AI Stocks & Markets

Today's Stories

1. 1

   Tech stocks set for earnings test after AI sell-off

   The stock market fell last week, with losses concentrated in technology and AI-related sectors. Major earnings reports are due this week from Alphabet, Tesla, Intel, GE Vernova, Interactive Brokers, and AMD, which is also hosting an AI event. Tech stocks have been a key market driver, and this week's earnings will signal whether the recent sell-off reflects genuine business weakness or a temporary pullback. The results could influence investor confidence heading into the next trading period.

   Futures for the Dow Jones, S&P 500, and Nasdaq are set to open Sunday evening, offering early signals for the week ahead.

2. 2

   QQQ's AI Capex Gamble: Two Forces Will Make or Break Your 2026 Gains

   The Invesco QQQ Trust trades near $720, up roughly 17% year to date, but its concentration in AI-heavy megacaps—NVIDIA ($5.1 trillion（約820兆円） market cap), Microsoft ($2.86 trillion（約460兆円）), Alphabet ($2.11 trillion（約340兆円）), and Meta ($1.45 trillion（約230兆円）)—means two macro and fund-specific factors will dominate returns in the second half of 2026. The top four holdings are betting that massive AI infrastructure spending converts to revenue; Meta raised its FY26 capex guide to $125-145 billion, Microsoft spent roughly $31 billion（約5兆円） in a single quarter, and Alphabet spent about $36 billion（約5.8兆円）. For now, the payback is showing—Micron's fiscal Q3 revenue hit roughly $41 billion（約6.6兆円） (up about 346% year over year with 84.6% gross margin) and Nvidia guided Q2 revenue to $91 billion（約15兆円）—but Goldman Sachs frames this as an "uneasy equilibrium" where AI capex may be masking softer parts of the real economy.

   The 10-year Treasury yield is at 4.62% (99th percentile of its 12-month range); if it settles below 4.30% while hyperscaler capex guidance holds firm, QQQ's setup improves materially. If it pushes through 4.75% and any top-four holding walks back 2027 AI spend, the fund's 17% year-to-date cushion will erode quickly. All four companies report earnings in late July and August.

3. 3

   Chip Index Falls to Bear Market; Apple Hits Record High

   The PHLX Semiconductor Index closed in a bear market on Friday, finishing more than 20% below its June peak. Apple touched a record intraday high of $334.98 and briefly surpassed Nvidia to reclaim its position as the world's most valuable company, valued at about $4.9 trillion（約780兆円）. Global chip stocks have erased about $3.3 trillion（約530兆円） in market value since June 22 as investors reassess AI infrastructure costs and profitability. Apple's light spending on AI—just $12.7 billion（約2兆円） in capital expenditures in fiscal 2025—shields it from the downturn that is hitting rivals like Microsoft and Amazon, who have committed hundreds of billions to AI infrastructure. Apple's revenue rose 17% year over year to $111.2 billion（約18兆円） in its fiscal second quarter, and the stock has gained nearly 59% over the past year.

   Apple trades at roughly 40 times earnings, a steep multiple for a company growing revenue 17%. The premium investors are paying for safety could expand if chip sell-offs deepen, but leaves little room for disappointment if iPhone momentum cools.

4. 4

   TSMC soars on AI chip demand; IBM stumbles as customers shift to AI

   TSMC reported second-quarter revenue jumping 36% year over year and net income rocketing 77.4% higher, with the company planning to expand its US footprint. Meanwhile, IBM preannounced Q2 earnings Tuesday, reporting adjusted EPS of $2.93 on revenue of $17.2 billion（約2.8兆円）—both falling short of analyst expectations (adjusted EPS of $3.02 on revenue of $17.86 billion（約2.9兆円）)—as customers shifted spending from mainframe systems to AI servers and memory chips. China's Moonshot AI also announced its new Kimi K3 model, which surpasses OpenAI's GPT-5.6 Sol and Anthropic's Fable 5 on certain benchmark tests, though it falls short in overall performance. TSMC's 36% revenue jump underscores how central semiconductor supply has become to the AI boom—the company produces chips for Apple, AMD, Nvidia, and Qualcomm. IBM's shortfall reflects a real shift in enterprise spending priorities: businesses are moving capital away from traditional systems toward AI infrastructure. Moonshot AI's strong benchmark performance shows how quickly Chinese AI companies are closing the gap with US leaders like OpenAI and Anthropic, particularly through open-weight models and lower pricing that appeal to cost-conscious businesses.

   TSMC CFO Wendell Huang expects strong demand to continue into the current quarter as tech companies seek more AI chips. Moonshot AI's approach mirrors China's DeepSeek strategy: releasing free, customizable open-weight models undercut the pricing of Anthropic's Claude, OpenAI's GPT, and Google's Gemini, making them more attractive to price-sensitive enterprises.

5. 5

   Palantir, Nvidia team up on sovereign AI for governments

   Palantir Technologies announced a partnership with Nvidia to deploy sovereign AI solutions for government agencies, using Nvidia's open AI model Nemotron as a core building block within Palantir's software platforms. The collaboration targets governments' need to keep sensitive data under local control while meeting compliance and national sovereignty requirements—a central requirement for public sector AI adoption that sits at the heart of Palantir's government business.

   The partnership may influence how Palantir approaches new government bids and technology alignment with public sector clients, and could shape how investors view Palantir's role in the wider AI supply chain spanning chips, models, and application-level software.

6. 6

   Apple's AI frugality hits a wall as technical crisis looms

   Apple avoided the massive capital spending on AI infrastructure that competitors like OpenAI and Google undertook, saving billions of dollars. New reports now suggest the company faces a quiet technical crisis that may compel it to make a different kind of costly investment. Apple's hands-off approach to AI CapEx had appeared strategically sound, but the emerging technical problems indicate the company may not have solved the underlying challenge — it may simply have deferred rather than dodged the expense. This means Apple's balance sheet advantage from avoiding AI infrastructure spending could be temporary.

   The specific nature of the technical crisis and whether Apple will ultimately be forced to commit substantial capital to resolve it — potentially eroding the financial advantage it gained by staying out of the AI spending race its rivals entered.