round To $450 Million originally appeared on © 2025 Benzinga does not provide investment advice. All rights reserved.
Yahoo
04-04-2025
- Business
- Yahoo
AI startup SandboxAQ adds Nvidia, Google as backers, raises additional $150 million
By Krystal Hu SandboxAQ, a startup drawing on quantum computing techniques to develop quantitative artificial intelligence models for enterprises, said it has raised $150 million from new investors including Google, Nvidia and BNP Paribas. The investment has increased SandboxAQ's Series E round to $450 million, valuing the startup at $5.75 billion. With this, SandboxAQ's total funding has reached $950 million, with T. Rowe Price Associates and Breyer Capital among backers. Participation of Google and Nvidia signals growing interest from technology giants to gain exposure in quantitative model development and place early bets on potential real-world applications. "We've proven ourselves from the first round in terms of delivering on our promises to a number of customers, and I think strategic investors were attracted to those breakthroughs," SandboxAQ CEO Jack Hidary told Reuters. SandboxAQ, a spin-off from Google-parent Alphabet in 2022, has designed Large Quantitative Models (LQMs) to handle extensive numerical datasets, perform complex calculations and conduct statistical analysis. Its models, available through first-party and third-party platforms such as Google Cloud, can potentially be used to assist drug discovery and develop sophisticated financial models. The company is based in Palo Alto and employs about 200 people. It plans to use the new funds to accelerate research and development and expand partnerships with enterprises in areas including biopharmaceuticals, chemicals and energy, Hidary said. Google and Nvidia have been increasing investment in-house and externally in quantum computing, which leverages the principles of quantum mechanics to perform computations beyond the capabilities of traditional computers. Nvidia, known for its chips that powered the generative AI boom, has recently placed emphasis on "physical AI." Nvidia CEO Jensen Huang dialed back skepticism regarding the timeline for practical quantum computing systems. At the chipmaker's "GTC Conference" last month, Huang said advancement in the field is progressing faster than anticipated as Nvidia set up its quantum research lab. Google's work in quantum computing drew attention in December when the firm announced a new generation of quantum chips, overcoming a major challenge in the field. In February, it participated in a $230 million funding round for QuEra Computing. Sign in to access your portfolio
Reuters
04-04-2025
- Business
- Reuters
AI startup SandboxAQ adds Nvidia, Google as backers, raises additional $150 million
April 4 - SandboxAQ, a startup drawing on quantum computing techniques to develop quantitative artificial intelligence models for enterprises, said it has raised $150 million from new investors including Google, Nvidia (NVDA.O), opens new tab and BNP Paribas ( opens new tab. The investment has increased SandboxAQ's Series E round to $450 million, valuing the startup at $5.75 billion. With this, SandboxAQ's total funding has reached $950 million, with T. Rowe Price Associates and Breyer Capital among backers. Participation of Google and Nvidia signals growing interest from technology giants to gain exposure in quantitative model development and place early bets on potential real-world applications. "We've proven ourselves from the first round in terms of delivering on our promises to a number of customers, and I think strategic investors were attracted to those breakthroughs," SandboxAQ CEO Jack Hidary told Reuters. SandboxAQ, a spin-off from Google-parent Alphabet (GOOGL.O), opens new tab in 2022, has designed Large Quantitative Models (LQMs) to handle extensive numerical datasets, perform complex calculations and conduct statistical analysis. Its models, available through first-party and third-party platforms such as Google Cloud, can potentially be used to assist drug discovery and develop sophisticated financial models. The company is based in Palo Alto and employs about 200 people. It plans to use the new funds to accelerate research and development and expand partnerships with enterprises in areas including biopharmaceuticals, chemicals and energy, Hidary said. Google and Nvidia have been increasing investment in-house and externally in quantum computing, which leverages the principles of quantum mechanics to perform computations beyond the capabilities of traditional computers. Nvidia, known for its chips that powered the generative AI boom, has recently placed emphasis on "physical AI." Nvidia CEO Jensen Huang dialed back skepticism regarding the timeline for practical quantum computing systems. At the chipmaker's "GTC Conference" last month, Huang said advancement in the field is progressing faster than anticipated as Nvidia set up its quantum research lab. Google's work in quantum computing drew attention in December when the firm announced a new generation of quantum chips, overcoming a major challenge in the field. In February, it participated in a $230 million funding round for QuEra Computing.
