Latest news with #MI300X
Economic Times
5 days ago
- Business
- Economic Times
Intel facing a BlackBerry moment as thousands laid off - CEO says too late to catch up with AI as firm falls out of global top 10
Synopsis Intel CEO Lip-Bu Tan made a shocking admission, saying it's now 'too late' for Intel to catch up in the AI race, as the company falls out of the top 10 semiconductor companies. Once a leader in chipmaking, Intel now faces massive layoffs, a $16 billion loss, and increasing reliance on TSMC for chip production. The company has lost ground to rivals like Nvidia, AMD, and Apple, especially in AI and data centers. With a renewed focus on edge AI and agentic systems, Tan promises change, but Intel's future remains uncertain. Read how the tech giant plans to reinvent itself. Reuters Intel CEO Lip-Bu Tan says it's too late to catch up with Nvidia in AI, as Intel drops out of the top 10 semiconductor companies and faces global layoffs, heavy losses, and a complete shift toward edge AI and chip outsourcing. Intel CEO admits it's 'too late' to catch up in AI race as chip giant slips out of top 10 semiconductor firms- Intel, once the undisputed leader of the semiconductor world, now finds itself at a critical crossroads. In a leaked internal discussion, Intel CEO Lip-Bu Tan made a brutally honest admission—he believes it's already 'too late' for Intel to catch up in the AI competition. The statement, shared during a global employee Q&A, reveals just how far the tech giant has fallen, even slipping out of the top 10 semiconductor companies by Tan's own words. This sharp self-assessment highlights the company's struggle to stay relevant amid fierce competition from AMD, Nvidia, Apple, TSMC, and Samsung. While Intel still holds legacy clout, that alone may not be enough to power through the rapidly evolving AI era. And with layoffs underway and massive losses stacking up, the pressure to turn things around has never been greater. Despite having the resources and infrastructure once deemed untouchable, Intel has fallen behind in the AI hardware race. Lip-Bu Tan's comment—"On training, I think it is too late for us"—makes it clear that Nvidia's runaway success in data center GPUs has created a gap that may now be impossible to close. AI development today heavily depends on powerful training hardware, most of which runs on Nvidia's CUDA-based ecosystem. While Intel tried to enter this space with its Habana Labs acquisition and Gaudi AI chips, it never gained the market traction needed to compete with Nvidia's H100s or AMD's MI300X chips. The rise of large language models like OpenAI's ChatGPT only widened the gap, further cementing Nvidia's lead. Instead of pushing further in data center AI, Intel plans to pivot towards edge AI, focusing on bringing artificial intelligence to personal devices like laptops, desktops, and embedded systems—where it still sees growth potential. In what's perhaps the most jarring part of Tan's talk, he reportedly said: 'Twenty, 30 years ago, we were really the leader. Now I think the world has changed. We are not in the top 10 semiconductor companies.' This admission shocked many across the tech industry. While Intel is still a recognized name globally, competitors like TSMC, Nvidia, Samsung, Apple, and AMD have outpaced it in terms of innovation, revenue, and market relevance. Even relatively smaller firms like Broadcom, MediaTek, Micron, and SK Hynix are making waves in specialized markets. According to recent financial data, Intel reported a $16 billion loss in Q3 of 2024, and it's struggling to reverse the trend. The company that once nearly acquired Nvidia for $20 billion is now watching from the sidelines as Nvidia crosses a staggering $4 trillion market cap. Intel's decision to exit the AI training chip space comes as the AI chip market explodes in value. Key stats: Global AI chip market was worth $23.2 billion in 2023 Projected to reach $117.5 billion by 2029 at a CAGR of ~31% Nvidia holds an estimated 90% share in AI training chips Meanwhile, AMD is quickly gaining ground with its MI300 series, and TSMC is dominating as the primary chip manufacturer for Nvidia, Apple, and AMD. While conceding the AI training space, Intel is attempting a pivot: Investing $20 billion in a new Ohio AI chip plant Backed by the CHIPS Act, receiving billions in grants Eligible for a 35% tax credit on investment in U.S. fabs This move aims to revitalize Intel's role as a domestic foundry powerhouse, producing edge and agentic AI chips rather than competing directly with Nvidia's data center dominance. Company AI Focus Area Market Position Key Advantage Nvidia AI training & inference ~90% market share Dominant CUDA software ecosystem, H100/Blackwell chips AMD Data center AI GPUs Rising rapidly Competitive MI300X chips with increasing adoption TSMC Manufacturing/foundry Backbone of AI industry Manufactures chips for Nvidia, AMD, Apple Intel Edge AI (future focus) Minor AI share Investing in U.S. fabs, but far behind in AI chips Intel's once-vibrant CPU leadership has failed to translate into GPU or AI-specific success. Analysts note that even if Intel builds capacity, it lacks the software stack, developer loyalty, and ecosystem that power Nvidia's moat. Intel now hopes to find success in: Edge AI: Chips powering autonomous devices, cars, and smart sensors Agentic AI: AI chips focused on decision-making in real-time systems Foundry services: Becoming a U.S.-based manufacturer for others, not just itself However, these bets are long-term, with profitability and success far from guaranteed. A big part of Intel's decline can be traced to delays in its own chipmaking technology. While AMD partnered with TSMC to produce cutting-edge 5nm and 3nm chips, Intel stuck with its internal foundries. Unfortunately, those fabs fell behind schedule. Intel's own hybrid architecture, similar to ARM's design, didn't take off the way it had hoped. Its Arrow Lake and Meteor Lake CPUs failed to gain significant ground on AMD's Ryzen and EPYC series, especially in high-performance computing. AMD now powers everything from handhelds like the Steam Deck and Rog Ally X, to gaming consoles like the PlayStation 5 and Xbox Series X/S. Meanwhile, Intel's attempts at entering the discrete GPU market with its Arc lineup were too little, too late. The GPUs suffered from driver issues, performance gaps, and poor market timing. By the time Intel showed up, Nvidia and AMD had already cornered the market. There's growing speculation that Intel may split into two entities—one focused on designing chips (like AMD and Apple) and the other running its foundry operations as a separate business. While nothing has been confirmed officially, the strategy could relieve some pressure and allow Intel to act more flexibly. As of 2025, Intel already outsources about 30% of its chip production to TSMC, a move that would have been unthinkable years ago. TSMC is now producing major parts of Intel's upcoming Lunar Lake and Meteor Lake chips, including the GPU and compute tiles. Intel's long-delayed 18A node—the supposed game-changer—isn't expected to be ready until late 2026. This shift to a fabless model, or something close to it, could be Intel's path to survival. Both AMD and Apple have succeeded by focusing entirely on chip design and leaving manufacturing to TSMC. Nvidia has always followed this model, too. To cut costs, Intel has been laying off thousands of employees globally. These layoffs come as part of a larger cost-cutting initiative after heavy R&D spending and failed product launches. According to OregonTech, the company is in "a fight for survival." CEO Lip-Bu Tan, who replaced former chief Pat Gelsinger in late 2024, has signaled a major cultural reset. He emphasized that Intel's comeback would be a 'marathon', not a sprint. The new approach? Fewer distractions and a laser-sharp focus on areas where Intel can still compete—namely edge AI, low-power computing, and eventually reclaiming performance leadership in CPU markets. Tan is also betting big on agentic AI, a fast-growing field where AI systems can operate independently without constant human input. He teased that more executive-level hires are coming to help accelerate the transformation, saying, 'Stay tuned. A few more people are coming on board.' The honest reality is, Intel has already missed the first AI wave. Nvidia owns the training market. AMD is now winning in data centers. TSMC continues to dominate manufacturing. Even Apple's M-series chips are setting new standards in efficiency and performance. Still, Intel isn't dead. It's wounded—yes—but not out. With the right leadership, sharper product focus, and a little humility, the company could still stage a comeback. The road ahead won't be easy, and it won't be fast. But if there's one thing we've seen from tech turnarounds, it's that big brands can rise again—if they're willing to let go of the past. Intel's survival now depends on its ability to adapt—not just to AI, but to a world where speed, specialization, and scale matter more than legacy. The next 18 months will likely determine whether the company can climb back into relevance, or fade deeper into the background. Intel CEO Lip-Bu Tan admits it's "too late" for Intel to catch up in AI training. The company reportedly no longer ranks among the top 10 global semiconductor firms. Intel posted a $16 billion loss in Q3 2024 and is laying off thousands worldwide. The company now outsources 30% of chip production to TSMC. Intel's future focus includes edge AI, agentic AI, and potentially a fabless business model. Q1: Why did Intel CEO say it's too late for AI? Intel CEO Lip-Bu Tan said Intel missed the AI training wave led by Nvidia and can't catch up now. Q2: Is Intel still a top semiconductor company? No, according to Tan, Intel is no longer among the top 10 semiconductor firms globally.
Time of India
5 days ago
- Business
- Time of India
Intel facing a BlackBerry moment as thousands laid off - CEO says too late to catch up with AI as firm falls out of global top 10
Intel CEO Lip-Bu Tan made a shocking admission, saying it's now 'too late' for Intel to catch up in the AI race, as the company falls out of the top 10 semiconductor companies. Once a leader in chipmaking, Intel now faces massive layoffs, a $16 billion loss, and increasing reliance on TSMC for chip production. The company has lost ground to rivals like Nvidia, AMD, and Apple, especially in AI and data centers. With a renewed focus on edge AI and agentic systems, Tan promises change, but Intel's future remains uncertain. Read how the tech giant plans to reinvent itself. Intel CEO Lip-Bu Tan says it's too late to catch up with Nvidia in AI, as Intel drops out of the top 10 semiconductor companies and faces global layoffs, heavy losses, and a complete shift toward edge AI and chip outsourcing. Tired of too many ads? Remove Ads Why is Intel struggling to keep up in the AI chip race? Tired of too many ads? Remove Ads Has Intel really fallen out of the top 10 semiconductor companies? AI chip market: Intel left behind Global AI chip market was worth $23.2 billion in 2023 Projected to reach $117.5 billion by 2029 at a CAGR of ~31% Nvidia holds an estimated 90% share in AI training chips Intel's $20 billion bet on U.S. chipmaking Investing $20 billion in a new Ohio AI chip plant Backed by the CHIPS Act, receiving billions in grants Eligible for a 35% tax credit on investment in U.S. fabs Market share comparison: Who leads the AI chip race? Company AI Focus Area Market Position Key Advantage Nvidia AI training & inference ~90% market share Dominant CUDA software ecosystem, H100/Blackwell chips AMD Data center AI GPUs Rising rapidly Competitive MI300X chips with increasing adoption TSMC Manufacturing/foundry Backbone of AI industry Manufactures chips for Nvidia, AMD, Apple Intel Edge AI (future focus) Minor AI share Investing in U.S. fabs, but far behind in AI chips Tired of too many ads? Remove Ads Strategic pivot or final chapter? Edge AI: Chips powering autonomous devices, cars, and smart sensors Agentic AI: AI chips focused on decision-making in real-time systems Foundry services: Becoming a U.S.-based manufacturer for others, not just itself Why did Intel lose its lead in CPU and GPU innovation? Is Intel going to split its business or become fabless? What's next for Intel as it lays off thousands and refocuses? Can Intel find a second act, or is this the beginning of the end? Intel CEO Lip-Bu Tan admits it's "too late" for Intel to catch up in AI training. The company reportedly no longer ranks among the top 10 global semiconductor firms. Intel posted a $16 billion loss in Q3 2024 and is laying off thousands worldwide. The company now outsources 30% of chip production to TSMC. Intel's future focus includes edge AI, agentic AI, and potentially a fabless business model. FAQs: Intel, once the undisputed leader of the semiconductor world, now finds itself at a critical crossroads. In a leaked internal discussion, Intel CEO Lip-Bu Tan made a brutally honest admission—he believes it's already 'too late' for Intel to catch up in the AI competition. The statement, shared during a global employee Q&A, reveals just how far the tech giant has fallen, even slipping out of the top 10 semiconductor companies by Tan's own sharp self-assessment highlights the company's struggle to stay relevant amid fierce competition from AMD, Nvidia, Apple, TSMC, and Samsung. While Intel still holds legacy clout, that alone may not be enough to power through the rapidly evolving AI era. And with layoffs underway and massive losses stacking up, the pressure to turn things around has never been having the resources and infrastructure once deemed untouchable, Intel has fallen behind in the AI hardware race. Lip-Bu Tan's comment—"On training, I think it is too late for us"—makes it clear that Nvidia's runaway success in data center GPUs has created a gap that may now be impossible to development today heavily depends on powerful training hardware, most of which runs on Nvidia's CUDA-based ecosystem. While Intel tried to enter this space with its Habana Labs acquisition and Gaudi AI chips, it never gained the market traction needed to compete with Nvidia's H100s or AMD's MI300X chips. The rise of large language models like OpenAI's ChatGPT only widened the gap, further cementing Nvidia's of pushing further in data center AI, Intel plans to pivot towards edge AI, focusing on bringing artificial intelligence to personal devices like laptops, desktops, and embedded systems—where it still sees growth what's perhaps the most jarring part of Tan's talk, he reportedly said: 'Twenty, 30 years ago, we were really the leader. Now I think the world has changed. We are not in the top 10 semiconductor companies.'This admission shocked many across the tech industry. While Intel is still a recognized name globally, competitors like TSMC, Nvidia, Samsung, Apple, and AMD have outpaced it in terms of innovation, revenue, and market relevance. Even relatively smaller firms like Broadcom, MediaTek, Micron, and SK Hynix are making waves in specialized to recent financial data, Intel reported a $16 billion loss in Q3 of 2024, and it's struggling to reverse the trend. The company that once nearly acquired Nvidia for $20 billion is now watching from the sidelines as Nvidia crosses a staggering $4 trillion market decision to exit the AI training chip space comes as the AI chip market explodes in value. Key stats:Meanwhile, AMD is quickly gaining ground with its MI300 series, and TSMC is dominating as the primary chip manufacturer for Nvidia, Apple, and conceding the AI training space, Intel is attempting a pivot:This move aims to revitalize Intel's role as a domestic foundry powerhouse, producing edge and agentic AI chips rather than competing directly with Nvidia's data center once-vibrant CPU leadership has failed to translate into GPU or AI-specific success. Analysts note that even if Intel builds capacity, it lacks the software stack, developer loyalty, and ecosystem that power Nvidia's now hopes to find success in:However, these bets are long-term, with profitability and success far from guaranteed.A big part of Intel's decline can be traced to delays in its own chipmaking technology. While AMD partnered with TSMC to produce cutting-edge 5nm and 3nm chips, Intel stuck with its internal foundries. Unfortunately, those fabs fell behind own hybrid architecture, similar to ARM's design, didn't take off the way it had hoped. Its Arrow Lake and Meteor Lake CPUs failed to gain significant ground on AMD's Ryzen and EPYC series, especially in high-performance computing. AMD now powers everything from handhelds like the Steam Deck and Rog Ally X, to gaming consoles like the PlayStation 5 and Xbox Series X/ Intel's attempts at entering the discrete GPU market with its Arc lineup were too little, too late. The GPUs suffered from driver issues, performance gaps, and poor market timing. By the time Intel showed up, Nvidia and AMD had already cornered the growing speculation that Intel may split into two entities—one focused on designing chips (like AMD and Apple) and the other running its foundry operations as a separate business. While nothing has been confirmed officially, the strategy could relieve some pressure and allow Intel to act more of 2025, Intel already outsources about 30% of its chip production to TSMC, a move that would have been unthinkable years ago. TSMC is now producing major parts of Intel's upcoming Lunar Lake and Meteor Lake chips, including the GPU and compute tiles. Intel's long-delayed 18A node—the supposed game-changer—isn't expected to be ready until late shift to a fabless model, or something close to it, could be Intel's path to survival. Both AMD and Apple have succeeded by focusing entirely on chip design and leaving manufacturing to TSMC. Nvidia has always followed this model, cut costs, Intel has been laying off thousands of employees globally. These layoffs come as part of a larger cost-cutting initiative after heavy R&D spending and failed product launches. According to OregonTech, the company is in "a fight for survival."CEO Lip-Bu Tan, who replaced former chief Pat Gelsinger in late 2024, has signaled a major cultural reset. He emphasized that Intel's comeback would be a 'marathon', not a sprint. The new approach? Fewer distractions and a laser-sharp focus on areas where Intel can still compete—namely edge AI, low-power computing, and eventually reclaiming performance leadership in CPU is also betting big on agentic AI, a fast-growing field where AI systems can operate independently without constant human input. He teased that more executive-level hires are coming to help accelerate the transformation, saying, 'Stay tuned. A few more people are coming on board.'The honest reality is, Intel has already missed the first AI wave. Nvidia owns the training market. AMD is now winning in data centers. TSMC continues to dominate manufacturing. Even Apple's M-series chips are setting new standards in efficiency and Intel isn't dead. It's wounded—yes—but not out. With the right leadership, sharper product focus, and a little humility, the company could still stage a comeback. The road ahead won't be easy, and it won't be fast. But if there's one thing we've seen from tech turnarounds, it's that big brands can rise again—if they're willing to let go of the survival now depends on its ability to adapt—not just to AI, but to a world where speed, specialization, and scale matter more than legacy. The next 18 months will likely determine whether the company can climb back into relevance, or fade deeper into the CEO Lip-Bu Tan said Intel missed the AI training wave led by Nvidia and can't catch up according to Tan, Intel is no longer among the top 10 semiconductor firms globally.
Time of India
5 days ago
- Business
- Time of India
AMD stock soars as HSBC predicts $200 target — Is Nvidia's AI crown in jeopardy?
AMD stock price jumps over 4% as HSBC raises target to $200—are AI chips finally putting real pressure on NVIDIA?- AMD stock price surged more than 4% on Thursday after HSBC upgraded its rating to 'Buy' and sharply increased its target price to $200, hinting at nearly 40% upside from current levels. This bullish revision is tied to the company's advancing AI chip portfolio, particularly the MI300X and MI350 series, which analysts now believe can directly challenge NVIDIA's dominance in the booming AI data center space. Investors are taking notice, with big names like Meta, Microsoft, and OpenAI confirming orders for AMD's latest GPUs. How did AMD stock perform today? As of Friday, July 11, 2025 , AMD stock is trading at $144.16 , up $5.74 (+4.15%) from the previous close. This marks one of AMD's strongest sessions in recent weeks, driven by bullish analyst sentiment and renewed AI optimism. 52-week range : $93.12 – $211.00 YTD performance : +27.4% Market cap : $233.2 billion Volume : 56.8 million shares (vs. 30-day avg of 44.3M) by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like Warum Seniorinnen in Sachsen ausgerechnet diesem Schuh vertrauen Senioren-Ratgeber Undo Why is HSBC suddenly bullish on AMD stock? HSBC had previously held a cautious view on AMD's AI roadmap, citing modest performance improvements in earlier versions of its accelerators. However, this view changed dramatically following the company's unveiling of the MI350 series in June at its 'Advancing AI' event. Analysts now believe that the MI350—especially the MI355 accelerator—can compete with NVIDIA's Blackwell platform, both on specs and price. HSBC upgraded AMD from 'Hold' to 'Buy' and set a new target of $200, up from its previous view that underestimated pricing power. HSBC analysts estimate the average selling price of MI355 to be around $25,000, which is $10,000 higher than their earlier forecast. Even then, it's still roughly 30% cheaper than NVIDIA's B200 chip, making AMD's value proposition highly competitive. They now project AI GPU revenue to hit $151 billion by FY2026—57% higher than the current market consensus of $96 billion. Live Events What triggered AMD's sudden surge? On July 10, HSBC upgraded AMD from Hold to Buy and doubled its price target from $100 to $200, projecting nearly 40% upside from current levels. 'AMD's AI GPU revenue could hit $15.1 billion by FY2026, far above Wall Street's consensus of $9.6 billion,' HSBC analysts said in their note. Here's what's driving HSBC's bullish thesis: Key Driver Details MI350 Series Matches Nvidia's Blackwell performance at ~30% lower cost (avg selling price ~$25,000 vs. $35,000 for Nvidia). Cost Advantage Lower total cost of ownership (TCO) could attract hyperscalers like Meta, Microsoft, and AWS. Roadmap strength AMD's upcoming MI400/MI450 chips are expected to rival Nvidia's next-gen Vera Rubin platform. AI Ecosystem Expansion Open software tools and ROCm platform improving fast, narrowing the CUDA advantage gap. What are analysts forecasting for AMD? Forecast Metric Estimate FY2025 Revenue (Consensus) $28.7 billion FY2025 EPS (Consensus) $4.42 FY2026 AI GPU Revenue (HSBC) $15.1 billion HSBC Price Target $200 (40% upside) Forward P/E (FY2026) ~32x (if $6.20 EPS materializes) Several analysts, including those from Barclays and Jefferies, are also warming up to AMD's prospects: Barclays : Maintains Overweight , target raised from $160 → $180 Jefferies : Buy , says 'AMD now firmly second in AI race' Goldman Sachs : Still cautious, holds Neutral with $140 target Can AMD's MI300X chip really challenge NVIDIA's H100? The real game-changer in AMD's lineup is the MI300X, which is already being adopted by major hyperscalers. Meta Platforms has confirmed the chip will power Llama 3.1, its next-generation open-source AI model. In addition, Microsoft Azure and OpenAI are exploring deployments of AMD chips for training workloads. Analysts at Jefferies, Raymond James, and Loop Capital have responded by raising their AMD price targets to between $190 and $200. They see potential for AMD to capture a meaningful share of the AI GPU market, previously dominated almost entirely by NVIDIA. The MI300X's strong price-to-performance ratio is driving this narrative shift. Is Nvidia's AI leadership in danger? Nvidia (NASDAQ: NVDA) still dominates the AI chip market with nearly 90% market share , thanks to its: Proprietary CUDA software stack Deep developer base Long-term enterprise relationships Broad product portfolio (H100, Blackwell, Vera Rubin) Yet, AMD's improving chip roadmap and cost-effective GPUs are beginning to turn heads: Comparison Nvidia (Blackwell) AMD (MI350) Performance Best-in-class Competitive parity (per HSBC) ASP (Avg Selling Price) ~$35,000 ~$25,000 Launch Timeline 2024 H2 2024 H2 Ecosystem CUDA, strong developer base ROCm, rapidly growing "AMD is finally closing the AI performance gap. If it can scale supply and support, it could become a serious alternative to Nvidia," said Vivek Arya, Senior Analyst at BofA. What do AMD's latest earnings say about its AI growth? In Q1, AMD reported revenue of $5.47 billion, in line with expectations, with earnings per share (EPS) of $0.62, slightly ahead of Wall Street's forecast of $0.61. The Data Center segment stood out with $2.3 billion in revenue, up 80% year-over-year, thanks to strong uptake of the MI300 line. Meanwhile, revenue from AMD's Client segment fell 25% YoY, and Gaming dropped 6%, reflecting industry-wide slowdowns. However, the company held its gross margin at 52%, and expects to reach 55%+ by mid-2026, driven by high-margin AI chip sales and increased adoption of the Ryzen 9000 series. AMD reaffirmed its $5 billion AI revenue goal by the end of 2025, even as some investors question the timeline. Still, the broader shift in sentiment suggests more are now buying into AMD's AI vision. What are analysts saying about AMD's future valuation? Despite trading at a forward P/E of 52x on expected 2025 earnings, analysts argue AMD's valuation is justified—perhaps even conservative—given its rapidly expanding AI opportunity. If AMD achieves $4B–$5B in AI-related sales by 2025, with an estimated 25–30% operating margin, it could bring in $1.2B–$1.5B in incremental income, boosting overall earnings by up to 25%. This could position AMD alongside other high-growth tech stocks like NVIDIA and Broadcom, which trade at even higher multiples due to their strong AI businesses. Short-term targets : $150–$160 range could be tested in coming weeks if technical momentum holds. Support: ~$135 Resistance: $151.40 (April high) Medium-to-long term : If AMD executes its MI400 launch in 2025 , and AI GPU sales hit $15B+ in FY26, a $200+ valuation is reasonable. Catalysts to watch: Q2 earnings (expected August 5), hyperscaler adoption updates, MI450 development news. Are institutions and traders betting big on AMD stock? Yes, and the momentum is growing. In Q2 2025 filings, institutional investors like Vanguard and BlackRock increased their AMD positions, while hedge funds such as Coatue Management and D1 Capital opened new stakes. Notably, AMD insiders have not sold stock since April, a sign of internal confidence. Retail investors are piling in too. Options trading volumes on AMD jumped 38% week-over-week, with heavy call buying on $180–$200 strike prices for July and August. This suggests short-term conviction is building around a breakout toward the $200 level. What are the risks to AMD's $200 stock target? Despite the strong setup, AMD isn't without risks. NVIDIA's lead in CUDA software and ecosystem loyalty still gives it a competitive edge. AMD must grow its ROCm software and ecosystem fast to win over more developers and customers. TSMC's production constraints may also limit output, especially with rising HBM3e demand. Additionally, Intel's Gaudi 3 chips pose a future challenge if widely adopted. However, analysts say AMD's pricing advantage, first-mover momentum, and real-world design wins make it a serious contender in AI chips—at least for the next few quarters. Is AMD stock a buy at current levels? With real traction from Meta, Microsoft, and OpenAI, rising gross margins, and a sharply upgraded AI revenue forecast, AMD stock (NASDAQ:AMD) is seeing a clear re-rating from Wall Street. If delivery timelines hold and adoption continues, the stock could realistically hit $195–$200 in Q3. The AI chip race is heating up—and AMD is no longer just a follower. FAQs: Q1: Why did AMD stock price rise after HSBC's rating upgrade? AMD stock price rose because HSBC raised its rating to 'Buy' and increased the target price to $200, driven by strong demand for AMD's AI chips. Q2: Is AMD's MI300X chip competing with NVIDIA's AI GPUs? Yes, AMD's MI300X is now seen as a real competitor to NVIDIA's H100, with big tech firms already using it for AI workloads.
Time of India
13-06-2025
- Business
- Time of India
AMD unveils AI server as OpenAI taps its newest chips
Synopsis AMD has unveiled its upcoming MI400-based "Helios" AI server, set for 2026, to rival Nvidia's dominance. CEO Lisa Su stressed open collaboration, with support from OpenAI, Meta, and xAI. Su was joined onstage by OpenAI's Sam Altman, who said his company is using AMD's MI300X and MI450 chips.
Yahoo
12-06-2025
- Business
- Yahoo
DigitalOcean and AMD Collaborate to Advance AI Using Cloud-Based GPUs
NEW YORK, June 12, 2025--(BUSINESS WIRE)--DigitalOcean Holdings, Inc. (NYSE: DOCN), the simplest scalable cloud for digital native enterprises, today announced a collaboration with AMD that provides DigitalOcean customers with access to AMD Instinct™ GPUs as DigitalOcean GPU Droplets to power their AI workloads starting with the AMD MI300X GPUs. Later this year, DigitalOcean will offer AMD Instinct™ MI325X GPUs, further expanding access to powerful and affordable GPU models. AMD Instinct™ MI325X GPU accelerators set new AI performance standards, delivering incredible performance and efficiency for training and inference. AMD Instinct MI300X GPUs deliver leadership performance for accelerated high-performance computing (HPC) applications and the newly exploding demands of generative AI. With the AMD ROCm™ software platform, customers can develop powerful HPC and AI production-ready systems faster than ever before. Its large memory capacity allows it to hold models with hundreds of billions of parameters entirely in memory, reducing the need for model splitting across multiple GPUs. By combining powerful AMD AI compute engines and DigitalOcean's cloud technologies, the collaboration aims to empower the massive community of digital native enterprises to integrate AI into their applications and support the most demanding AI workloads at scale. These next-generation GPUs have already been available in bare metal configurations for customers seeking increased control and computing power. These GPUs are now also available as GPU Droplets or as DigitalOcean Kubernetes worker nodes. The GPU Droplets are available both as single and eight GPU configurations, allowing customers to optimize costs for their specific use cases. Accessing these GPU Droplets through DigitalOcean offers several key benefits, including competitive pricing at $1.99/GPU per hour, a simple setup process, and enterprise-grade SLAs. While other cloud providers require multiple steps and deep technical knowledge to configure security, storage, and network requirements, DigitalOcean's GPU Droplets can be set up with just a few clicks. In addition to these new GPUs, customers will also have access to AMD Developer Cloud, a new platform powered by DigitalOcean that is purpose-built for rapid, high-performance AI development. Customers will have access to a fully managed environment that provides instant access to AMD Instinct MI300X GPUs—with zero hardware investment or local setup required. Whether fine-tuning LLMs, benchmarking inference performance, or building a scalable inference stack, the AMD Developer Cloud provides the tools and flexibility to get started instantly—and grow without limits. "DigitalOcean's collaboration with AMD is another proof point to make AI easily accessible to our customers," said Bratin Saha, Chief Product & Technology Officer at DigitalOcean. "With access to AMD GPUs, DigitalOcean customers have an extensive portfolio of GPUs with the flexibility of the computing configuration that best suits their requirements." "At AMD, we are proud to work with DigitalOcean to provide developers with cutting-edge solutions for developer enablement and demanding workloads that require large amounts of memory," said Negin Oliver, corporate vice president of business development, Data Center GPU Business, at AMD. "Together, AMD and DigitalOcean are committed to providing the critical innovative technologies required to support the evolving needs of growing tech businesses." To access AMD Instinct GPUs with DigitalOcean, visit the DigitalOcean website. About DigitalOcean DigitalOcean is the simplest scalable cloud platform that democratizes cloud and AI for digital native enterprises around the world. Our mission is to simplify cloud computing and AI to allow builders to spend more time creating software that changes the world. More than 600,000 customers trust DigitalOcean to deliver the cloud, AI, and ML infrastructure they need to build and scale their organizations. To learn more about DigitalOcean, visit View source version on Contacts Media Contact Ken Lotichpress@ Investor Contact Melanie Strateinvestors@
