Latest news with #GPUs
The Verge
10 hours ago
- Business
- The Verge
Today I'm touring Micro Center, Silicon Valley's first big computer store in years.
Sean Hollister The SF Bay Area used to have a lot of PC stores. Most got wiped out! But Micro Center has returned to Santa Clara, CA, and it's a joy to browse. (Yes, the store reportedly sold dozens of GPUs that turned out to be backpacks; the company hasn't yet answered my questions.) BTW, you'll see a special gold GPU in this video, signed by Nvidia's CEO. It's now up for charity, with bidding at $8,600.
Associated Press
a day ago
- Business
- Associated Press
Aligned Data Centers Debuts Advanced Cooling Lab to Further Accelerate Cooling Technology Innovation for Next-Gen GPUs
DALLAS , June 04, 2025 (GLOBE NEWSWIRE) -- Aligned Data Centers, a leading technology infrastructure company offering innovative, sustainable and adaptive Scale Data Centers and Build-to-Scale solutions for global hyperscale, AI / HPC, and enterprise customers, announces the launch of its new Advanced Cooling Lab. The lab is dedicated to testing and innovating Aligned's flexible design and patented and patent-pending air and liquid cooling solutions to continue to master the thermal demands of the densest Graphics Processing Units (GPUs) and emerging AI accelerators. Aligned's Phoenix-based Advanced Cooling Lab serves as a vital hub for innovation, dedicated to promoting hybrid cooling environments and pushing the boundaries of data center infrastructure. It showcases Aligned's infrastructure solutions with the ability to handle the demanding needs of advanced compute systems. This responsiveness is directly enabled by the synergy of Aligned's patented and award-winning Delta Cube™ air-cooled system and patent-pending DeltaFlow~™ liquid-cooled system. By efficiently removing the intense heat from GPUs and AI accelerators, the system ensures customers have the instant capacity and performance needed for the most demanding AI and HPC workloads of today and tomorrow. 'Aligned has been innovating data center cooling for more than a decade,' says Michael Welch, Chief Technology Officer at Aligned Data Centers. 'The Advanced Cooling Lab is a testament to our commitment to delivering cutting-edge data center solutions and our passion for innovation. By investing in research and development, we can continue to provide our customers with the most flexible and advanced infrastructure available, capable of handling the dynamic demands of AI workloads.' Aligned's Advanced Cooling Lab features both Delta Cubes and DeltaFlows~ to create a true hybrid cooling environment. The lab also showcases the power of Aligned's Adaptive Modular Infrastructure (AMI), flexible design, and the synergy of its cooling systems. It illustrates the dynamic capability to transition from air-cooled to liquid-cooled systems in the same data hall as IT densities grow, ensuring future-proof asset and IT investments. Discover how Aligned is revolutionizing data center cooling and delivering the power and flexibility needed for today's high-performance computing: About Aligned Data Centers Aligned Data Centers is a leading technology infrastructure company offering innovative, sustainable, and adaptive Scale Data Centers and Build-to-Scale solutions for global hyperscale and enterprise customers. Our intelligent infrastructure allows densification and vertical growth within the same footprint, enabling customers to scale up without disruption, all while maintaining industry-leading Power Usage Effectiveness (PUE). By reducing the energy, water and space needed to operate, our data center solutions, combined with our patented cooling technology, offer businesses a competitive advantage by improving sustainability, reliability, and their bottom line. For more information, visit and connect with us on X, LinkedIn , Instagram and Facebook. Press and Analyst Inquiries Jennifer Handshew for Aligned Data Centers [email protected] +1 (917) 359-8838 A video accompanying this announcement is available at
Globe and Mail
a day ago
- Business
- Globe and Mail
Prediction: Nvidia's Rebound From the Correction Will Continue to Beat the Market
Nvidia (NASDAQ: NVDA) shares recovered nicely after the April market swoon. The stock is now just 10% off its all-time high, as of this writing. After a correction that bottomed on April 5, Nvidia shares have rocketed 48% higher. That compares to just a 27% rebound by the Nasdaq Composite since its early-April low. Some may believe that will mean Nvidia shares could level off while the overall index catches up as other high-growth tech companies also benefit from the surge in spending for artificial intelligence (AI) infrastructure. I'd argue that Nvidia will continue to outpace its peers, though, as the next phases of AI build-out and development will also lead to surging sales and profits for Nvidia. Nvidia's next big growth driver The first stage of the AI wave has been adding massive amounts of computing power to build and train models. Nvidia's sales exploded fourfold in its data center segment in just the last two years, materially by selling advanced graphics processing units (GPUs) needed for those powerful computer clusters. As the large language models (LLMs) built with that chip power multiply, another phase in the AI revolution is taking center stage. Nvidia CEO Jensen Huang called it out in the company's recent fiscal 2026 first-quarter report, released May 28. Huang said: Global demand for Nvidia's AI infrastructure is incredibly strong. AI inference token generation has surged tenfold in just one year, and as AI agents become mainstream, the demand for AI computing will accelerate. AI inference refers to the practical application of using LLMs in the real world. The abundance of LLMs now include OpenAI's ChatGPT and Anthropic's Claude, as well as many AI-powered search engines and chatbot platforms using multiple LLMs. Private and public enterprises are also running their own custom models tapping into LLMs. The inference tokens Huang refers to are units of data -- groups of text that the models read, process, and generate. That occurs after any question is answered, or an AI agent does a task. Tokens need a query or prompt when they are processed by GPUs. The volume of those queries is unsurprisingly growing and becoming more complex. The more complex the interaction, the more tokens it consumes. As with AI training, Nvidia is dominant in inference. AI factories are the next era of artificial intelligence Nvidia is now leading the global development of AI factories. That's a smart strategy that helps take advantage of the entire AI ecosystem by keeping it in-house as much as practical. AI factories are effectively highly advanced data centers. AI factories do more than just store and process data. They host the full life cycle of AI from data input, training, tweaking, and calibrating, to the voluminous amount of inference. The result gives enterprises the ability to enable prediction, generate content, and perform reasoning to seek solutions. Nvidia's products play roles in all of these functions. The company supplies software that optimizes its most advanced GPUs to lower per-token costs for customers. Nvidia offers an example where integrating software optimizations and adopting the latest-generation chips reduced costs by up to 20-fold versus older GPUs and processes. Customers can thus see more material returns on investment. The market is global for Nvidia. It is partnering with Saudi Arabia's state-owned AI company Humain to build AI factories that will utilize hundreds of thousands of Nvidia's most advanced GPUs as they are developed in the next several years. Nvidia is an investment for the future Nvidia realized a massive amount of success over the last several years as AI technology entered the mainstream with chatbots. Plans to build infrastructure blossomed, and Nvidia was the primary supplier able to support what was necessary to build and train models. More services are now being built around the LLMs, too. Nvidia has software stacks to support the models and supercomputers along with related services. Competition may rise around GPU supply, but Nvidia has many more products to continue growing revenue as AI expands across virtually every sector. Investors owning Nvidia stock now should have a solid chance of beating the market for years to come. Should you invest $1,000 in Nvidia right now? Before you buy stock in Nvidia, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Nvidia wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $657,385!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $842,015!* Now, it's worth noting Stock Advisor 's total average return is987% — a market-crushing outperformance compared to171%for the S&P 500. Don't miss out on the latest top 10 list, available when you join Stock Advisor. See the 10 stocks » *Stock Advisor returns as of June 2, 2025
Globe and Mail
2 days ago
- Business
- Globe and Mail
Better Artificial Intelligence Stock: Nvidia vs. AMD
Even with new export controls cutting off a vital market in China, demand for advanced chips used to power artificial intelligence (AI) infrastructure remains high. While there is a growing market for custom AI chips, the most commonly used chips for running AI workloads are graphics processing units (GPUs). This name stems from the fact that these chips were originally designed to speed up graphics rendering in video games. Due to their powerful processing speeds, GPUs are now used for a variety of high-power computing tasks, such as training large language models (LLMs) and running AI inference. The GPU market is basically a duopoly at this point, headed by Nvidia (NASDAQ: NVDA) and Advanced Micro Devices (NASDAQ: AMD). The question many investors ask, though, is: Which stock is the better buy? Where to invest $1,000 right now? Our analyst team just revealed what they believe are the 10 best stocks to buy right now. Learn More » The leader versus the challenger The unquestioned leader in the GPU space is Nvidia, which commands an over 80% market share. Not only is Nvidia larger than AMD, but it's also been growing its data center revenue more quickly. Last quarter, Nvidia grew its data center revenue by 73% to $39.1 billion, while AMD's data center revenue jumped 57% to $3.7 billion. Nvidia's advantage comes from its software platform, CUDA. It launched the free software platform all the way back in 2006 as a way to let developers program its GPUs for different tasks in an effort to expand beyond the video game market. The company pushed the use of the software to universities and research labs, which made it the software program upon which developers were taught to program GPUs. While AMD made some half-hearted efforts with software, it didn't launch a true CUDA competitor until around 10 years later with ROCm. By that time, CUDA had already become the default software used to program GPUs, and ROCm was still behind with less hardware support, limited documentation, and more difficulty to install and use. Meanwhile, Nvidia has since expanded upon its software lead through a collection of AI-specific libraries and tools built on top of CUDA, called CUDA X, which helps bolster the performance of its chips for AI tasks. Ultimately, CUDA has given Nvidia a big network effect advantage. The more CUDA is used, the more tools and libraries are built for it, making Nvidia GPUs all the stickier. While ROCm continues to improve, it still trails CUDA, especially for use in LLM training. However, where AMD has been able to gain more traction is in AI inference. Training AI models is a much more difficult task, which is why Nvidia has dominated this market and where its CUDA advantage really shines through. Inference, on the other hand, is easier, and there is more of a focus on things such as latency, power consumption, and cost. Due to its competitive positioning, AMD's GPUs tend to be less expensive than those from Nvidia, and while its ROCm software trails CUDA, it is generally considered good enough for running most AI inference workloads. The good thing for AMD is that the inference market is eventually expected to become the much larger of the two markets. In fact, some pundits, including venture capitalist and former Facebook executive Chamath Palihapitiya, have said the inference market could be up to 100 times larger than the market for training AI models. But whether the inference market becomes 2 times bigger or 100 times than the training market, AMD could have an opportunity to gain some market share. Which stock is the better buy? When it comes to valuation, both stocks trade in a similar range. Nvidia has a forward price-to-earnings (P/E) ratio of just over 32 times this year's analyst estimates, while AMD is at 28 times. Nvidia, meanwhile, is growing its revenue more quickly. With their valuations similar, the key factor to which stock will outperform in the coming years will largely come down to growth. Nvidia is the clear leader in the GPU space and should continue to see strong growth as the AI infrastructure buildout continues. However, its AI data center revenue is now 10 times that of AMD. so the law of large numbers can come into play. As AI infrastructure begins to shift more toward inference, AMD should have a nice opportunity to take some market share. Nvidia still has the lead in inference, but the gap is narrower compared to training. AMD also doesn't need to take a lot a of share in what could be a rapidly growing market to really make a big difference off its much smaller AI data center revenue base. As such, there is a good possibility it could begin to grow more quickly than the much bigger Nvidia. If that happens, I think its stock will outperform. Ultimately, investors can own both stocks, which is probably a good idea. With AI infrastructure spending still appearing to be in its early days, both should be winners, although I do think AMD has more potential upside. The biggest risk, meanwhile, would be if AI spending unexpectedly starts to slow. Should you invest $1,000 in Nvidia right now? Before you buy stock in Nvidia, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Nvidia wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $651,049!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $828,224!* Now, it's worth noting Stock Advisor 's total average return is979% — a market-crushing outperformance compared to171%for the S&P 500. Don't miss out on the latest top 10 list, available when you join Stock Advisor. See the 10 stocks » *Stock Advisor returns as of June 2, 2025 Geoffrey Seiler has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Advanced Micro Devices and Nvidia. The Motley Fool has a disclosure policy.
Globe and Mail
3 days ago
- Business
- Globe and Mail
Prediction: Nvidia Will Beat the Market. Here's Why
Nvidia (NASDAQ: NVDA), the world's largest producer of discrete graphics processing units (GPUs), saw its stock surge 25,250% over the past 10 years as the S&P 500 advanced less than 180%. From fiscal 2015 to fiscal 2025 (which ended this January), its revenue rose at a compound annual growth rate (CAGR) of 39% as its net income increased at a CAGR of 61%. That explosive growth was initially fueled by its brisk sales of gaming GPUs, which were also used to mine certain cryptocurrencies. But over the past few years, its expansion was primarily driven by its soaring shipments of data center GPUs for the artificial intelligence (AI) market. Unlike central processing units (CPUs), which process single pieces of data at a time, GPUs process a broad range of integers and floating numbers simultaneously. That advantage makes them better suited than stand-alone CPUs for processing complex AI tasks, so the rapid expansion of the AI market generated explosive tailwinds for its sales of data center GPUs. But since the start of 2025, Nvidia's stock rose less than 4% as the S&P 500 stayed nearly flat. The Trump administration's unpredictable tariffs, tighter curbs on exported chips, and the delays for its latest Blackwell chips all caused Nvidia to lose its luster. However, I believe Nvidia's stock can stay ahead of the S&P 500 this year for five simple reasons. 1. It still dominates the booming AI chip market Nvidia controlled 82% of the discrete GPU market at the end of 2024, according to JPR. Its closest competitor, AMD, held a 17% share, while Intel -- which returned to the discrete GPU market in 2022 -- controlled just 1% of the market. Nvidia also controls about 98% of the data center GPU market, according to TechInsights. The remaining 2% is split between AMD and Intel. Nvidia's dominance of that booming market, which is supported by the widespread usage of its older A100 chips and current-gen H100 and H200 chips, makes it tough for its competitors to gain a meaningful foothold. The global AI market could still expand at a CAGR of 31% from 2025 to 2032, according to Markets and Markets. If Nvidia merely matches that growth rate, its annual revenue would surge from $130.5 billion in fiscal 2025 to $1.31 trillion by fiscal 2032. So assuming it maintains roughly the same valuations, its stock still has a clear path toward delivering a ten-bagger gain over the next seven years. 2. Its ecosystem is sticky Nvidia reinforces its dominance through its proprietary Compute Unified Device Architecture (CUDA) programming platform. When software developers write their AI applications in a parallel code (such as C++ or Python) on CUDA, those applications become optimized for Nvidia's GPUs but can only be executed on its chips. If a developer wants to run that same application on an AMD or Intel GPU, it needs to be rewritten in other frameworks. In addition, most libraries, frameworks, and deep learning models are optimized for CUDA instead of other platforms. That stickiness should keep Nvidia well ahead of its competitors for the foreseeable future. 3. It can keep growing without China China accounted for just 12.5% of Nvidia's revenue in fiscal 2025, compared to 16.9% in fiscal 2024 and 21.5% in fiscal 2023. That decline was mainly caused by America's tighter export curbs on its high-end data center GPU shipments to China. Nvidia tried to counter those challenges by selling less powerful, modified versions of its flagship GPUs. However, those versions (like the scaled-back H20 variant of its H100 and H200 chips) were also recently added to the growing list of banned U.S. chip shipments to China. That sounds like grim news for Nvidia, but it can still easily offset its declining revenues in China with its growth in its other, less controversial markets. That's why its revenue grew at a CAGR of 120% from fiscal 2023 to fiscal 2025, even as the export curbs choked its Chinese business. 4. Its other smaller businesses are growing Nvidia generated 89% of its revenue from its data center chips in the first quarter of fiscal 2026. However, its smaller gaming, professional visualization, automotive, and OEM segments also grew year over year alongside its core growth engine. Its gaming business benefited from its rollout of its new RTX Super GPUs. Its professional visualization segment grew as it launched more design-oriented chips and expanded its Omniverse platform for digital projects, and its automotive chip sales improved as more Chinese automakers integrated its Drive platform into their electric vehicles. These oft-overlooked businesses should continue expanding in the shadow of its massive AI data center business. 5. It still looks reasonably valued From fiscal 2025 to fiscal 2028, analysts expect Nvidia's revenue and earnings per share to grow at CAGRs of 31% and 29%, respectively. Yet its stock still looks reasonably valued at 34 times this year's earnings. So once investors realize that its near-term issues won't affect its long-term growth, Nvidia's stock should outperform the market for the rest of the year. Should you invest $1,000 in Nvidia right now? Before you buy stock in Nvidia, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Nvidia wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $651,049!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $828,224!* Now, it's worth noting Stock Advisor 's total average return is979% — a market-crushing outperformance compared to171%for the S&P 500. Don't miss out on the latest top 10 list, available when you join Stock Advisor. See the 10 stocks » *Stock Advisor returns as of June 2, 2025
