404K SEMI-AI Tech Morning Brief 2026-07-06 — Memory Price Increases, AI Power Constraints, Catch-Up in Passive Components
目录
After-Market Summary
Top 10 U.S. Stocks by Trading Value
Top U.S. Stock Gainers
Top U.S. Stock Decliners
AI/Semiconductor Full Value Chain
AI Models/Applications and Capex
CSP/Cloud Capex
AI Cloud/Data-Center Operators
GPU/CPU/ASIC
HBM/DRAM/NAND/SSD/HDD
Foundry
Semiconductor Equipment/Testing
MLCC/Passive Components and ABF
Power Semiconductors/Thermal and Power
Optical Communications / Optics Chain
Robotics / Autonomous Driving and Space Satellites
Internet / Platforms
Software / SaaS
Consumer Electronics / Smart Vehicles
Investment Bank Target Price Changes Over the Past 12 Hours
Huang’s Selected Portfolio
The AI infrastructure trade is entering a supply-chain gap-finding phase. U.S. tech and semiconductors pulled back in the latest closing session, but capital has not left the AI theme. Instead, it is spreading from GPUs into memory, MLCCs, ABF, power, electricity, silicon photonics, and data center operators.
After-Market Summary
The latest U.S. equity closing session was 2026-07-02, and the technology theme sold off first. The Nasdaq 100 fell 1.73%, the technology ETF fell 2.71%, the semiconductor ETF fell 4.54%, and the equal-weight semiconductor reference fell 5.57%. The equal-weight S&P; rose 0.70% and the Dow rose 1.05%, showing that the pullback was concentrated in mega-cap technology and the semiconductor chain.
By style, software was more resilient than hardware. The software ETF rose 0.25%, cloud computing fell 1.06%, cybersecurity fell 0.48%, while AI and big data fell 2.80%. In 20-day relative strength, software and cloud remain below prior highs, but 5-day relative strength has started to recover. Semiconductor 5-day relative strength ranked near the back, as crowded short-term positioning was amplified by profit-taking in memory and equipment chains.
At the single-stock level, Apple rose 4.86% and Microsoft rose 1.85%, while Nvidia fell 1.62%, AMD fell 4.42%, Intel fell 12.70%, Micron fell 5.52%, and SanDisk fell 13.58%. The market signal is straightforward: the AI demand narrative remains intact, but the market is first cutting valuation and crowding, then looking again for the segments that can truly raise prices, secure power, and deliver.
Top 10 U.S. Stocks by Trading Value
Top U.S. Stock Gainers
Top U.S. Stock Decliners
AI/Semiconductor Full Value Chain
AI Models/Applications and Capex
AI Application Adoption
1) Enterprise AI value validation is beginning to shift from consumer chat tools to mission-critical workflows. The materials note that the top 20% of early AI-adopting enterprises can already quantify value at the organizational level, especially in security, internal processes, and dedicated model services.
2) The investment implication is that frontier model labs’ revenue will not only come from general-purpose APIs. Enterprise security and private models may become more stable budget items, but renewal rates and real procurement scale remain unproven.
"top 20% of early adopting enterprises；value is quantified at scale across the organization；mission critical functions"
Anthropic
1) Anthropic is seeking 1.4 GW of data-center capacity in Australia. Reported build-out scale varies between US$15 billion and US$21.6 billion, with roughly 1 GW targeted to come online by end-2027, potentially split into 4-5 contracts.
2) This shows model companies are competing not for a single GPU, but for power, sites, and delivery timing. The key difference among CDC, AirTrunk, NextDC, IREN, and other counterparties is who can deliver power on schedule.
OpenAI/Anthropic Duopoly
1) Model-layer concentration continues to rise. The materials state that OpenAI and Anthropic together control 88% of enterprise LLM spending. Anthropic’s ARR exceeded US$45 billion in May 2026, while OpenAI’s ARR was about US$24 billion-US$33 billion in the same period.
2) The risk is that application companies hand workflows and product roadmaps to the same group of frontier models. The upstream model layer gains pricing power, while downstream product differentiation weakens.
"Anthropic and OpenAI now control 88% of enterprise LLM spend"
CSP/Cloud Capex
Google
1) Google’s AI logic is to run Gemini on in-house TPUs and reduce cost per token. The materials state that its profit could rise from about US$170 billion to US$247 billion by 2028. The key question is who can control unit inference cost when compute is scarce.
2) This is positive for TPUs, HBM, advanced packaging, and the data-center chain, but the risk is that cloud revenue growth and ad monetization must keep pace with capex.
Meta
1) Meta is repeatedly cited as counterevidence that AI demand has not disappeared. On one side, the market worries it may sell excess compute capacity. On the other, there are claims of up to 1.6 GW of AI compute contracts and stronger long-term demand for HBM, LPDDR5, and eSSD.
2) For storage and data-center companies, Meta’s real orders matter more than headlines. The next things to watch are capex guidance and long-term supplier agreements.
Microsoft
1) Microsoft’s latest trading logic centers on its core software franchise, returns on AI capex, and pricing mechanisms. The materials state that Microsoft’s “software business is safe,” AI capex will turn ROI-positive, and the company is 15% undervalued.
2) This is not a formal rating or target price, but it shows the market is shifting from “Microsoft is spending too much” to “can Copilot, Azure, and software bundling raise revenue per customer?”
"Its software business is safe. AI capex will turn ROI positive. Changes in software pricing will drive growth."
Amazon
1) Amazon benefits from AWS while also designing in-house chips at the device end. Its hardware chief said some devices will move to end-to-end chip design, while the company will still procure from external suppliers such as Qualcomm.
2) If edge AI enters hardware such as Echo and Fire TV, Amazon’s chip requirements will expand from cost control to model experience and local inference.
Aggregate Cloud Capex
1) AI capex from Google, Amazon, Meta, Microsoft, and Oracle is expected to exceed US$800 billion in 2026 and rise to US$1.1 trillion in 2027, equal to roughly 3.2% of US GDP.
2) The investment implication is direct: GPUs are only the first layer. Memory, servers, power, lease commitments, cooling, and interconnects are all absorbing this budget.
AI Cloud/Data-Center Operators
Nebius
1) Nebius is viewed as one of the few neoclouds with power, customers, and a software layer at the same time. The materials show Q1 2026 revenue of US$399 million, up 684% YoY, year-end ARR guidance of US$7 billion-US$9 billion, contracted power of 3.5 GW, and a year-end target above 4 GW.
2) The company has more than US$46 billion of contracts with Meta and Microsoft extending to 2031. The risk is that the capital-intensive model makes financing capacity and delivery cadence central to valuation.
"Most neoclouds have none of those three things simultaneously but Nebius has all of them"
CoreWeave
1) CoreWeave has pulled back more than 50% from its high, but backlog remains near US$100 billion and revenue is still growing more than 100% YoY.
2) The company represents the debate around neoclouds: contracts and revenue are very strong, but debt, losses, and hyperscalers building their own clouds will compress valuation tolerance.
IREN
1) The debate around IREN is “megawatt assets” versus “platform capability.” The materials state that it will approach 1 GW of operating or completed capacity by end-2026, including 160 MW in Canada and 750 MW at Childress. Sweetwater 1, a single 1.4 GW site, was energized on May 28, 2026.
2) Nvidia has announced an initial 60 MW deployment, but an Anthropic partnership remains unconfirmed speculation. What the share price needs to validate is whether IREN can convert power assets into contracted AI cloud revenue.
TeraWulf, Cipher Mining, Applied Digital, Galaxy Digital
1) These companies are all on the AI data-center operator list, but the strength of hard evidence varies in this round. The investable narrative should include data centers, power capacity, AI compute hosting, financing, and customer contracts; a stock should not be included merely because it appears.
2) Future tracking should focus on power interconnection, customer credit quality, GPU financing, and take-or-pay contracts, not one-day share-price moves.
GPU/CPU/ASIC
Nvidia
1) Nvidia remains the largest beneficiary of AI factory budgets. The materials state that a 1 GW AI factory based on Nvidia architecture could cost close to US$100 billion, with about half flowing to Nvidia chips, systems, and software.
2) The risk is also starting to shift from demand to architecture execution: Kyber NVL144 has been delayed by more than 12 months to 2028, the back-to-back NVL72x2 solution has been cancelled, and Rubin Ultra’s scale-up world size is constrained.
"1GW AI factory... could now cost nearly 100 billion dollars"
Intel
1) Intel 18A yield is still in the early ramp phase, but company commentary indicates improvement is ahead of internal targets. Management has mentioned monthly yield improvement of 7% or 8%. 14A is planned for risk production in 2028 and mass production in 2029, with the 0.9 PDK version to be released in October.
2) The business question for this line is whether Intel can lock in major fabless customers over the next 18 months. If not, the advanced foundry story will continue to be overshadowed by TSMC A14 and Samsung Electronics SF2Z.
Broadcom
1) Broadcom’s latest quarterly AI revenue grew 106% YoY to US$8.4 billion, driven by custom accelerators and AI networking chips for Google, Meta, and Anthropic.
2) At the same time, the market questions whether the company is “chips only” and lacks a full AI system-integration narrative. Future valuation depends on ASIC customer expansion and networking-chip volume ramp.
AMD
1) AMD’s opportunity comes from small-scale deployment feedback for MI355x and the potential for MI500X to compete in the Rubin Ultra scale-up window. The materials show MI355x preregistration has reached 6 nodes and 48 GPUs, with a US$100 threshold per preregistration.
2) This is not a formal order, but it shows independent compute deployers are beginning to queue for AMD GPUs. The next validation points are MI450/MI500 mass production, customer financing, and software-stack stability.
HBM/DRAM/NAND/SSD/HDD
Micron
1) Micron has started a JPY1.5 trillion, or about US$9.3 billion, AI memory expansion in Hiroshima to produce HBM, with shipments expected in summer 2028. The Japanese government will provide support of up to JPY500 billion, with total support of roughly JPY775 billion.
2) This has limited impact on near-term supply, but it reinforces Micron’s medium- to long-term capacity position in HBM. The near-term share-price pullback is more about crowding and profit-taking in memory stocks at elevated levels.
"The new facility will produce high-bandwidth memory for AI processors"
Samsung Electronics, SK Hynix
1) UBS raised its DDR contract-price forecast to +32% QoQ in 3Q26 and +18% QoQ in 4Q26, and its NAND forecast to +30% QoQ in 3Q26 and +12% QoQ in 4Q26. The report expects DRAM to remain in shortage at least through 2Q28.
2) SK Hynix is also rumored to be planning a Nasdaq listing, with the logic of using the US equity market to reprice HBM, DRAM, and flash demand. However, leveraged single-stock ETFs in Korea amplify volatility, so not all short-term price action should be treated as fundamentals.
SanDisk, Kioxia
1) BofA believes Korea’s KRW800 trillion memory cluster will not generate effective output quickly, while NAND shortages and enterprise SSD demand remain strong. SanDisk’s enterprise SSD revenue grew 7x YoY, and the company is developing high-bandwidth flash, expected to be released later in 2026 to 2027.
2) The core of Kioxia and SanDisk is the NAND pricing cycle and eSSD supply-demand, not traditional consumer flash. The risk is whether downstream procurement can continue to absorb compounded price increases.
China Memory Chain
1) Lenovo has begun equipping global ThinkBook 14 G9 configurations with YMTC SSDs. CXMT is testing a bonded DRAM pilot line in Hefei, attempting to use DUV multi-patterning to work around EUV.
2) Neither development is yet large-scale mass production or order realization, but they show China’s memory substitution is advancing simultaneously from PC SSDs and DRAM process routes.
Foundry
TSMC
1) TSMC accounts for about 70% of global advanced foundry share, with Nvidia and Apple alone contributing roughly 40% of revenue. At 2025 IEEE ECTC, the company introduced SoW-X, pointing to wafer-level system integration to address reticle-size, I/O bandwidth, and thermal-management bottlenecks.
2) Advanced process nodes and advanced packaging are merging into a system capability. TSMC’s risks are not demand, but geopolitics, energy, and customer concentration.
"SoW-X redefines how logic and memory interact at scale"
Semiconductor Equipment/Testing
Equipment Chain
1) Samsung Electronics and SK Hynix are evaluating alternatives to Mattson’s PR strip and RTP equipment. Supply-chain diversification benefits Applied Materials, ASML, Lam Research, Tokyo Electron, KLA, and Korean equipment vendors.
2) SEAJ raised its FY2026 Japan semiconductor equipment sales outlook to JPY6.55 trillion, with FY2027 at JPY7.4 trillion and FY2028 at JPY7.77 trillion. The equipment cycle is supported by advanced logic and DRAM expansion.
FormFactor, Teradyne, Advantest
1) FormFactor’s Q1 2026 revenue was US$226 million, up 32% YoY, with non-GAAP EPS of US$0.56, above expectations of US$0.44. Through Keystone Photonics, it is partnering with Advantest to enter silicon photonics wafer-level testing.
2) Rising complexity in CPO, silicon photonics, and high-speed electro-optical testing will expand equipment value from traditional electrical testing to combined optical-electrical validation.
MLCC/Passive Components and ABF
Yageo
1) Goldman Sachs maintained Buy and raised its 12-month target price from NT$346 to NT$1,490. The report argues that migration of capacity to AI-grade MLCCs will squeeze general-purpose MLCC supply, with global non-AI MLCC utilization returning to 97%/100% in 2027/2028.
2) Yageo’s general-purpose MLCC prices are expected to rise 29%/93%/84% YoY in 2026/2027/2028. This is a typical case of AI infrastructure spilling over into ordinary passive components.
"more and more MLCC capacity is being transferred into the AI grade MLCC supply chain"
Samsung Electro-Mechanics, LG Innotek
1) Goldman Sachs raised its target price for Samsung Electro-Mechanics from KRW1.0 million to KRW2.6 million and maintained Buy. AI MLCC revenue is expected to grow 6.4x from 2025 to 2028 and account for 28% of MLCC revenue in 2028.
2) LG Innotek’s target price was raised from KRW550,000 to KRW1.0 million, with Neutral maintained. ABF revenue is expected to rise from KRW50 billion in 2025 to KRW700 billion in 2028, but still represent only 2.5% of total revenue.
ABF/Fiberglass Materials
1) Industry-wide new capacity for high-end ABF substrates will be limited before 2H27. Higher power, larger packages, and faster interconnects in AI servers are raising layer counts and material requirements.
2) Nittobo has roughly 90% global share in low-CTE T-glass and 60-70% share in low-Dk NER-glass. China’s Guangyuan New Material is investing US$1 billion to challenge it, but certification cycles remain the moat.
Power Semiconductors/Thermal and Power
Texas Instruments, Infineon, STMicroelectronics
1) Power semiconductors have already begun to rise in price before the arrival of 1 MW racks. Infineon raised prices by 10%-25%, Texas Instruments raised prices again on PMICs and MOSFETs on July 1, and STMicroelectronics implemented a second round of price increases on some products.
2) The reason is that a Vera Rubin single rack is about 225 kW, while Rubin Ultra is roughly above 600 kW. VRM phases, MOSFETs, drivers, controllers, capacitors, and inductors all need to scale up.
onsemi and the OSAT Supply Chain
1) Greatek plans to acquire equity in a Philippines-based OSAT services company from onsemi Japan Holdings for no more than US$45 million. After closing, the company is expected to be renamed Greatek Electronics Philippines Corporation.
2) This is not a positive signal for onsemi orders. It reflects OSAT supply-chain diversification into Southeast Asia in response to customer requirements for Taiwan PCB and substrate +1 strategies and global delivery resilience.
Thermal Components
1) MinebeaMitsumi plans to invest JPY 58 billion to expand precision-bearing capacity, lifting monthly capacity to more than 500 million units. The company has over 60% global share in miniature bearings below 22mm.
2) As AI server power consumption rises, liquid cooling will not eliminate air-side components. Fan motors, bearings, and rear-door heat-exchange systems should still benefit.
Optical Communications / Optics Chain
CPO / Silicon Photonics Chain
1) Broadcom covers PIC design, laser sources, photodiodes, and EICs; Marvell Technology is the DSP engine for optical modules; MACOM is positioned in 1.6T/3.2T optical transceivers; Keysight, FormFactor, Teradyne, and EXFO benefit from rising test complexity.
2) Foxconn Industrial Internet reported Q1 2026 revenue of US$66.6 billion, up 29.7% YoY. AI servers accounted for more than 50% of server revenue. CPO switches are expected to enter mass production in Q3 2026, with full-year shipments forecast at 10,000 units.
"Every AI data center being built depends on what's in that chart"
Fiber-Optic Cables and Materials
1) Optical interconnects are not only about optical modules. Fiber, optical materials, testing, and server assembly are all benefiting. Cable and fiber-material companies such as Furukawa Electric, Fujikura, and Sumitomo Electric should be included in the optical communications chain rather than viewed separately as a Japan materials theme.
2) In the near term, the key is to verify the order cadence for 1.6T/3.2T optical modules, CPO switches, DSPs, and silicon photonics test equipment.
Robotics / Autonomous Driving and Space Satellites
Robotics Components
1) VPG reported Q1 revenue of US$84.35 million, up 17.6% YoY, with orders of US$102.08 million and a book-to-bill ratio of 1.21. However, humanoid robot orders were only US$1 million, slightly above 1% of the total.
2) This line shows that tactile sensors and safety certification are real bottlenecks. But the stock was once priced at close to 270x PER, so long-term robotics TAM cannot be capitalized into current-period earnings all at once.
Agility / Robotics Commercialization
1) Agility plans to list via SPAC. It has raised about US$640 million in private financing, deployed around 100 Digit robots, has more than US$300 million in unfulfilled orders, and targets annual capacity of more than 10,000 units.
2) Deployments by customers including Amazon, GXO, Schaeffler, Toyota, and MELI show that logistics is leading adoption. But safety certification, the real payback period, and whole-machine cost remain key.
Tesla and Starlink
1) The Tesla app has begun showing whether FSD is enabled, improving vehicle-side software visibility. Future Robotaxi services may require similar remote status monitoring.
2) Starlink antennas are testing emergency Wi-Fi in Japan. With 120,000 fire-hydrant markers nationwide, LEO communications are expanding from home broadband into public safety and disaster-recovery networks.
Internet / Platforms
Amazon
1) Amazon spans three lines: platform, advertising, and cloud capex. The advertising business is more mature, while AWS continues to support group investment with operating margins near 35%. In-house chips for edge hardware are moving the device ecosystem into an AI cost-control phase.
2) The risk is that in-house chips do not mean a complete escape from external suppliers such as Qualcomm. In the near term, the key is whether Alexa, Echo, Fire TV, and other products can convert local inference into experiences users are willing to pay for.
Meta
1) Market disagreement on Meta comes from the intensity of AI investment, not the disappearance of the advertising core. Materials indicate it may still increase AI infrastructure spending and continue locking in HBM, LPDDR5, and eSSD.
2) If its self-built AI cloud delivers cost advantages, external clouds such as CoreWeave will face pressure. If self-built capacity is insufficient to cover demand, neoclouds and data-center landlords will still have contract opportunities.
Reddit, AppLovin, and Unity Software
1) AI ad optimization continues to spread across internet platforms. After restructuring, Unity Software revenue grew 17% YoY, with the Grow advertising business up about 50% YoY; AppLovin revenue grew 59% YoY; Reddit advertising revenue grew 74% YoY.
2) The key in this line is not the term “AI,” but whether ad conversion, the number of stores, data assets, and model distribution capabilities can keep lifting the revenue slope.
Netflix, Uber, DoorDash, and Airbnb
1) These platforms appeared in the opening leaderboard mainly as market facts, with limited new hard evidence tied to the AI or semiconductor core themes.
2) The focus here is marginal change in platform business models. Streaming, local services, and travel platforms remain gauges of consumer-internet risk appetite, but they do not drive this issue of the tech morning note.
Software / SaaS
Microsoft
1) The software base and AI pricing power are Microsoft’s clearest main lines. Materials state that the “software business is safe” and suggest AI capex will shift toward positive ROI.
2) For investors, the next things to watch are Copilot penetration, Azure AI revenue, enterprise contract renewals, and bundled price increases, rather than only the absolute amount of capex.
Palantir
1) SaaS valuation comparisons show Palantir with expected NTM revenue growth of 63.5% and EV/gross profit of 67.8x, making it one of the most expensive names in the software group.
2) Its premium comes from the AI data platform and government/enterprise workflow deployment, but the risk is also clear: high growth must be delivered alongside gross margin, operating margin, retention, and free cash flow.
"SaaS valuation: growth alone is not enough"
Snowflake, Datadog, and Cloudflare
1) The software budget debate is shifting from pure revenue growth to growth quality. Snowflake, Datadog, and Cloudflare all benefit from data, observability, and edge cloud, but valuations need to be viewed together with gross margin, operating margin, renewal rates, and retention.
2) The software group’s relative defensiveness versus semiconductors shows that near-term capital is willing to look for AI applications and infrastructure software with lighter cash-flow demands, but there were no new hard target-price actions.
Figma and Model-Application Competition
1) The timing of Anthropic’s Claude Design launch was used to discuss competition with Figma’s core product. Materials state that Figma’s share price fell 7% on the launch day, was down about 80% from its historical high, and erased nearly US$50 billion of market value.
2) The core risk is that when frontier models enter vertical applications, the product moats of existing SaaS vendors may be compressed. But model companies themselves also need to prove they can turn functionality into high-retention paid products.
Generative AI Website Traffic
1) The traffic data only provides YoY growth by marketing channel for the top five generative AI websites as of May 2026 and Fable 5 search trends over the past 28 days. It does not disclose specific growth rates.
2) This type of data is suitable for tracking application momentum, but it cannot be directly extrapolated to revenue and valuation.
Consumer Electronics / Smart Vehicles
Apple
1. Apple rose 4.86% in the latest trading session, outperforming most large-cap technology stocks. Supply-chain information points to folding-screen and high-end new-model build progress that “looks okay,” but actual shipments may fall below external expectations.
2. Memory price increases will pressure iPhone, Mac, and iPad costs. The materials also note that memory accounts for roughly 40% of the BOM in high-end smartphones, which will test Apple’s pricing power.
Consumer Electronics Memory Costs
1. After AI data centers absorbed HBM, server DRAM, and eSSD supply, smartphones and PCs are starting to face pressure. IDC expects global smartphone shipments to decline by nearly 13%, while ASP rises to USD 523; higher memory prices are being transmitted into end hardware.
2. This benefits memory makers, but creates dual pressure on consumer electronics brands through gross margin and unit volume.
Tesla
1. Tesla fell 6.95% in the short term, but the useful information in this package relates to FSD status displays and the longer-term Robotaxi scenario.
2. Prices for Chinese humanoid robots are also moving lower: Unitree R1 is priced at RMB 26,900, Booster K1 at RMB 29,900, and Noetix Bumi at RMB 9,998. Cost declines will accelerate application pilots, while also compressing full-system premiums.
Robotics Supply Chain
1. China shipped 14,400 humanoid robots in 2025, with 2026 shipments expected at 100,000-200,000 units. Unitree’s average selling price fell from about RMB 593,000 in 2023 to RMB 167,000 by end-2025, while production cost declined from RMB 73,200 to RMB 62,200.
2. The United States is stronger in foundation models, autonomous driving, and action scaling laws; China is stronger in shipments and the cost curve. Supply-chain opportunities are more concentrated in reducers, actuators, sensors, and batteries.
"The United States leads the world in where robotics is heading... while losing the race on where robotics is shipping today."
LG Innotek and Satellite Substrates
1. LG Innotek is seeking to enter the low-earth-orbit satellite substrate supply chain, but there is no order value or mass-production timeline.
2. This theme fits within space/satellite supply-chain tracking: satellite communications hardware may drive demand for substrates, antennas, optical communications, and low-earth-orbit ground infrastructure.
Investment Bank Target Price Changes Over the Past 12 Hours
Huang’s Selected Portfolio
404K SEMI-AI Tech Morning Brief 2026-07-06 — Memory Price Increases, AI Power Constraints, Catch-Up in Passive Components
目录
After-Market Summary
Top 10 U.S. Stocks by Trading Value
Top U.S. Stock Gainers
Top U.S. Stock Decliners
AI/Semiconductor Full Value Chain
AI Models/Applications and Capex
CSP/Cloud Capex
AI Cloud/Data-Center Operators
GPU/CPU/ASIC
HBM/DRAM/NAND/SSD/HDD
Foundry
Semiconductor Equipment/Testing
MLCC/Passive Components and ABF
Power Semiconductors/Thermal and Power
Optical Communications / Optics Chain
Robotics / Autonomous Driving and Space Satellites
Internet / Platforms
Software / SaaS
Consumer Electronics / Smart Vehicles
Investment Bank Target Price Changes Over the Past 12 Hours
Huang’s Selected Portfolio
The AI infrastructure trade is entering a supply-chain gap-finding phase. U.S. tech and semiconductors pulled back in the latest closing session, but capital has not left the AI theme. Instead, it is spreading from GPUs into memory, MLCCs, ABF, power, electricity, silicon photonics, and data center operators.
After-Market Summary
The latest U.S. equity closing session was 2026-07-02, and the technology theme sold off first. The Nasdaq 100 fell 1.73%, the technology ETF fell 2.71%, the semiconductor ETF fell 4.54%, and the equal-weight semiconductor reference fell 5.57%. The equal-weight S&P; rose 0.70% and the Dow rose 1.05%, showing that the pullback was concentrated in mega-cap technology and the semiconductor chain.
By style, software was more resilient than hardware. The software ETF rose 0.25%, cloud computing fell 1.06%, cybersecurity fell 0.48%, while AI and big data fell 2.80%. In 20-day relative strength, software and cloud remain below prior highs, but 5-day relative strength has started to recover. Semiconductor 5-day relative strength ranked near the back, as crowded short-term positioning was amplified by profit-taking in memory and equipment chains.
At the single-stock level, Apple rose 4.86% and Microsoft rose 1.85%, while Nvidia fell 1.62%, AMD fell 4.42%, Intel fell 12.70%, Micron fell 5.52%, and SanDisk fell 13.58%. The market signal is straightforward: the AI demand narrative remains intact, but the market is first cutting valuation and crowding, then looking again for the segments that can truly raise prices, secure power, and deliver.
Top 10 U.S. Stocks by Trading Value
Top U.S. Stock Gainers
Top U.S. Stock Decliners
AI/Semiconductor Full Value Chain
AI Models/Applications and Capex
AI Application Adoption
1) Enterprise AI value validation is beginning to shift from consumer chat tools to mission-critical workflows. The materials note that the top 20% of early AI-adopting enterprises can already quantify value at the organizational level, especially in security, internal processes, and dedicated model services.
2) The investment implication is that frontier model labs’ revenue will not only come from general-purpose APIs. Enterprise security and private models may become more stable budget items, but renewal rates and real procurement scale remain unproven.
“top 20% of early adopting enterprises；value is quantified at scale across the organization；mission critical functions”
Anthropic
1) Anthropic is seeking 1.4 GW of data-center capacity in Australia. Reported build-out scale varies between US$15 billion and US$21.6 billion, with roughly 1 GW targeted to come online by end-2027, potentially split into 4-5 contracts.
2) This shows model companies are competing not for a single GPU, but for power, sites, and delivery timing. The key difference among CDC, AirTrunk, NextDC, IREN, and other counterparties is who can deliver power on schedule.
OpenAI/Anthropic Duopoly
1) Model-layer concentration continues to rise. The materials state that OpenAI and Anthropic together control 88% of enterprise LLM spending. Anthropic’s ARR exceeded US$45 billion in May 2026, while OpenAI’s ARR was about US$24 billion-US$33 billion in the same period.
2) The risk is that application companies hand workflows and product roadmaps to the same group of frontier models. The upstream model layer gains pricing power, while downstream product differentiation weakens.
“Anthropic and OpenAI now control 88% of enterprise LLM spend”
CSP/Cloud Capex
Google
1) Google’s AI logic is to run Gemini on in-house TPUs and reduce cost per token. The materials state that its profit could rise from about US$170 billion to US$247 billion by 2028. The key question is who can control unit inference cost when compute is scarce.
2) This is positive for TPUs, HBM, advanced packaging, and the data-center chain, but the risk is that cloud revenue growth and ad monetization must keep pace with capex.
Meta
1) Meta is repeatedly cited as counterevidence that AI demand has not disappeared. On one side, the market worries it may sell excess compute capacity. On the other, there are claims of up to 1.6 GW of AI compute contracts and stronger long-term demand for HBM, LPDDR5, and eSSD.
2) For storage and data-center companies, Meta’s real orders matter more than headlines. The next things to watch are capex guidance and long-term supplier agreements.
Microsoft
1) Microsoft’s latest trading logic centers on its core software franchise, returns on AI capex, and pricing mechanisms. The materials state that Microsoft’s “software business is safe,” AI capex will turn ROI-positive, and the company is 15% undervalued.
2) This is not a formal rating or target price, but it shows the market is shifting from “Microsoft is spending too much” to “can Copilot, Azure, and software bundling raise revenue per customer?”
“Its software business is safe. AI capex will turn ROI positive. Changes in software pricing will drive growth.”
Amazon
1) Amazon benefits from AWS while also designing in-house chips at the device end. Its hardware chief said some devices will move to end-to-end chip design, while the company will still procure from external suppliers such as Qualcomm.
2) If edge AI enters hardware such as Echo and Fire TV, Amazon’s chip requirements will expand from cost control to model experience and local inference.
Aggregate Cloud Capex
1) AI capex from Google, Amazon, Meta, Microsoft, and Oracle is expected to exceed US$800 billion in 2026 and rise to US$1.1 trillion in 2027, equal to roughly 3.2% of US GDP.
2) The investment implication is direct: GPUs are only the first layer. Memory, servers, power, lease commitments, cooling, and interconnects are all absorbing this budget.
AI Cloud/Data-Center Operators
Nebius
1) Nebius is viewed as one of the few neoclouds with power, customers, and a software layer at the same time. The materials show Q1 2026 revenue of US$399 million, up 684% YoY, year-end ARR guidance of US$7 billion-US$9 billion, contracted power of 3.5 GW, and a year-end target above 4 GW.
2) The company has more than US$46 billion of contracts with Meta and Microsoft extending to 2031. The risk is that the capital-intensive model makes financing capacity and delivery cadence central to valuation.
“Most neoclouds have none of those three things simultaneously but Nebius has all of them”
CoreWeave
1) CoreWeave has pulled back more than 50% from its high, but backlog remains near US$100 billion and revenue is still growing more than 100% YoY.
2) The company represents the debate around neoclouds: contracts and revenue are very strong, but debt, losses, and hyperscalers building their own clouds will compress valuation tolerance.
IREN
1) The debate around IREN is “megawatt assets” versus “platform capability.” The materials state that it will approach 1 GW of operating or completed capacity by end-2026, including 160 MW in Canada and 750 MW at Childress. Sweetwater 1, a single 1.4 GW site, was energized on May 28, 2026.
2) Nvidia has announced an initial 60 MW deployment, but an Anthropic partnership remains unconfirmed speculation. What the share price needs to validate is whether IREN can convert power assets into contracted AI cloud revenue.
TeraWulf, Cipher Mining, Applied Digital, Galaxy Digital
1) These companies are all on the AI data-center operator list, but the strength of hard evidence varies in this round. The investable narrative should include data centers, power capacity, AI compute hosting, financing, and customer contracts; a stock should not be included merely because it appears.
2) Future tracking should focus on power interconnection, customer credit quality, GPU financing, and take-or-pay contracts, not one-day share-price moves.
GPU/CPU/ASIC
Nvidia
1) Nvidia remains the largest beneficiary of AI factory budgets. The materials state that a 1 GW AI factory based on Nvidia architecture could cost close to US$100 billion, with about half flowing to Nvidia chips, systems, and software.
2) The risk is also starting to shift from demand to architecture execution: Kyber NVL144 has been delayed by more than 12 months to 2028, the back-to-back NVL72x2 solution has been cancelled, and Rubin Ultra’s scale-up world size is constrained.
“1GW AI factory... could now cost nearly 100 billion dollars”
Intel
1) Intel 18A yield is still in the early ramp phase, but company commentary indicates improvement is ahead of internal targets. Management has mentioned monthly yield improvement of 7% or 8%. 14A is planned for risk production in 2028 and mass production in 2029, with the 0.9 PDK version to be released in October.
2) The business question for this line is whether Intel can lock in major fabless customers over the next 18 months. If not, the advanced foundry story will continue to be overshadowed by TSMC A14 and Samsung Electronics SF2Z.
Broadcom
1) Broadcom’s latest quarterly AI revenue grew 106% YoY to US$8.4 billion, driven by custom accelerators and AI networking chips for Google, Meta, and Anthropic.
2) At the same time, the market questions whether the company is “chips only” and lacks a full AI system-integration narrative. Future valuation depends on ASIC customer expansion and networking-chip volume ramp.
AMD
1) AMD’s opportunity comes from small-scale deployment feedback for MI355x and the potential for MI500X to compete in the Rubin Ultra scale-up window. The materials show MI355x preregistration has reached 6 nodes and 48 GPUs, with a US$100 threshold per preregistration.
2) This is not a formal order, but it shows independent compute deployers are beginning to queue for AMD GPUs. The next validation points are MI450/MI500 mass production, customer financing, and software-stack stability.
HBM/DRAM/NAND/SSD/HDD
Micron
1) Micron has started a JPY1.5 trillion, or about US$9.3 billion, AI memory expansion in Hiroshima to produce HBM, with shipments expected in summer 2028. The Japanese government will provide support of up to JPY500 billion, with total support of roughly JPY775 billion.
2) This has limited impact on near-term supply, but it reinforces Micron’s medium- to long-term capacity position in HBM. The near-term share-price pullback is more about crowding and profit-taking in memory stocks at elevated levels.
“The new facility will produce high-bandwidth memory for AI processors”
Samsung Electronics, SK Hynix
1) UBS raised its DDR contract-price forecast to +32% QoQ in 3Q26 and +18% QoQ in 4Q26, and its NAND forecast to +30% QoQ in 3Q26 and +12% QoQ in 4Q26. The report expects DRAM to remain in shortage at least through 2Q28.
2) SK Hynix is also rumored to be planning a Nasdaq listing, with the logic of using the US equity market to reprice HBM, DRAM, and flash demand. However, leveraged single-stock ETFs in Korea amplify volatility, so not all short-term price action should be treated as fundamentals.
SanDisk, Kioxia
1) BofA believes Korea’s KRW800 trillion memory cluster will not generate effective output quickly, while NAND shortages and enterprise SSD demand remain strong. SanDisk’s enterprise SSD revenue grew 7x YoY, and the company is developing high-bandwidth flash, expected to be released later in 2026 to 2027.
2) The core of Kioxia and SanDisk is the NAND pricing cycle and eSSD supply-demand, not traditional consumer flash. The risk is whether downstream procurement can continue to absorb compounded price increases.
China Memory Chain
1) Lenovo has begun equipping global ThinkBook 14 G9 configurations with YMTC SSDs. CXMT is testing a bonded DRAM pilot line in Hefei, attempting to use DUV multi-patterning to work around EUV.
2) Neither development is yet large-scale mass production or order realization, but they show China’s memory substitution is advancing simultaneously from PC SSDs and DRAM process routes.
Foundry
TSMC
1) TSMC accounts for about 70% of global advanced foundry share, with Nvidia and Apple alone contributing roughly 40% of revenue. At 2025 IEEE ECTC, the company introduced SoW-X, pointing to wafer-level system integration to address reticle-size, I/O bandwidth, and thermal-management bottlenecks.
2) Advanced process nodes and advanced packaging are merging into a system capability. TSMC’s risks are not demand, but geopolitics, energy, and customer concentration.
“SoW-X redefines how logic and memory interact at scale”
Semiconductor Equipment/Testing
Equipment Chain
1) Samsung Electronics and SK Hynix are evaluating alternatives to Mattson’s PR strip and RTP equipment. Supply-chain diversification benefits Applied Materials, ASML, Lam Research, Tokyo Electron, KLA, and Korean equipment vendors.
2) SEAJ raised its FY2026 Japan semiconductor equipment sales outlook to JPY6.55 trillion, with FY2027 at JPY7.4 trillion and FY2028 at JPY7.77 trillion. The equipment cycle is supported by advanced logic and DRAM expansion.
FormFactor, Teradyne, Advantest
1) FormFactor’s Q1 2026 revenue was US$226 million, up 32% YoY, with non-GAAP EPS of US$0.56, above expectations of US$0.44. Through Keystone Photonics, it is partnering with Advantest to enter silicon photonics wafer-level testing.
2) Rising complexity in CPO, silicon photonics, and high-speed electro-optical testing will expand equipment value from traditional electrical testing to combined optical-electrical validation.
MLCC/Passive Components and ABF
Yageo
1) Goldman Sachs maintained Buy and raised its 12-month target price from NT$346 to NT$1,490. The report argues that migration of capacity to AI-grade MLCCs will squeeze general-purpose MLCC supply, with global non-AI MLCC utilization returning to 97%/100% in 2027/2028.
2) Yageo’s general-purpose MLCC prices are expected to rise 29%/93%/84% YoY in 2026/2027/2028. This is a typical case of AI infrastructure spilling over into ordinary passive components.
“more and more MLCC capacity is being transferred into the AI grade MLCC supply chain”
Samsung Electro-Mechanics, LG Innotek
1) Goldman Sachs raised its target price for Samsung Electro-Mechanics from KRW1.0 million to KRW2.6 million and maintained Buy. AI MLCC revenue is expected to grow 6.4x from 2025 to 2028 and account for 28% of MLCC revenue in 2028.
2) LG Innotek’s target price was raised from KRW550,000 to KRW1.0 million, with Neutral maintained. ABF revenue is expected to rise from KRW50 billion in 2025 to KRW700 billion in 2028, but still represent only 2.5% of total revenue.
ABF/Fiberglass Materials
1) Industry-wide new capacity for high-end ABF substrates will be limited before 2H27. Higher power, larger packages, and faster interconnects in AI servers are raising layer counts and material requirements.
2) Nittobo has roughly 90% global share in low-CTE T-glass and 60-70% share in low-Dk NER-glass. China’s Guangyuan New Material is investing US$1 billion to challenge it, but certification cycles remain the moat.
Power Semiconductors/Thermal and Power
Texas Instruments, Infineon, STMicroelectronics
1) Power semiconductors have already begun to rise in price before the arrival of 1 MW racks. Infineon raised prices by 10%-25%, Texas Instruments raised prices again on PMICs and MOSFETs on July 1, and STMicroelectronics implemented a second round of price increases on some products.
2) The reason is that a Vera Rubin single rack is about 225 kW, while Rubin Ultra is roughly above 600 kW. VRM phases, MOSFETs, drivers, controllers, capacitors, and inductors all need to scale up.
onsemi and the OSAT Supply Chain
1) Greatek plans to acquire equity in a Philippines-based OSAT services company from onsemi Japan Holdings for no more than US$45 million. After closing, the company is expected to be renamed Greatek Electronics Philippines Corporation.
2) This is not a positive signal for onsemi orders. It reflects OSAT supply-chain diversification into Southeast Asia in response to customer requirements for Taiwan PCB and substrate +1 strategies and global delivery resilience.
Thermal Components
1) MinebeaMitsumi plans to invest JPY 58 billion to expand precision-bearing capacity, lifting monthly capacity to more than 500 million units. The company has over 60% global share in miniature bearings below 22mm.
2) As AI server power consumption rises, liquid cooling will not eliminate air-side components. Fan motors, bearings, and rear-door heat-exchange systems should still benefit.
Optical Communications / Optics Chain
CPO / Silicon Photonics Chain
1) Broadcom covers PIC design, laser sources, photodiodes, and EICs; Marvell Technology is the DSP engine for optical modules; MACOM is positioned in 1.6T/3.2T optical transceivers; Keysight, FormFactor, Teradyne, and EXFO benefit from rising test complexity.
2) Foxconn Industrial Internet reported Q1 2026 revenue of US$66.6 billion, up 29.7% YoY. AI servers accounted for more than 50% of server revenue. CPO switches are expected to enter mass production in Q3 2026, with full-year shipments forecast at 10,000 units.
“Every AI data center being built depends on what’s in that chart”
Fiber-Optic Cables and Materials
1) Optical interconnects are not only about optical modules. Fiber, optical materials, testing, and server assembly are all benefiting. Cable and fiber-material companies such as Furukawa Electric, Fujikura, and Sumitomo Electric should be included in the optical communications chain rather than viewed separately as a Japan materials theme.
2) In the near term, the key is to verify the order cadence for 1.6T/3.2T optical modules, CPO switches, DSPs, and silicon photonics test equipment.
Robotics / Autonomous Driving and Space Satellites
Robotics Components
1) VPG reported Q1 revenue of US$84.35 million, up 17.6% YoY, with orders of US$102.08 million and a book-to-bill ratio of 1.21. However, humanoid robot orders were only US$1 million, slightly above 1% of the total.
2) This line shows that tactile sensors and safety certification are real bottlenecks. But the stock was once priced at close to 270x PER, so long-term robotics TAM cannot be capitalized into current-period earnings all at once.
Agility / Robotics Commercialization
1) Agility plans to list via SPAC. It has raised about US$640 million in private financing, deployed around 100 Digit robots, has more than US$300 million in unfulfilled orders, and targets annual capacity of more than 10,000 units.
2) Deployments by customers including Amazon, GXO, Schaeffler, Toyota, and MELI show that logistics is leading adoption. But safety certification, the real payback period, and whole-machine cost remain key.
Tesla and Starlink
1) The Tesla app has begun showing whether FSD is enabled, improving vehicle-side software visibility. Future Robotaxi services may require similar remote status monitoring.
2) Starlink antennas are testing emergency Wi-Fi in Japan. With 120,000 fire-hydrant markers nationwide, LEO communications are expanding from home broadband into public safety and disaster-recovery networks.
Internet / Platforms
Amazon
1) Amazon spans three lines: platform, advertising, and cloud capex. The advertising business is more mature, while AWS continues to support group investment with operating margins near 35%. In-house chips for edge hardware are moving the device ecosystem into an AI cost-control phase.
2) The risk is that in-house chips do not mean a complete escape from external suppliers such as Qualcomm. In the near term, the key is whether Alexa, Echo, Fire TV, and other products can convert local inference into experiences users are willing to pay for.
Meta
1) Market disagreement on Meta comes from the intensity of AI investment, not the disappearance of the advertising core. Materials indicate it may still increase AI infrastructure spending and continue locking in HBM, LPDDR5, and eSSD.
2) If its self-built AI cloud delivers cost advantages, external clouds such as CoreWeave will face pressure. If self-built capacity is insufficient to cover demand, neoclouds and data-center landlords will still have contract opportunities.
Reddit, AppLovin, and Unity Software
1) AI ad optimization continues to spread across internet platforms. After restructuring, Unity Software revenue grew 17% YoY, with the Grow advertising business up about 50% YoY; AppLovin revenue grew 59% YoY; Reddit advertising revenue grew 74% YoY.
2) The key in this line is not the term “AI,” but whether ad conversion, the number of stores, data assets, and model distribution capabilities can keep lifting the revenue slope.
Netflix, Uber, DoorDash, and Airbnb
1) These platforms appeared in the opening leaderboard mainly as market facts, with limited new hard evidence tied to the AI or semiconductor core themes.
2) The focus here is marginal change in platform business models. Streaming, local services, and travel platforms remain gauges of consumer-internet risk appetite, but they do not drive this issue of the tech morning note.
Software / SaaS
Microsoft
1) The software base and AI pricing power are Microsoft’s clearest main lines. Materials state that the “software business is safe” and suggest AI capex will shift toward positive ROI.
2) For investors, the next things to watch are Copilot penetration, Azure AI revenue, enterprise contract renewals, and bundled price increases, rather than only the absolute amount of capex.
Palantir
1) SaaS valuation comparisons show Palantir with expected NTM revenue growth of 63.5% and EV/gross profit of 67.8x, making it one of the most expensive names in the software group.
2) Its premium comes from the AI data platform and government/enterprise workflow deployment, but the risk is also clear: high growth must be delivered alongside gross margin, operating margin, retention, and free cash flow.
“SaaS valuation: growth alone is not enough”
Snowflake, Datadog, and Cloudflare
1) The software budget debate is shifting from pure revenue growth to growth quality. Snowflake, Datadog, and Cloudflare all benefit from data, observability, and edge cloud, but valuations need to be viewed together with gross margin, operating margin, renewal rates, and retention.
2) The software group’s relative defensiveness versus semiconductors shows that near-term capital is willing to look for AI applications and infrastructure software with lighter cash-flow demands, but there were no new hard target-price actions.
Figma and Model-Application Competition
1) The timing of Anthropic’s Claude Design launch was used to discuss competition with Figma’s core product. Materials state that Figma’s share price fell 7% on the launch day, was down about 80% from its historical high, and erased nearly US$50 billion of market value.
2) The core risk is that when frontier models enter vertical applications, the product moats of existing SaaS vendors may be compressed. But model companies themselves also need to prove they can turn functionality into high-retention paid products.
Generative AI Website Traffic
1) The traffic data only provides YoY growth by marketing channel for the top five generative AI websites as of May 2026 and Fable 5 search trends over the past 28 days. It does not disclose specific growth rates.
2) This type of data is suitable for tracking application momentum, but it cannot be directly extrapolated to revenue and valuation.
Consumer Electronics / Smart Vehicles
Apple
1. Apple rose 4.86% in the latest trading session, outperforming most large-cap technology stocks. Supply-chain information points to folding-screen and high-end new-model build progress that “looks okay,” but actual shipments may fall below external expectations.
2. Memory price increases will pressure iPhone, Mac, and iPad costs. The materials also note that memory accounts for roughly 40% of the BOM in high-end smartphones, which will test Apple’s pricing power.
Consumer Electronics Memory Costs
1. After AI data centers absorbed HBM, server DRAM, and eSSD supply, smartphones and PCs are starting to face pressure. IDC expects global smartphone shipments to decline by nearly 13%, while ASP rises to USD 523; higher memory prices are being transmitted into end hardware.
2. This benefits memory makers, but creates dual pressure on consumer electronics brands through gross margin and unit volume.
Tesla
1. Tesla fell 6.95% in the short term, but the useful information in this package relates to FSD status displays and the longer-term Robotaxi scenario.
2. Prices for Chinese humanoid robots are also moving lower: Unitree R1 is priced at RMB 26,900, Booster K1 at RMB 29,900, and Noetix Bumi at RMB 9,998. Cost declines will accelerate application pilots, while also compressing full-system premiums.
Robotics Supply Chain
1. China shipped 14,400 humanoid robots in 2025, with 2026 shipments expected at 100,000-200,000 units. Unitree’s average selling price fell from about RMB 593,000 in 2023 to RMB 167,000 by end-2025, while production cost declined from RMB 73,200 to RMB 62,200.
2. The United States is stronger in foundation models, autonomous driving, and action scaling laws; China is stronger in shipments and the cost curve. Supply-chain opportunities are more concentrated in reducers, actuators, sensors, and batteries.
“The United States leads the world in where robotics is heading... while losing the race on where robotics is shipping today.”
LG Innotek and Satellite Substrates
1. LG Innotek is seeking to enter the low-earth-orbit satellite substrate supply chain, but there is no order value or mass-production timeline.
2. This theme fits within space/satellite supply-chain tracking: satellite communications hardware may drive demand for substrates, antennas, optical communications, and low-earth-orbit ground infrastructure.
Investment Bank Target Price Changes Over the Past 12 Hours
Huang’s Selected Portfolio
