All articles tagged with #ai chips
AI-driven gains push SK Hynix above $1 trillion in market value as Micron rallies; China’s April industrial profits jump about 24.7%, and European firms remain committed to Chinese manufacturing. ECB signals it will do what’s necessary to bring inflation to 2% while markets hover near records, and investor attention turns to Ferrari’s disappointing Luce EV launch and BP’s share decline after the chairman’s exit over conduct concerns.
SK Hynix shares jumped up to 11%, pushing its market cap above $1 trillion on surging AI-memory demand and Nvidia ties; Samsung Electronics also crossed the $1 trillion mark, underscoring a concentration of AI-related semiconductors in Korea’s Kospi and signaling potential market volatility.
Cerebras Systems (CBRS) stock fell more than 5% in premarket trading on its second day of trading after an IPO that priced at $185 and opened at $350, an 89% jump from the offering price, as investors weigh demand for AI hardware.
Cerebras Systems began trading on Nasdaq with an IPO priced at $185 and closed its first session around $311.07, up about 68%, in what was the largest IPO of 2026 so far. The company raised roughly $5.55 billion by selling 30 million shares, valuing it near a $67 billion market cap. Cerebras, whose wafer-scale AI chips power systems like CS-2 and CS-3, counts OpenAI, Amazon and Meta among its customers and is pitched as a rival to Nvidia, albeit far smaller. Revenue has grown rapidly (2022–2025: from $24.6M to $510M in 2025), but the company remains unprofitable on an operating basis, with 2025 R&D at about 48% of sales and negative operating cash flow (~$10.1M). Analysts note potential index inclusions (S&P 500, Nasdaq-100) could provide tailwinds, but Fool’s Stock Advisor does not list Cerebras among its current top picks, underscoring the stock’s growth-story risk and the need to watch profitability as it scales.
Nvidia is poised to report strong earnings as AI demand remains robust, but rising competition and a rich valuation create headwinds, with customers building their own AI chips and Broadcom/OpenAI/Google options; the article argues Nvidia isn’t a buy now and that Amazon offers a more diversified, cheaper AI-chip opportunity through Trainium, Graviton, Nitro and AWS growth.
The U.S. has cleared about 10 Chinese firms (including Alibaba, Tencent, ByteDance and JD.com) and several distributors to buy Nvidia’s H200 AI chips, with a cap of 75,000 chips per buyer, but not a single shipment has occurred as Beijing weighs security concerns and broader domestic AI ambitions while Nvidia’s Jensen Huang pursues a breakthrough during high-level talks between Trump and Xi.
Cerebras Systems is planning to raise the size and price of its IPO, considering a new price range of $150-$160 per share and up to 30 million shares, potentially pulling in about $4.8 billion, as demand for AI chips remains strong; the offering is set for Nasdaq under the symbol CBRS with pricing expected May 13, and orders have run more than 20x the available shares. The company counts Amazon and OpenAI among customers and previously paused its 2024 IPO after a CFIUS review of its G42 partnership, which has since been cleared.
Advanced Micro Devices (AMD) surged to a 52-week high with a year-to-date gain near 112%, as investors rotate out of Nvidia into AMD on faster growth and a smaller base. AMD’s strength in Agentic AI workloads boosts demand for its EPYC CPUs and Instinct GPUs, while MI355X accelerators gain traction for AI inference and ROCm’s maturation closes the CUDA gap. Price targets up to $625 imply meaningful upside despite a high trailing P/E, making AMD a leading momentum play for 2026 as the AI server market shifts in its favor.
Arm beat Q4 estimates, posting adjusted EPS of $0.60 on $1.49B revenue, but after an initial ~12% after-hours surge, the stock slid about 8% as investors weighed supply bottlenecks and higher costs from Arm’s shift into in-house AI chips. Management said AGI CPU demand has already topped $2B within six weeks, yet securing wafers, memory, and advanced packaging remains tight, leaving the revenue target for the product line at $1B through FY2027. The move into manufacturing could boost long-term growth but may pressure margins if growth slows. Analysts remain largely bullish, though the elevated expectations leave room for near-term volatility.
Nvidia has ridden AI-driven demand to a market cap above $5 trillion, but three 2026 risks loom: customer concentration (two clients accounted for about 36% of FY26 revenue), intensifying AI-chip competition from AMD, INTC and in-house efforts by Google, Amazon, and Meta, and a rich valuation (P/E around 43) that could amplify volatility if growth slows. Despite these risks, analysts still see upside and rate NVDA as a Strong Buy, with a ~30%+ upside to a year-ahead target.
Anthropic plans to spend about $200 billion with Google over five years as part of a deal to dramatically expand Google Cloud capacity and chip supply, representing more than 40% of Google's disclosed cloud revenue backlog and underscoring Anthropic’s role in the AI-infrastructure race.
SpaceX’s IPO could raise up to $75 billion, with the fresh cash expected to be deployed quickly into AI infrastructure. Nvidia is the obvious winner, given SpaceX’s heavy use of Nvidia GPUs and plans to build in-house chips. SpaceX’s xAI venture and potential ties to Tesla’s autonomy and energy initiatives could further lift the AI ecosystem. Overall, the IPO is portrayed as a catalyst for AI hardware and related stock gains.
Google and Amazon are moving to sell their own AI chips (TPU and Trainium) directly to customers, challenging Nvidia's dominance. Google plans select data-center sales this year with broader revenue by 2027, while Amazon aims to offer full chip racks beyond its cloud in the coming years. Analysts say the shift is irreversible but won’t be easy due to Nvidia’s ecosystem and bespoke deployments, and Nvidia remains a major supplier as AI workloads diversify.
Stocks of Nvidia, AMD, Oracle and other AI-chip names dropped after reports that OpenAI’s growth is slowing and may miss internal user and revenue targets, suggesting weaker near-term demand for the compute capacity powering AI. The Fool notes Nvidia and AMD still posted strong quarterly growth, and while OpenAI’s slowdown could push out some orders, the broader AI market appears to be redistributing demand among competitors rather than collapsing, leaving room for value opportunities for long-term investors.
Google Cloud chief Thomas Kurian argues that owning the full AI stack—in-house chips (TPUs), Gemini models, and DeepMind-driven tech—will help Google close the gap with AWS and Azure. The company previewed newer TPU generations, touted its self-developed hardware and software as a differentiator, and expanded its Chips–to–Models ecosystem with a $40 billion Anthropic investment. Google says this approach reduces Nvidia dependency, supports faster, cheaper AI deployments, and underpins a forecast of rapid cloud revenue growth (around $70 billion this year) with heavy capex of about $185 billion.