Report
No Data Yet
Nasdaq 100 futures declined 0.5% in pre-market trading Thursday as semiconductor stocks came under renewed selling pressure, while oil prices held steady after falling to the lowest level since before the Iran conflict began. "The chip selloff is rotating back into focus after a one-day pause, with traders positioning ahead of PCE data that could shift the inflation narrative," said Sarah Lin, equity market analyst at Edgen. The Invesco PHLX Semiconductor Sector Index sank 7% on Tuesday in its worst single-day drop this year, then stabilized Wednesday with a modest recovery as the broader market rallied on falling oil prices. Micron Technology Inc., which fell 14% over Tuesday and Wednesday combined from an all-time high, reported earnings after Wednesday's close. The stock added to losses in after-hours trading, extending pressure on the sector. WTI crude traded near $70 a barrel Thursday after sliding 4% on Wednesday to touch $69.84 intraday, the first dip below that level since early March. The decline followed news that more than 11,000 seafarers stranded in the Persian Gulf received safety guarantees to exit through the Strait of Hormuz, with President Donald Trump saying Iran committed to no tolls or extra charges on ships. Brent fell 4% to around $73. The 10-year Treasury yield held near 4.41% after falling 8 basis points Wednesday, while the 2-year yield stayed around 4.15%. The moves across the curve pointed to a shift in inflation expectations as crude returned to pre-conflict levels. Thursday's personal consumption expenditures report, the Federal Reserve's preferred inflation gauge, arrives with oil at its cheapest since before U.S. and Israeli strikes on Iran started in late February. S&P 500 futures edged higher alongside the Dow, suggesting a split session where tech weakness may be offset by gains in other sectors. The S&P 500 closed Wednesday at 7,572, up 0.6%, after testing its 50-day moving average at 7,350 and holding. The Dow Jones Industrial Average added 457 points, or 0.9%. This article is for informational purposes only and does not constitute investment advice.
**Japan is building the world's first national AI infrastructure, powered by 27,500 of Nvidia's latest Rubin GPUs in a 140-megawatt data center.** Japan's Ministry of Economy, Trade and Industry partnered with Nvidia Corp. and Noetra Corp. to build the world's first national AI infrastructure, a 140-megawatt data center powered by 27,500 Rubin GPUs and 13,750 Vera CPUs. "This infrastructure will serve as the computing foundation for Japan's FRONTia Project, strengthening the country's ecosystem across manufacturing, logistics and health care," a METI official said. The facility, built on Nvidia's DSX platform, will deliver 140 MW of capacity — enough to power roughly 115,000 homes. Noetra Corp will serve as the construction partner. The deployment marks the first commercial use of Nvidia's Vera Rubin architecture, which the company unveiled as its next-generation AI computing platform. The deal confirms Nvidia's strategy of selling complete AI factory solutions rather than individual chips, a model that pressures rivals Advanced Micro Devices Inc. and Intel Corp. to match the integrated approach. For Japan, the investment positions the country as a sovereign AI leader at a time when nations are racing to secure domestic computing infrastructure. **Vera Rubin Marks Nvidia's Next Architecture Leap** The Vera Rubin platform represents Nvidia's successor to the Blackwell architecture. Each Rubin GPU is designed for training and inference of large language models, while the Vera CPU handles data processing and orchestration. Nvidia has not disclosed per-chip pricing, but the 27,500-GPU deployment implies a multi-billion-dollar procurement for Noetra and its backers. The 140 MW capacity places the facility among the largest single-site AI data centers globally. By comparison, typical hyperscaler data centers range from 30 MW to 100 MW, according to industry data from Synergy Research Group. The scale highlights Japan's ambition to compete with the U.S. and China in AI infrastructure buildout. **Japan's Broader AI Push Extends Beyond One Facility** The FRONTia Project is part of a wider Japanese government effort to integrate AI across its industrial base. Earlier this week, Fujitsu Ltd. announced it would lead a consortium of Japanese robotics companies using Nvidia technology to develop "physical AI" for manufacturing and logistics applications. The twin announcements — a national AI factory and a robotics-AI push — signal that Japan is pursuing a two-track strategy: building centralized compute capacity while embedding AI into its traditional manufacturing strength. Toyota Motor Corp. has also expanded its AI partnership with Nvidia for smart city and factory applications, according to a Bloomberg report. **Investment Implications** Nvidia shares, trading at roughly 35 times forward earnings, have gained more than 140 percent over the past 12 months on the back of surging AI infrastructure spending. The Japan deal adds a new sovereign demand driver beyond the hyperscaler customers — Amazon Web Services, Microsoft Corp. and Alphabet Inc.'s Google — that have driven the bulk of Nvidia's data center revenue. For AMD and Intel, the integrated factory model raises the competitive bar. Both companies sell individual chips and networking components but lack Nvidia's full-stack DSX platform that ties hardware, software and networking into a single deployment. If sovereign AI demand accelerates, Nvidia's first-mover advantage in turnkey infrastructure could widen further. This article is for informational purposes only and does not constitute investment advice.
Apple has gained 20% so far in 2026, doubling the S&P 500's 10% rise, as the iPhone maker stages a comeback from a lackluster 2025 weighed down by tariff concerns and persistent inflation. The company's market capitalization now sits at roughly $4.2 trillion, trailing only Nvidia's $5.1 trillion valuation — a gap that may close faster than many expect as Apple's core business regains momentum. "Rising memory and component costs pushed most Android vendors to raise prices, which cooled upgrade demand," IDC Global said in a report on China's smartphone market. Apple was one of only two vendors to post growth in the quarter. The dynamics are playing out most sharply in China, which accounts for about 18% of Apple's sales. Chinese smartphone shipments fell 4.3% year over year in the most recent quarter, marking the fifth consecutive period of decline, according to IDC. Yet Apple's iPhone sales in the country jumped 24% year over year, the highest growth rate among all vendors in China. The company has absorbed higher input costs rather than passing them to consumers, stealing share from Android rivals such as Xiaomi and Oppo that were forced to raise prices as soaring demand for DRAM and NAND flash memory chips pushed component costs higher. Apple has a long history with the market cap crown. In August 2018, it became the first publicly traded U.S. company to reach $1 trillion. It added $2 trillion in August 2020 and $3 trillion in January 2022. The AI revolution shifted the crown to Nvidia, which became the first to reach $4 trillion in July 2025 and $5 trillion in October 2025. Now, Apple's iPhone momentum and expanding services business are setting up a potential reversal. **Apple Intelligence Approval Opens New Revenue Path** Chinese regulators this week approved Apple Intelligence for deployment on iPhones in the country, ending a two-year licensing process. Apple partnered with Alibaba and Baidu to meet China's requirement that foreign companies collaborate with local partners on AI services. The approval could accelerate iPhone upgrades among China's base of existing users, many of whom delayed purchases pending the feature's availability. The company's strategy of maintaining iPhone prices despite rising component costs has expanded its installed base. That larger user pool feeds Apple's services business, which carries higher margins than hardware sales and creates stickiness for accessories and other Apple products. Services revenue now represents a growing share of Apple's total revenue, providing a more predictable income stream that supports the company's valuation premium. iPhone users are also more likely to adopt other Apple products, including the Apple Watch, AirPods, and Mac, creating a cycle of ecosystem lock-in that competitors have struggled to replicate. **Why Apple's Valuation Could Close the Gap** Nvidia's $5.1 trillion market cap reflects investor expectations for continued AI infrastructure spending. The chipmaker's data center revenue has grown at triple-digit rates for multiple quarters, but any sign of slowing AI adoption could pressure its valuation. Apple trades at roughly 30 times forward earnings, compared with Nvidia's 35 times — a discount that could narrow as Apple's earnings growth accelerates on the back of China market share gains and the Apple Intelligence upgrade cycle. For investors, the key question is whether Apple can sustain its China momentum. The country has historically accounted for about 18% of Apple's sales, and the company's ability to hold prices steady while competitors raise them has created a rare opportunity to gain share in the world's largest smartphone market. Combined with the Apple Intelligence approval, the conditions are in place for a multi-quarter upgrade cycle that could push Apple's market cap past Nvidia's. Apple's path to reclaiming the market cap crown depends on sustaining its China momentum and converting Apple Intelligence approvals into a measurable upgrade cycle. With the S&P 500 up 10% this year and Apple doubling that return, the market is already pricing in a recovery. The full re-rating may only come once iPhone sales data confirms the trend is durable. This article is for informational purposes only and does not constitute investment advice.
**Japan's government is placing one of the largest known sovereign orders for Nvidia's next-generation AI chips.** Japan will purchase 27,500 of Nvidia Corp.'s Rubin chips to build a national robotics AI system, marking one of the biggest government AI hardware procurements to date. "This order reflects Japan's commitment to building sovereign AI infrastructure for robotics," Jensen Huang, Nvidia's chief executive officer, said at a developer event in Tokyo. Huang also dismissed reports of manufacturing delays for the Vera Rubin platform, calling them "not true" and vowing to deliver "giant amounts" of the systems. The Rubin architecture, built on TSMC's advanced nodes, succeeds Nvidia's Blackwell line as the company's flagship AI accelerator. The Blackwell B200, Nvidia's current-generation chip, delivers up to 20 petaFLOPS of FP4 performance and 4.5 terabytes per second of memory bandwidth, according to Nvidia's published specifications. The Vera Rubin platform — named after the American astronomer who discovered dark matter — is expected to deliver significant performance gains over the Blackwell Ultra, though Nvidia has not disclosed full specifications. Huang's comments in Tokyo were the first public confirmation that Rubin production remains on schedule. Japan's robotics push is a strategic priority for a nation facing a shrinking workforce. The country's population aged 65 and older now accounts for about 29% of the total, creating urgent demand for automation in manufacturing, logistics and elder care. The 27,500 Rubin chips will power AI models that enable robots to perceive, plan and act in real time — capabilities that require the massive parallel processing that graphics processing units provide. The Japanese procurement highlights a broader trend of sovereign nations building domestic AI infrastructure rather than relying solely on US-based cloud providers. For Nvidia, which generated $47.5 billion in data center revenue in fiscal 2025, government orders are becoming a meaningful demand driver alongside hyperscaler customers such as Microsoft Corp., Amazon.com Inc. and Alphabet Inc. The order comes as Nvidia faces intensifying competition from Advanced Micro Devices Inc., whose MI300X and upcoming MI400 accelerators target the same AI workloads. AMD has secured government AI contracts in Europe and the US, though Nvidia's CUDA software ecosystem — the industry-standard platform for GPU computing — remains a significant competitive advantage. Japan's selection of Rubin over AMD's Instinct line reinforces Nvidia's dominance in sovereign AI deployments. On the supply chain side, Nvidia relies on Taiwan Semiconductor Manufacturing Co. for chip production and on advanced packaging providers such as ASE Technology Holding Co. for CoWoS (chip-on-wafer-on-substrate) packaging, a critical step in assembling high-bandwidth memory with the GPU die. Huang's confidence that Rubin is on track suggests no disruption to TSMC's capacity allocation for Nvidia's next-generation products. Nvidia shares trade at about 35 times forward earnings, reflecting investor expectations that AI infrastructure spending will continue to grow. Japan's 27,500-chip order, while modest relative to Nvidia's total annual output of millions of AI accelerators, signals that sovereign demand is becoming a structural revenue contributor. Morgan Stanley analyst Joseph Moore has maintained an overweight rating on Nvidia, citing sustained demand across hyperscale and enterprise customers. This article is for informational purposes only and does not constitute investment advice.
**Apple's in-house M2 Ultra server chip cannot run Google's Gemini model, forcing the company to rely on Nvidia hardware and sparking a hunt for chip startup acquisitions.** Apple's push into AI is hitting a hardware wall. The company's M2 Ultra server chip cannot run Google's Gemini model, forcing it to rent Nvidia GPUs on Google Cloud for the revamped Siri. "These chips simply cannot handle models of this scale," a person familiar with Apple's internal testing told The Information, describing the company's failed attempt to deploy Gemini on its own infrastructure. Apple's chip team, long focused on mobile power efficiency, faces a fundamentally different set of demands in AI servers — high power consumption, high concurrency, and large memory bandwidth. The company had hoped its next-generation server chip, code-named Baltra, would close the gap, but the project has been delayed, according to people familiar with the matter. The gap leaves Apple dependent on Nvidia, a company some Apple executives have described as "difficult to work with," for at least three more years. Its M7 Ultra server chip — with up to 1.5TB of memory, roughly double the M5 Ultra — is not expected until 2029, leaving a multiyear window in which rivals could widen their lead. **Acquisition Strategy Takes Shape** Apple has held discussions with bankers about potential chip acquisitions in recent months and has approached semiconductor startups to gauge their interest in a sale, according to The Information. The move marks a shift for a company that has historically favored small, bolt-on deals over large transactions. Apple's largest acquisition remains the $3 billion purchase of Beats Electronics in 2014. But the company signaled a bigger appetite for deals this year, agreeing to acquire Israeli startup Q.ai for about $2 billion — its second-largest acquisition ever. Q.ai's technology interprets speech content through facial micro-expressions. Financial policy changes also point to a more aggressive posture. Chief Financial Officer Kevan Parekh told investors on the second-quarter earnings call that Apple would abandon its long-standing "net cash neutral" policy, which had kept cash reserves balanced against total debt. The Information noted the change could free up cash for larger acquisitions. Apple's in-house chip effort itself began with an acquisition: the $278 million purchase of PA Semi in 2008, which laid the foundation for more than a decade of custom silicon development. **Broadcom Partnership and the Road to 2029** Apple is pursuing multiple paths to bridge the gap. The company has been working with Broadcom on AI server chip development since 2024, and Broadcom disclosed in a securities filing last week that the two companies have extended their long-term technology partnership through 2031, though it did not specify the scope of the collaboration. In the near term, Apple is planning a server upgrade based on the M5 Ultra as an interim solution. The more ambitious M7 Ultra, which could rival Nvidia's Blackwell architecture in performance, is not expected to reach servers until 2029, according to Bloomberg. The timeline means Apple faces at least three years of relying on external partners for the most demanding AI workloads — a strategic setback for a company built on vertical integration. Nvidia shares have gained more than 4% in Wednesday trading as the market digests the implications of Apple's dependency. **Leadership Transition Adds Uncertainty** Apple is approaching a CEO transition, with hardware chief John Ternus set to replace Tim Cook in September 2026. Chip head Johny Srouji will be promoted to oversee all hardware engineering while retaining responsibility for semiconductor development. The new leadership team may bring a more aggressive acquisition approach, according to people familiar with Apple's internal dynamics. For investors, the key question is whether Apple can close its AI infrastructure gap before competitors widen their advantage. Nvidia, which trades at about 35 times forward earnings, continues to dominate the AI chip market, while Google's custom TPU and Microsoft's partnership with OpenAI keep both companies ahead in AI deployment. Apple's M7 Ultra, if it delivers on its promised performance, could shift the balance — but not for three years. This article is for informational purposes only and does not constitute investment advice.
Nvidia enlisted 10 of Japan's largest industrial companies to join its Cosmos Coalition, betting the nation's manufacturing heritage can accelerate physical AI deployment across factories, farms and hospitals. "The next frontier of AI is in the physical world, and this is a once-in-a-generation opportunity for Japan," Jensen Huang, founder and chief executive officer of Nvidia, said. "Japan invented modern manufacturing. Now, it has the opportunity to reinvent it for the age of intelligent industries." The coalition includes FANUC, Yaskawa Electric, Kawasaki Heavy Industries, Hitachi, Sony Group, SoftBank Corp., NEC, Kubota, Fujitsu and AIRoA. Nvidia also introduced Cosmos 3 Edge, a 4-billion-parameter model for on-device vision reasoning and robot policy deployment on its Jetson Thor platforms. The lightweight model, built on Nvidia's Nemotron architecture, can be adapted for specific robots, vehicles and environments in about a day, the company said. The partnerships position Nvidia's physical AI stack — spanning Cosmos world models, Isaac robotics development tools, Metropolis vision AI libraries and Jetson edge hardware — as the foundational platform for Japan's next industrial wave. Japanese manufacturers spent an estimated $35 billion on industrial automation in 2025, according to the Japan Robot Association, a figure that could grow as AI-powered machines replace traditional programmable logic controllers. **Cosmos 3 Edge Brings Frontier AI to the Factory Floor** Cosmos 3 Edge runs on Nvidia's newly announced Jetson Thor modules, including the T3000 and T2000. The T3000 delivers 865 FP4 teraflops of AI compute with a Blackwell GPU, an eight-core Neoverse Arm CPU and 32 gigabytes of LPDDR5X memory in a form factor roughly half the size of the T5000. The T2000 offers 400 FP4 teraflops and 16 gigabytes of memory as a lower-cost entry point for autonomous mobile robots and industrial manipulators. Both modules are scheduled for availability in the first quarter of 2027. The model helps robots understand their surroundings, reason in real time and generate actions locally without cloud connectivity — a requirement for factory environments where latency and data privacy matter. Nvidia's Metropolis libraries, also announced alongside Cosmos 3 Edge, help developers build video intelligence systems at least six times faster using coding agents, the company said. Fujitsu is exploring a collaborative control platform with FANUC, Yaskawa Electric and Kawasaki Heavy Industries that integrates Nvidia's full physical AI stack, including Cosmos world foundation models, the Isaac robotics platform, Omniverse NuRec libraries and the Newton physics engine. The platform would support digital twins, robot learning, simulation-to-real workflows and pre-deployment validation across industrial sectors. SoftBank Corp. is developing its own physical AI platform built on Cosmos, Omniverse and Isaac Sim, while also advancing AI-RAN initiatives using Nvidia's AI Aerial technology to deliver connectivity for billions of physical AI devices. NEC, Hitachi, OMRON and Preferred Networks are using Cosmos for world models and industrial AI research. **Japan's Industrial Giants Spread Physical AI Across Sectors** The applications span Japan's industrial base. Kawasaki Heavy Industries is applying Nvidia's physical AI technologies across healthcare, shipbuilding, transportation, aerospace and energy. Kubota is exploring Cosmos-based physical AI for autonomous agriculture and smart farming. Enactic is fine-tuning Nvidia's Isaac GR00T open model for elder-care semi-humanoid robots, while GROOVE X builds Jetson-powered companion robots called LOVOT. In manufacturing, TRON K.K. is developing data workflows for task-specific physical AI models in assembly, picking, inspection and material handling, alongside factory 3D digitization workflows. Mujin is exploring Cosmos for autonomous robotics powered by its MujinOS operating system. Hitachi, OMRON and Shimizu Corp. are using Metropolis to bring Cosmos-powered vision AI agents into smart-building operations, automated inspection and construction safety, respectively. The coalition expansion gives Nvidia a beachhead in Japan's industrial automation market, where incumbents like Mitsubishi Electric and Keyence have long dominated. Nvidia shares, trading at about 35 times forward earnings, have gained 140 percent over the past 12 months as investors priced in the physical AI opportunity. The company's data center revenue reached $35.6 billion in its most recent fiscal year, driven largely by AI training and inference workloads that Cosmos aims to extend into robotics and edge computing. This article is for informational purposes only and does not constitute investment advice.
Apple Inc. has held discussions with bankers about potential chip acquisitions in recent months and approached semiconductor startups to gauge interest in a sale, according to a person familiar with the matter. The iPhone maker's M2 Ultra chips — built on TSMC's 5nm process — couldn't run Google's Gemini models efficiently, forcing Apple to rent Nvidia Corp. GPUs hosted in Google Cloud for more demanding workloads. "Apple has held discussions with bankers about potential chip acquisitions in recent months and has also approached semiconductor startups to gauge their interest in a sale," the person said. The company's future AI server chip, code-named Baltra, has been delayed, according to the report. Apple's current infrastructure relies on internally designed M2 Ultra processors for some workloads, but those chips have struggled with larger AI models. The company had to turn to Nvidia GPUs hosted in Google Cloud for more demanding tasks. Apple shares rose more than 4% Wednesday and hit a fresh all-time high on July 15 as investors priced in potential M&A upside. A confirmed acquisition would reduce Apple's dependence on Nvidia and strengthen its in-house AI capabilities, potentially reshaping the competitive dynamics in the AI semiconductor space. Apple's server chip struggles mirror a broader industry push. Amazon.com Inc., Alphabet Inc. and Microsoft Corp. have all developed custom AI chips to reduce reliance on Nvidia, whose H100 GPU — with 990 TFLOPS of FP16 performance and 80GB of HBM3 memory — dominates the data center market. The M2 Ultra, designed for Mac Pro workstations rather than data center-scale inference, lacks the high-bandwidth memory and parallel compute capacity needed for large language models. Running models like Gemini requires sustained memory bandwidth that consumer-grade chips cannot provide. Nvidia's H100 delivers 3.35 TB/s of memory bandwidth through its HBM3 stack, while Apple's M2 Ultra offers 800 GB/s — a gap that makes inference on large models impractical at scale. This performance shortfall forced Apple to rely on Google Cloud's Nvidia-powered infrastructure during the development of its revamped Siri. Apple agreed to acquire Israeli startup Q.ai for $2 billion earlier this year, its second-largest acquisition after the $3 billion purchase of Beats Electronics in 2014. The deal signaled a greater willingness to pursue larger transactions as competition in AI intensifies. Acquiring a chip startup could accelerate development of the delayed Baltra server chip. Apple needs processors capable of running large AI models efficiently on its own infrastructure — a capability that would reduce cloud rental costs and give Apple greater control over its AI roadmap. The company has approached bankers and semiconductor startups in recent months, suggesting it is actively evaluating targets rather than passively monitoring the market. Apple shares trade at roughly 30x forward earnings, a premium to the S&P 500's 21x but below Nvidia's 35x multiple. The AI chip acquisition speculation has added momentum to a stock that has already gained more than 20% this year. If Apple successfully acquires a chip startup and delivers Baltra on schedule, it could save hundreds of millions annually in GPU rental costs from cloud providers. Nvidia faces a potential long-term headwind if Apple reduces reliance on its GPUs, though any competitive threat remains years away. Chip development cycles from acquisition to production typically span 18 to 24 months, and Apple has yet to name a specific target. For now, Nvidia's dominance in AI data center chips remains unchallenged — the company controls an estimated 80% of the market for AI training and inference processors. This article is for informational purposes only and does not constitute investment advice.
**The traditional 60/40 stock-bond portfolio is obsolete because artificial intelligence has become impossible for investors to avoid, according to Apollo's chief economist.** For decades, the golden rule of investing was simple: Put 60% of money into stocks and 40% into bonds. That framework is officially dead, replaced by a binary bet on artificial intelligence versus everything else, according to Torsten Slok, chief economist at Apollo. "The new 60-40 is AI vs. non-AI," Slok said in a research note shared with MarketWatch. The 10 largest companies in the S&P 500 now account for about 40% of the capitalization-weighted index's value, Slok said. Nine of those 10 have businesses tied to AI, with drugmaker Eli Lilly the lone exception. Nvidia Corp. alone represents 7.5% of the benchmark, followed by Apple Inc. at 6.8% and Alphabet Inc. at 6.4%. Microsoft Corp., Amazon.com Inc., Broadcom Inc., Meta Platforms Inc., Tesla Inc. and Micron Technology Inc. round out the top 10, each with weightings between 1.6% and 4.2%. The concentration risk extends well beyond equities. In the investment-grade bond market, AI infrastructure accounts for 49% of all net new issuance this year, while 87% of net new venture capital has flowed to AI companies, according to Apollo data. Even high-yield bonds show a 38% AI share of net new issuance, meaning investors who thought they held diversified portfolios may be far more exposed to a single theme than they realize. **AI's Grip on Capital Markets** The dominance of AI as an investment theme has made it nearly impossible for diversified investors to avoid. Foreign stock markets show similar patterns, with semiconductor names in Taiwan and South Korea dominating major emerging-market indexes, Slok said. The data-center buildout alone is expected to drive about half of the 2% real GDP growth projected for the U.S. economy in 2026, according to Slok. That makes the AI theme not just a market story but a genuine macroeconomic risk with consequences for investors and consumers alike. "The big risk is that the technology fails to deliver the hoped-for results," Slok said, pointing to the need for dramatic gains in worker productivity and corporate profit margins. So far, the only companies clearly profiting from AI are those making the semiconductors and equipment needed to power and operate data centers. **What's at Stake for the 493** The critical question, Slok said, is whether the productivity gains will spill over to the other 493 companies in the S&P 500 — those outside the trillion-dollar "Magnificent Seven" club. "There's no doubt that the Mag Seven have done well, but at the end of the day, is this going to spill over?" he said. If the data-center buildout slows, the effect could ripple across the economy. A sharp decline in asset values could also hit consumer spending, as the wealth effect has played an increasingly important role in driving U.S. consumption since the pandemic. For now, investor appetite for AI-related assets remains robust, according to Rob Haworth, a senior strategist at U.S. Bank Wealth Management. The S&P 500 finished about half a percentage point shy of its record close from early June, suggesting investors are rotating within equities rather than exiting the market entirely. "Market sentiment is telling you the demand is there, credit spreads aren't widening out, so investors aren't being scared away by all of this debt issuance," Haworth said. *This article is for informational purposes only and does not constitute investment advice.*
Dan Ives, the Wedbush Securities analyst, said Q2 earnings will be the primary driver for mega-cap stocks in the weeks ahead. "Q2 earnings will be the driver for mega-cap stocks," Ives, a managing director at Wedbush, said Wednesday on CNBC's "Closing Bell." Ives, who recently formed Yorkville Ives, a merchant bank in partnership with Yorkville Securities, also discussed SpaceX and how to value the private space company. He did not disclose a specific valuation figure during the interview. The new venture combines Ives' technology research expertise with Yorkville's capital markets capabilities. The bullish outlook comes as investors prepare for the second-quarter earnings season. Mega-cap technology companies — Apple Inc., Microsoft Corp., Nvidia Corp., Amazon.com Inc. and Alphabet Inc. — represent a significant portion of the S&P 500's market capitalization, making their earnings reports a key factor for broader index performance. Ives has been among the most vocal bulls on the technology sector, particularly on companies with artificial intelligence exposure. Ives' comments suggest AI-related spending and demand will continue to drive revenue growth for the largest US technology companies. The Q2 earnings season will test whether AI investments are translating into financial results for mega-cap firms. For investors, the upcoming reports will provide the clearest signal yet on whether the AI-driven rally in mega-cap stocks is supported by fundamentals. This article is for informational purposes only and does not constitute investment advice.
**Chip stocks are swinging more than 1% daily as early earnings season delivers conflicting signals on AI demand and inflation.** Semiconductor stocks are whipsawing investors as early earnings season delivers conflicting signals, with ASML's raised $51 billion outlook boosting chip equipment names while broader inflation data keeps rate-sensitive tech on edge. "Nvidia's next-generation AI platform is already in production with giant amounts still to come," Jensen Huang, chief executive officer of Nvidia, said, pushing back on speculation about delays to the Vera Rubin architecture. Huang also revealed that H200 shipments to China have only recently begun. The VanEck Semiconductor ETF rose more than 1% Wednesday, led by ASML's 3% gain after the Dutch chip-equipment giant raised its full-year revenue outlook to a range of $49.1 billion to $51.4 billion, well above the roughly $43.5 billion analysts expected. Intel and Lam Research each climbed more than 2%. The moves came as the producer price index unexpectedly fell 0.3% in June, extending relief from a cooler CPI reading the prior day. The volatility reflects a market struggling to price three simultaneous forces: AI infrastructure spending that shows no sign of slowing, a macro environment where inflation is cooling but remains above the Fed's 2% target, and geopolitical risks around chip exports to China. ASML is nearly sold out on EUV orders for 2027 and plans to boost production 30% annually for the next two years, signaling that foundries expect demand to remain elevated. Apple shares hovered near record highs as the company scouts chip acquisitions to strengthen its push into AI server silicon, according to The Information. The search suggests Apple wants more control over the hardware layer behind AI, potentially reducing reliance on Nvidia's GPUs — a development that could reshape competitive dynamics in the data center chip market. The Philadelphia Semiconductor Index's recent swings underscore a broader tension. While AI-related demand continues to drive orders for advanced packaging and high-bandwidth memory, the consumer electronics recovery remains uneven. ASML's order backlog, which extends into 2028, suggests foundries are betting heavily on future capacity needs, but any pullback in AI capital expenditure from major cloud providers could trigger a rapid repricing. For investors, the question is whether current valuations already reflect the AI boom or leave room for disappointment. Nvidia shares trade at elevated multiples relative to historical semiconductor averages, making them sensitive to any sign of demand softening. The next major test comes as more chip companies report quarterly results in the coming weeks, with data center revenue trends and forward guidance likely to determine whether the whiplash resolves into a clearer direction. This article is for informational purposes only and does not constitute investment advice.
**Bank of America's latest Global Fund Manager Survey shows 82% of managers calling "long global semiconductors" the most crowded trade in the survey's history, surpassing "Long Magnificent 7" at just 7%.** The semiconductor trade has become the most crowded in Bank of America's Global Fund Manager Survey history, with 82% of managers calling it the consensus bet — yet the four AI-chip stocks at its center carry sharply different valuations that demand stock-picking discipline. "Long global semiconductors has never been this crowded in our survey's history, well ahead of the Magnificent 7 at 7%," the BofA team led by Michael Hartnett wrote in the July report. The VanEck Semiconductor ETF (SMH) has surged 66.69% year to date, while the iShares Semiconductor ETF (SOXX) has climbed 88.78%. Within the group, NVIDIA trades at a forward P/E of 24x against 85.2% year-over-year revenue growth, while Broadcom sits at a forward 21x with AI semiconductor revenue guidance of $16 billion in Q3, up more than 200% year over year. AMD's trailing P/E of 185x and forward 79x reflect a 148.2% year-to-date run that has badly outrun its fundamentals. The crowding raises the risk of a sharp reversal if any of the group's earnings disappoint, but the underlying demand numbers still support the thesis. NVIDIA guided Q2 revenue to roughly $91 billion and authorized an $80 billion buyback. Broadcom delivered its eighth straight earnings-per-share beat. The question is not whether AI chip demand exists — it is which stocks have priced in too much of it. ## Valuation Dispersion Masks a Diverging Story The four stocks at the center of the trade could hardly be more different on valuation. NVIDIA's 32x trailing and 24x forward multiples are defensible against triple-digit revenue growth and an $80 billion buyback authorization on top of $38.5 billion remaining as of March. Broadcom's trailing 64x compresses to a forward 21x, reflecting the AI ramp still to come — its Q3 AI semiconductor revenue guidance of $16 billion represents more than 200% year-over-year growth alongside its eighth straight EPS beat. AMD is the stretched name. At 185x trailing earnings and a beta of 2.47, any growth wobble hits the multiple twice. Its data center revenue reached $5.78 billion in Q1, up 57% year over year, with the Meta 6-gigawatt Instinct GPU commitment anchoring the MI450 ramp. But the valuation leaves no room for error. Qualcomm is the outlier at a trailing 19x and forward 16x, with a 2.07% dividend yield. Its near-term setup is the softest: Q3 adjusted EPS guidance of $2.10 to $2.30 steps down sequentially. But hyperscaler custom-silicon shipments begin later in 2026, giving the stock a new growth leg the market has not yet priced in. ## Risk and Entry Points Diverge by Name Prediction markets signal asymmetric consolidation ahead for NVIDIA. Polymarket assigns only a 5.5% probability of the stock closing above $240 by month-end, versus 75% above $200. Reddit sentiment on NVDA has cooled to neutral, with retail investors flagging DeepSeek's in-house AI chip and SK Hynix's US market entry as fresh competitive worries. For income-oriented portfolios, Qualcomm's 15.88% one-month drawdown has already provided an entry the others have not offered. AMD carries the true valuation risk: at 185x trailing earnings, a single growth miss could compress the multiple sharply. NVIDIA and Broadcom still have the earnings power to grow into their multiples, making them the more defensible names on any weakness. For investors navigating the most crowded trade in history, the dispersion within the group matters more than the crowding itself. NVIDIA and Broadcom screen as the more defensible setups given their earnings visibility and reasonable forward multiples. Qualcomm's sell-off offers a value entry with a concrete 2026 catalyst in custom-silicon shipments. AMD's 185x trailing multiple warrants close monitoring before the risk-reward rebalances. The trade is crowded, but the fundamentals that drove it remain intact — the key is knowing which names can still deliver. This article is for informational purposes only and does not constitute investment advice.
**Jensen Huang staked Nvidia's product cycle credibility on Vera Rubin being "already in production" with "giant" volumes, directly refuting a research report that claimed manufacturing delays.** Nvidia's next-generation Vera Rubin AI accelerator system is already in production, Chief Executive Officer Jensen Huang said, directly refuting a research report that claimed manufacturing setbacks would delay the platform. "Vera Rubin is already in production. Giant amounts of production incoming," Huang told reporters Wednesday on the sidelines of a developer event in Tokyo, according to Bloomberg. The chief executive delivered a one-word dismissal of the SemiAnalysis findings before elaborating on production volumes. The July report from research firm SemiAnalysis — which has built a reputation for detailed Nvidia supply chain analysis — said the Vera Rubin AI server rack system faced delays due to difficulties manufacturing a specialized circuit board that connects electronic modules within the rack. The packaging complexity cited, a bottleneck that has historically constrained next-generation accelerator systems, would have pushed the platform into 2028, according to the report. The Vera Rubin cycle carries outsized importance for Nvidia investors. The company's Data Center revenue reached $75.2 billion in fiscal Q1, up 85% year over year, and Morgan Stanley recently raised its Rubin rack-system price assumption to about $49 billion per gigawatt — implying materially higher customer spending per deployment than the current Blackwell generation. **The Numbers Behind the Denial** Nvidia's Q1 FY2027 results set a high bar for Rubin to clear. Revenue hit $81.6 billion, up 85% year over year, with Data Center contributing $75.2 billion and Networking revenue rising 199%. Non-GAAP gross margin came in at 75%, and free cash flow reached $48.6 billion in the quarter. The company has $119 billion tied to supply-related commitments and is guiding for $91 billion in Q2 revenue, a forecast that excludes any China Data Center compute sales. Huang framed the buildout as generational: "The buildout of AI factories, the largest infrastructure expansion in human history, is accelerating at extraordinary speed," he said on the Q1 earnings call. Manufacturing partner Taiwan Semiconductor Manufacturing Co. (TSMC) is signaling similarly robust demand. June revenue jumped 68% year over year to NT$442.7 billion, and TSMC is adding three new advanced packaging facilities in Chiayi Science Park Phase II to relieve CoWoS (chip-on-wafer-on-substrate) bottlenecks that have constrained AI accelerator supply. **Japan's AI Pivot and the China Factor** The Tokyo setting for Huang's remarks was not incidental. Japan's Prime Minister Sanae Takaichi has unveiled an unprecedented $2.3 trillion spending plan aimed at encouraging private sector investment in domestic AI, and SoftBank Group has separately announced a $5.4 billion deal to acquire ABB Ltd.'s robotics unit. For Nvidia, whose physical AI and robotics platforms are increasingly central to its pitch beyond the data center, Japan represents a strategically important market. Huang also addressed the status of Nvidia's H200 chip shipments to China, an issue that has drawn significant investor attention since Washington eased export restrictions. The H200 was cleared for export by President Donald Trump in December, Bloomberg reported, marking a notable relaxation of controls designed to limit Beijing's access to advanced AI hardware. Until Blackwell-architecture chips arrived in late 2024, the H200 was the most powerful AI accelerator on the market, and its availability to Chinese buyers carries meaningful revenue implications for Nvidia. Nvidia shares trade at $211.54, with a trailing price-to-earnings ratio of 32 times and a forward multiple of 24 times. The consensus analyst target sits at $301.62, with 48 Buy and 10 Strong Buy ratings against just 2 Holds. If Huang's "giant" volumes materialize on Rubin at Morgan Stanley's higher average selling prices, current forward estimates likely understate fiscal 2028 earnings power. The competitive stakes are equally high: any credible delay in Vera Rubin's ramp would have sharpened pressure from Advanced Micro Devices Inc.'s advancing MI350 and MI400 roadmap, making the chief executive's on-record rebuttal particularly consequential for investors who have priced Nvidia's product cycle into its elevated valuation. This article is for informational purposes only and does not constitute investment advice.
**OpenAI's first branded hardware is a $230 shortcut keyboard for its Codex coding platform, not the Jony Ive-designed smart speaker expected next year.** OpenAI entered the hardware market with a $230 mini-keyboard called Codex Micro, a limited-edition device that lets developers monitor and manage multiple AI coding agents through color-coded keys and tactile controls. "The frosted keys provide a live view of your Codex threads, using different colors to indicate whether a task is complete, needs feedback, or has encountered an error," Mike Di Genova, cofounder of keyboard maker Work Louder, said in a video explaining the device. The device closely resembles Work Louder's Creator Micro 2 pad, featuring 13 mechanical switches, a joystick, dial, and touch sensor. Six translucent keys at the top cycle through colors — white for idle, blue for thinking, green for complete, amber for feedback needed, and red for errors — giving users at-a-glance status of up to six Codex threads. All controls are configurable through the ChatGPT desktop app, and the device ships with 32 additional keycaps featuring Codex icons. The joystick can start common workflows, while the dial adjusts the agent's reasoning level. The launch shows OpenAI's deepening commitment to developer tools as Codex and ChatGPT Work have reached 8 million active users, according to Thibault Sottiaux, Codex's engineering lead. The company merged Codex into the ChatGPT desktop app last week, and the Micro keyboard gives power users a dedicated physical interface for a workflow that increasingly runs in the background. For developers running multiple agents simultaneously — a practice that has led some to keep laptops half-open in public to monitor their threads — the color-coded keys eliminate the need to constantly check screens. The Codex Micro is separate from OpenAI's primary hardware project with former Apple design chief Jony Ive, which Bloomberg reported will be a portable, screenless smart speaker designed as an AI companion for the home. That device, expected to launch in 2027, faces headwinds after Apple sued OpenAI last week, accusing it of stealing trade secrets related to hardware manufacturing. OpenAI has denied the allegations, saying it has "no interest in other companies' trade secrets." OpenAI acquired Ive's design firm LoveFrom for $6.5 billion last year, and its hardware division is working on about five products, according to reports. The Codex Micro, by contrast, is a far simpler bet — a rebadged version of existing Work Louder hardware with OpenAI branding and Codex-specific software integration. Orders are open "while supplies last" on Supply Co, with shipping expected shortly after purchase. OpenAI did not disclose how many units are available. For investors, the Micro keyboard is a low-cost experiment in hardware-software bundling. OpenAI's $230 device creates a physical moat around Codex usage — developers who buy the keyboard are likelier to stay within the platform. But the limited-run nature suggests OpenAI is testing demand rather than committing to a product line. Microsoft, which competes with OpenAI through its GitHub Copilot coding assistant, has not announced companion hardware. Nvidia, whose GPUs power the AI models behind both platforms, stands to benefit regardless of which coding assistant wins developer mindshare. This article is for informational purposes only and does not constitute investment advice.
The first wave of Q2 2026 earnings cleared a lowered bar, and now the market faces its real test: technology. Non-tech sectors — healthcare, consumer staples, financials — delivered results that met or exceeded reduced expectations, supporting the S&P 500 even as the Nasdaq Composite fell 0.66% to 25,949.60. The Dow Jones Industrial Average hit an all-time high of 53,289.30 before reversing to close at 52,879.27, down 0.33%. "The rotation into defensive sectors tells you the market is positioning for tech to disappoint," said Sarah Lin, equity analyst at Edgen. "The non-tech results were good enough, but the bar for semiconductors and AI-related names has moved well past what even a blowout quarter can clear." The Philadelphia Semiconductor Index dropped 5.5% to its lowest level in four weeks. Intel Corp. fell 8.2%, Micron Technology Inc. lost 7.3%, and KLA Corp., Marvell Technology Inc., Broadcom Inc. and Advanced Micro Devices Inc. all traded sharply lower. The VanEck Semiconductor ETF lost more than 5%. Nvidia Corp. slipped 1.8% after reports that Chinese AI startup DeepSeek is developing its own chip. Samsung Electronics Co. reported a 19-fold increase in operating profit for the second quarter, yet its stock sold off nearly 7% in Seoul. The reaction underscored how expectations have outpaced even exceptional results. South Korea's Kospi index gave back nearly 5% on the session. The selling pressure carried into U.S. markets, where the S&P 500 held at 7,516.76, down 0.27%, supported by gains in healthcare and consumer staples. Eli Lilly & Co. rose about 3%. Walmart Inc. advanced after announcing price cuts on products including ground beef and Coca-Cola. JPMorgan Chase & Co. and Microsoft Corp. also attracted buyers. Money leaving chips is rotating into sectors where the earnings bar is lower. Fiserv Inc. climbed 3.5% after reports the payments company held discussions with JPMorgan, Bank of America Corp. and other large U.S. banks about selling its debit card payments infrastructure business. In India, Tata Consultancy Services Ltd. met analysts' net profit estimates, supported by cost-cutting that offset weakness in its core IT services business. HCL Technologies Ltd., Wipro Ltd. and Tech Mahindra Ltd. are set to report this week. Accenture Plc earlier projected weaker-than-expected quarterly revenue, reinforcing demand concerns. Taiwan Semiconductor Manufacturing Co. is expected to release delayed June sales figures after Typhoon Bavi disrupted the schedule, offering a key indicator of global AI-driven demand. SK Hynix Inc. begins trading on the Nasdaq later this week, testing whether institutional money returns to chip stocks at current prices. The rotation into healthcare, staples and financials has been building for several sessions. The S&P 500 is sitting on a short-term retracement zone at 7,474.57 to 7,429.38, with the 50-day moving average at 7,410.62. The Nasdaq is pressing its 50-day moving average at 25,969.61. A break below those levels would signal the selling is broadening beyond tech. The guidance raise from non-tech companies signals management teams see stable demand in their end markets. But tech earnings will determine whether this remains a sector rotation or turns into a broader market correction. Investors will watch the June FOMC minutes on Wednesday for Chair Kevin Warsh's latest policy stance, and the SK Hynix listing later this week for a read on institutional appetite for semiconductor exposure. This article is for informational purposes only and does not constitute investment advice.
Morgan Stanley raised its bottom-up cost estimates for next-generation AI clusters, with Nvidia's Vera Rubin-based systems now priced at $49 billion per gigawatt of computing capacity — a nearly 20% increase from prior forecasts that only a handful of the world's most cash-rich technology companies can absorb. "The cost of building frontier AI infrastructure is rising faster than many investors expected, and it's concentrating the market among a small group of hyperscalers," said Joseph Moore, an analyst at Morgan Stanley, in a research note published Tuesday. The investment bank's updated estimates show Nvidia's GB200 systems cost about $35 billion per GW, up 16% from prior estimates, while GB300 clusters rose to $39 billion per GW. Those figures align closely with Nvidia's own guidance of $50 billion to $60 billion per GW for Rubin-era installations. The costs encompass not just graphics processors but networking equipment, storage, liquid cooling systems, and power delivery for facilities consuming as much electricity as 700,000 to 1 million US homes. The rising price tag does not weaken Nvidia's outlook — it may strengthen it. Only companies generating hundreds of billions in annual operating cash flow, such as Microsoft, Amazon, Alphabet, and Meta Platforms, can comfortably finance projects at this scale. Smaller AI companies will increasingly lease capacity from cloud providers or specialists like CoreWeave rather than building their own campuses, shifting even more demand toward the largest operators while reinforcing Nvidia's dominant ecosystem of GPUs, networking hardware, and software. **The $50 Billion Barrier to Entry** OpenAI's Stargate initiative, backed by SoftBank and Oracle, plans to invest $500 billion through 2029 to build up to 10 GW of AI infrastructure. Meta is developing its Hyperion campus with plans to expand from 2 GW to 5 GW, while Microsoft and Google continue building multi-gigawatt data center campuses across the US. These projects require capital commitments that few companies outside the top-tier hyperscalers can match. Morgan Stanley also noted that power availability — not financing — is increasingly becoming the biggest bottleneck. Utilities face multi-year delays adding new generation and transmission capacity, stretching construction timelines and increasing project costs. McKinsey estimates cumulative AI infrastructure spending could reach trillions of dollars by 2030, while Epoch AI projects multiple frontier AI clusters exceeding 1 GW this year alone. **What Rising Costs Mean for Investors** For Nvidia, more expensive AI factories translate into higher revenue per deployment because its chips, networking products, and software remain at the center of those installations. Suppliers of high-bandwidth memory, power management systems, and liquid cooling equipment also stand to benefit as clusters become larger and more complex. Nvidia shares, trading at roughly 30x forward earnings, have already priced in much of this infrastructure buildout. The question for investors is whether the market has fully accounted for the concentration risk — that only a handful of companies can sustain this level of spending, and any pullback from Microsoft, Amazon, or Meta could ripple through the entire AI supply chain. Morgan Stanley's revised estimates suggest the AI buildout is not slowing down, but the cost of entry is creating a competitive moat that favors the biggest players and the chipmaker at the center of it all. This article is for informational purposes only and does not constitute investment advice.
Nvidia's Vera Rubin platform has entered production, Chief Executive Officer Jensen Huang said July 15, extending the company's lead as rivals Advanced Micro Devices Inc. and Broadcom Inc. invest billions to challenge its AI chip dominance. "Vera Rubin is progressing well and has entered production," Huang said in a statement, without disclosing a specific timeline for customer shipments. The Vera Rubin architecture succeeds Nvidia's Blackwell platform, which began ramping in late 2024. Super Micro Computer Inc. introduced a blueprint based on the Vera Rubin NVL4 platform at the ISC 2026 conference in June, with each Scalable Unit housing as many as 1,152 Rubin graphics processing units and 576 Vera central processing units, using liquid cooling and Nvidia's Quantum-X800 InfiniBand networking. The platform is built on TSMC's advanced process node and uses next-generation high-bandwidth memory, though Nvidia has not disclosed the specific node or memory configuration. Nvidia's Data Center revenue surged 92% year over year to $75.2 billion in the fiscal first quarter ended April, while total revenue hit a record $81.6 billion — an 85% increase. The company guided for second-quarter revenue of about $91 billion, signaling continued demand for its AI infrastructure. The Zacks consensus estimate for fiscal 2027 revenue stands at $385.5 billion, implying 78.5% annual growth. Despite reports of a slight delay in the Rubin rollout, one analyst still expects 62% upside for Nvidia shares, citing the company's widening competitive moat through its integrated hardware-software ecosystem. Nvidia has expanded partnerships with Google Cloud to deploy Vera Rubin-powered AI instances, with Marvell Technology Inc. through NVLink Fusion for custom AI infrastructure, and with Coherent Corp., Corning Inc. and Lumentum Holdings Inc. to improve optical networking for next-generation data centers. The Vera Rubin production milestone comes as Nvidia's rivals accelerate their own AI chip efforts. AMD's Data Center segment revenue rose 57% year over year to $5.78 billion in its first quarter, driven by demand for its Instinct GPUs and EPYC processors, while the company has strengthened its open-source ROCm software platform to attract developers. Broadcom has also been investing aggressively in custom AI accelerators for hyperscale customers. Nvidia's software ecosystem — including open-source platforms Dynamo, Agent Toolkit and Nemotron — encourages developers to build AI applications on Nvidia hardware, creating switching costs that make it harder for customers to migrate to competing platforms. The company's broad partner network and integrated chip-to-software stack create a structural advantage that rivals have yet to replicate at scale. Nvidia shares trade at about 35 times forward earnings. The production ramp of Vera Rubin, combined with the company's expanding software moat and partner ecosystem, suggests the market has not fully priced in the platform's revenue contribution for fiscal 2028, according to analysts tracking the stock. This article is for informational purposes only and does not constitute investment advice.
**The Trump administration elevated the UAE's trade classification to the same tier as European allies, unlocking unrestricted access to Nvidia's most advanced AI chips after the Gulf state fought alongside the US against Iran.** The Commerce Department on Friday moved the United Arab Emirates from a restricted group that included China and Yemen to a category shared with European nations, South Korea and India, according to a statement reviewed by Edgen. The change allows G42, the UAE's main artificial intelligence company controlled by national-security adviser Sheikh Tahnoon bin Zayed Al Nahyan, to buy Nvidia chips freely for at least nine months and removes export license requirements for Microsoft and OpenAI data centers planned in the country. "The UAE has been a great partner with Iran, but that doesn't necessarily mean they've demonstrated the capability to keep a data center secure," said Michael Sobolik, a senior fellow at the Hudson Institute, a conservative think tank. The decision caps a yearslong push by the UAE to obtain American technology to diversify its economy, a campaign that accelerated after the Gulf state bore the brunt of Iran's retaliatory drone strikes. Emirati forces carried out dozens of airstrikes against Iran, intercepted hundreds of missiles and kept oil moving through the Strait of Hormuz, which handles about 21 percent of global seaborne crude trade. The shift could be worth billions of dollars in chip purchases, industry analysts said. The greater chip access is attracting scrutiny in Congress because of financial ties between Sheikh Tahnoon and President Trump. Four days before Trump's second inauguration, Tahnoon struck a deal to invest $500 million for a 49 percent stake in World Liberty Financial, a cryptocurrency company started by the Trump family. The president's financial disclosures released last month reported $263 million from the sale of that stake, one of the largest chunks of his 2025 income. The UAE also pledged $1.4 trillion in US investment. "It smells like it could be an illegal pay-to-play scheme," Representative Sydney Kamlager-Dove, a California Democrat, said Tuesday at a House committee hearing. She questioned Jeffrey Kessler, a Commerce Department official whose unit oversees export controls, about whether he discussed chips going to the UAE with Trump family members or World Liberty Financial executives. Kessler said he did not and defended the move as "one of the most significant achievements of the administration." **Military support unlocks technology access** The UAE initially lobbied the US against starting a war with Iran, then pivoted to an aggressive stance after Iran's retaliatory attacks hit Emirati territory. The country coordinated strikes with the US and Israel, demonstrating to the White House that it was a reliable ally, an American official said. The UAE in 2020 signed the Abraham Accords, normalizing ties with Israel, and its decision to fight alongside the US against Iran marked a further deepening of the security relationship. Emirati officials led by Sheikh Tahnoon had lobbied for chip access going back to the Biden administration. After the Iran war began, they approached the White House directly, pointing to India's elevation to Major Defense Partner in 2016, which unlocked expanded trade benefits. This time, the reception was more favorable, people familiar with the matter said. The Commerce Department cited "the UAE's commitment to preventing the diversion and misuse of sensitive US technology" in its statement on the change. UAE Ambassador to the US Yousef Al Otaiba said the move "advances decades of deep and dependable UAE-US cooperation." **What's at stake for markets** The decision opens a multi-billion dollar purchasing channel for Nvidia's most advanced AI processors, benefiting the chipmaker as well as Microsoft and OpenAI, whose UAE data center plans were previously held up by months-long export license delays. The shift signals a new geopolitical framework where AI chip access is used as a diplomatic and military reward, potentially pressuring competitors such as AMD and Intel to seek similar arrangements for their customers. The controversy over Trump family financial ties introduces political risk that could lead to future restrictions or investigations. For the near term, however, the removal of regulatory hurdles is a significant positive catalyst for the involved US technology firms and the UAE's AI ecosystem. This article is for informational purposes only and does not constitute investment advice.
**Jim Cramer pushed back against dot-com crash comparisons, arguing the S&P 500's 20 times forward earnings is far below the 25 times multiple that preceded the 2000 collapse.** The S&P 500 trades at 20 times forward earnings, well below the 25 times multiple that preceded the dot-com crash, CNBC's Jim Cramer said Tuesday, dismissing bubble fears tied to AI-driven gains. "There are always outliers. There is some froth, but the froth does not represent what we trade. What we own," Cramer, host of "Mad Money," said. Cramer cited cooler-than-expected CPI data, strong corporate earnings from Bank of America, Goldman Sachs and JPMorgan, and lower interest rates as evidence the market is not overheated. Goldman Sachs trades at 12 to 18 times forward earnings despite reporting substantial earnings and revenue beats Tuesday, he said. SK Hynix trades at roughly four times 2027 earnings estimates, while Micron is at six times. "You don't get a dotcom crash scenario without a series of tremendous rate hikes and we simply aren't there yet," Cramer said, adding that new Fed Chair Kevin Warsh did not sound like he would tighten if CPI stays at current levels. Cramer's defense comes as stocks have surged to new highs over the past year, with enthusiasm surrounding artificial intelligence fueling massive gains in semiconductor companies. Memory-chip makers Micron and Sandisk have jumped more than 243% and 644% this year, respectively, stoking comparisons to the dot-com boom of the late 1990s. The latest consumer price index report came in cooler than expected Tuesday, easing concerns that the Federal Reserve would soon need to raise interest rates. Cramer's Charitable Trust, the portfolio run by CNBC's Investing Club, owns shares of Goldman Sachs and Nvidia. "What typifies this market is the inexpensive nature of so many big-cap stocks," Cramer said. Nvidia, the dominant player in artificial intelligence chips, trades at a similar multiple to the broader market despite its market-leading position, Cramer argued. The stock closed at $203.53 on July 13 with a market capitalization near $4.93 trillion, according to FactSet data. Nvidia reported Q1 FY2027 revenue of $81.61 billion, up 85.2% year over year, and guided Q2 revenue to $91 billion. Heading into 2000, the S&P 500 traded at more than 25 times forward earnings, compared with about 20 times today, FactSet data shows. "That's a big difference, and while 20 isn't exactly cheap, it's certainly not expensive like 2000," Cramer said. This article is for informational purposes only and does not constitute investment advice.
Nvidia Corp. shares climbed 10% from their June low to the highest since June 22, forming a falling wedge pattern that technical analysts say could drive a rally toward the $235 all-time high as the chipmaker's valuation reaches its cheapest levels in years. "Nvidia's price-to-earnings growth ratio is at decade lows, making the stock a bargain despite its multi-year rally," said analysts at Zacks Investment Research. A discounted cash flow analysis by Simply Wall St. places the stock's fair value at $220, implying about 7.7% upside from current levels. The chipmaker's revenue surged 85% to $81.6 billion in its most recent fiscal year as hyperscalers including Microsoft Corp. and Amazon.com Inc. continued pouring capital into AI infrastructure. Analysts expect revenue to have climbed 96.2% in the most recent quarter to $91.75 billion, with annual revenue on track to reach $400 billion. Nvidia has also expanded into the CPU market, projecting that business will exceed $20 billion this year. The company's forward P/E of 22 is roughly half its five-year average of 43, while the PEG ratio of 0.50 is less than a third of the five-year average of 1.46. Nvidia boosted its share repurchase authorization by $80 billion in its last earnings report, reducing outstanding shares to 24.2 billion from 24.3 billion in 2023. The buyback program, combined with the cheap valuation, could tighten the float and provide additional support for the stock price. The bullish case faces risks from rising client competition. OpenAI has developed its own chip with Broadcom Inc., Alphabet Inc.'s Google is expanding production of its tensor processing units, and both Microsoft and Amazon are building custom silicon. If hyperscalers shift procurement from Nvidia's GPUs to in-house alternatives, the company's growth rate could decelerate even as revenue continues rising. Data center projects worth $64 billion have been canceled, and New York became the first state to impose a moratorium on new data centers, raising questions about the sustainability of AI infrastructure buildout. The stock's recovery comes as the broader market digests the impact of recent geopolitical events and trade policy. The S&P 500 has followed a pattern similar to 2025, correcting early in the year before staging a V-shaped recovery, according to Zacks Investment Research. **Technical Setup Points Higher** The stock found support at its 200-day exponential moving average and has broken above the upper boundary of a falling wedge pattern, a formation that typically resolves upward. If the pattern plays out, the next target is the all-time high of $235, with a potential extension to $300. Nvidia shares have underperformed the Nasdaq 100 this year, rising about 10% versus the index's 15.7% gain, which has contributed to the compression in valuation multiples. The stock is trading inside the Ichimoku cloud indicator, a technical measure that often precedes trend changes. **Insider Buying Strengthens the Bullish Case** Tech stock insiders have bought more shares over the past six months than at any point in history, according to Zacks Investment Research. The buying spree suggests executives believe their companies are undervalued, adding a fundamental catalyst to the technical setup. The broader tech sector's forward P/E is also below its 10-year average, indicating that the valuation compression is not unique to Nvidia but reflects a broader market trend. Other AI-related companies such as SanDisk Corp. and Marvell Technology Inc. are also reporting record profits, reinforcing the fundamental strength of the semiconductor cycle. **Competition Threatens the Growth Narrative** Nvidia's dominance in AI training and inference chips faces its most credible challenge yet as major customers develop their own silicon. OpenAI's chip, built with Broadcom, targets inference workloads where Nvidia currently commands premium pricing. Google's sixth-generation TPU is already deployed internally, and Amazon's Trainium chip is gaining traction with cloud customers. The risk is not that Nvidia loses all its business but that its pricing power erodes as alternatives emerge, compressing margins even if revenue continues growing. Micron Technology Inc. is expected to generate more profit this year than it produced over the previous two decades combined, showing that the AI chip boom is broadening beyond Nvidia. This article is for informational purposes only and does not constitute investment advice.
**A U.S. Commerce Department official told Congress that new regulatory action on AI and semiconductors is imminent, threatening to deepen export controls on advanced technology.** A U.S. Commerce Department official told lawmakers Tuesday that regulatory action on artificial intelligence and semiconductors is imminent, threatening to tighten export controls that have already reshaped the global chip supply chain. "Action regulating artificial intelligence and semiconductors is coming," the official, who oversees export controls at the Commerce Department's Bureau of Industry and Security, said at a congressional hearing. The official did not specify the scope or timing of the new measures. The announcement marks the potential third major expansion of U.S. chip export restrictions since October 2022, when the Biden administration first barred shipments of advanced semiconductors and chipmaking equipment to China. The October 2023 rules broadened those curbs to cover a wider range of AI chips and tightened licensing requirements for exports to more than 40 countries. Semiconductor stocks have historically sold off 3 percent to 8 percent on similar regulatory signals, according to market data. The new rules could further restrict revenue growth for U.S. chipmakers including Nvidia Corp., Advanced Micro Devices Inc. and Intel Corp., which together derive roughly 25 percent of sales from China and other markets subject to U.S. export controls. The Commerce Department's actions come as the $52.7 billion CHIPS Act, signed in 2022, continues to fund domestic semiconductor fabrication plants aimed at reducing reliance on Asian supply chains. The hearing follows a series of escalating U.S. measures targeting China's access to advanced computing technology. The October 2022 rules restricted exports of Nvidia's A100 and H100 chips, while the October 2023 update added the company's A800, H800 and L40S products — chips specifically designed to comply with the earlier restrictions. Each round has prompted China to accelerate domestic chip development, with companies like Huawei Technologies Co. and startups such as Biren Technology racing to close the gap. The Commerce Department's Bureau of Industry and Security has also added more than 150 Chinese entities to the Entity List since 2022, restricting their access to U.S.-origin technology. The latest regulatory push suggests the agency is preparing to close loopholes that Chinese firms have exploited to obtain restricted chips through third countries. **Market Impact and Forward Outlook** The potential for tighter rules comes at a sensitive moment for the semiconductor industry. The Philadelphia Stock Exchange Semiconductor Index has gained 22 percent over the past 12 months, driven by AI-related demand, but faces headwinds from escalating U.S.-China technology tensions and potential retaliatory measures from Beijing. China's Commerce Ministry has previously threatened to restrict exports of gallium, germanium and antimony — critical minerals used in chip manufacturing — in response to U.S. controls. The new regulatory push also aligns with broader workforce development efforts. The U.S. Department of Labor on July 7 awarded nearly $162 million through five cooperative agreements to expand Registered Apprenticeships in sectors including artificial intelligence, semiconductors and nuclear energy, according to a department statement. The funding targets what Acting Labor Secretary Keith Sonderling called "the industries that will define America's future economic competitiveness." This article is for informational purposes only and does not constitute investment advice.