#我的七夕交易分享 US AI Stocks
Based on the latest institutional views and market data, US AI stocks have evolved from the early-stage “NVIDIA dominance” into an ecosystem covering multiple segments, including chip design, semiconductor equipment, cloud computing platforms, AI application software, storage, and networking. The following research list is organized by position in the industry chain:
I. Chip Design: High-Profit Barriers and Long-Term Core Holdings
· NVIDIA (NVDA): The undisputed leader in AI GPUs, with approximately 86% of the data center GPU market. Although its stock price rose “only” 15% in Q2, HSBC expects its Q1 revenue to reach $81.1 billion, continuing to exceed expectations, with a price target as high as $325.
· Broadcom (AVGO): A leader in custom AI chips (ASICs), providing TPU solutions for companies such as Google, with a gross margin as high as 77%. The company expects AI chip business revenue to surpass $100 billion in 2027.
· AMD (AMD): Advancing on both the CPU and GPU fronts, with its market capitalization increasing by approximately $615 billion in Q2 2026, benefiting from the expansion of AI platforms in data centers.
II. Semiconductor Equipment: The “Shovel Sellers” of AI Capacity
· Applied Materials (AMAT) & ASML (ASML): Direct beneficiaries of increased capital expenditure by global technology giants, with their stock prices surging 200% and 150%, respectively, over the past year. Global AI capital expenditure is expected to jump from approximately $705 billion in 2026 to more than $1 trillion in 2027, further reinforcing equipment makers’ core position.
III. Cloud Computing and Platforms: The Main Battlefield for AI Monetization
Wall Street is shifting from “who invests the most” to “who can turn AI into profits.”
· Amazon (AMZN): AWS cloud revenue surged 37% year over year to $42.2 billion in Q2, while annualized AI business revenue exceeded $25 billion, driving the stock to lead the “Magnificent Seven.”
· Microsoft (MSFT): Strong demand for AI on Azure cloud, with its enterprise contract backlog reaching a record high; Wedbush considers it the most favored large-cap technology stock for 2026.
· Google (GOOGL): Its cloud business achieved its strongest growth ever, integrating the Gemini AI model with its cloud platform.
IV. Storage and Networking: The Overlooked “Bottleneck”
Capital is spreading from NVIDIA to the AI infrastructure supply chain, with storage standing out as the biggest highlight.
· Micron (MU): Explosive HBM demand drove its stock price up more than 240% in Q2, while its gross margin surged to 84.9% and its market capitalization briefly exceeded $1 trillion.
· SanDisk (SNDK) & Western Digital (WDC): The storage sector has performed strongly year to date, providing critical data support for AI servers.
· Lumentum (LITE): A core optical communications supplier benefiting from demand for connectivity within data centers, with its stock rising more than 13% in a single day in August.
V. AI Application Software: Stocks with Commercialization Potential
· Palantir (PLTR): Defense and data analytics, with US commercial revenue growing 121% year over year. Analysts believe it has the potential to become a “trillion-dollar market cap” company.
· CrowdStrike (CRWD): AI-enabled cybersecurity, with analysts assigning it a $700 price target.
· ServiceNow (NOW) & Salesforce (CRM): Software leaders in enterprise AI agents.
VI. Other Stocks Worth Watching
· Intel (INTC): Its market capitalization increased by approximately $480 billion in Q2, supported both by government backing and expectations of an AI chip transformation.
· Arm (ARM): Chip IP licensing, benefiting from demand for AI computing architectures.
Disclaimer: The above is for technical observations and industry analysis only and does not constitute any investment advice. $SNDK ‌

#OpenAIAnnualRevenueSurpasses40B
My view is this: Yes, a high growth rate can justify a very high IPO valuation; however, a valuation exceeding $1 trillion requires investors to believe that the current $40 billion annual revenue run rate represents the start of a sustained revenue growth trajectory, rather than the peak of an AI spending cycle.
The headline is truly impressive. Reports indicate that OpenAI’s annualized revenue has surpassed the $40 billion mark—roughly doubling its level from late 2025—driven by momentum in coding, enterprise AI agents, and advertising.
The valuation math presents some striking figures:
OpenAI’s March 2026 investment round valued the company at $852 billion (post-money).
Based on the $40 billion annual revenue run rate:
$852 billion valuation / $40 billion revenue = ~21x (price-to-sales ratio)
$1 trillion valuation / $40 billion = 25x
$1.5 trillion / $40 billion = 37.5x
$2 trillion / $40 billion = 50x
These are extraordinary multiples for a company that is still spending heavily on computing power and infrastructure.
However, there is an important nuance here: The market isn't necessarily valuing OpenAI based on its current $40 billion revenue; it is evaluating the company based on the revenue potential it could reach between 2027 and 2030.
We see exactly this scenario with Anthropic as well. Investors are taking into account projections that Anthropic could reach $190–200 billion in revenue by 2028, even though its current annualized revenue run rate stands at approximately $47 billion. Anthropic's most recent private funding round valued the company at $965 billion.
Consequently, the valuation race is increasingly shifting away from traditional Software-as-a-Service (SaaS) multiples and turning into a bet on the future AI economy.
Why am I optimistic about OpenAI's revenue growth trajectory?
1. Coding and AI agents represent a market that is potentially far larger than that of chatbot subscriptions.
This is the most significant development. If companies begin paying OpenAI not just for "AI assistants" but for "agents" that actually perform tasks—such as software engineering, research, customer service, and analysis—then revenues could scale based on the volume of economic work performed rather than just the number of users (seats/licenses). OpenAI itself noted earlier in the year that enterprise users accounted for over 40% of its revenue and were on track to match consumer revenue by year-end.
This makes for a far more compelling IPO narrative than the simple story of "ChatGPT has a massive user base."
2. Advertising offers OpenAI yet another enormous revenue stream.
OpenAI reported that its advertising pilot generated over $100 million in annualized revenue in less than six weeks earlier this year.
While small compared to the $40 billion figure, this is strategically significant. If ChatGPT evolves into a major discovery and search interface, advertising could eventually become a multi-billion-dollar business.
3. The distribution advantage is immense.
OpenAI’s distribution flows from consumers to developers, then to businesses, and finally to agents.
This cycle is likely what investors are paying for.
But there's a huge problem
Revenue growth isn't the same thing as economic profit.
Frontier AI is extraordinarily capital intensive. OpenAI itself has emphasized that compute is a strategic constraint, while hyperscaler AI infrastructure spending has exploded.
So I'd watch four numbers much more closely than the $40B headline:
Revenue growth + gross margin + inference cost per unit of intelligence + free cash flow
If revenue goes:
$40B → $70B → $110B
but compute costs rise almost proportionally, the IPO could disappoint.
If revenue goes:
$40B → $70B → $120B
while inference costs collapse and gross margins expand, then a $1T valuation could eventually look surprisingly reasonable.
And Anthropic makes this much more interesting
The competitive situation is arguably the biggest IPO risk.
Anthropic is already reporting a roughly $47B annualized run rate, ahead of OpenAI's $40B, and it has been gaining traction particularly in enterprise.
That means investors aren't going to ask:
"Is OpenAI growing?"
They're going to ask:
"Is OpenAI growing faster and more profitably than Anthropic, Google, Meta, xAI and the open-model ecosystem?"
That's a much harder question.
My valuation framework
I'd roughly think about it this way:
Scenario Future revenue Plausible valuation logic
Bear $60–80B $600–900B
Base $100–130B $1.2–1.6T
Bull $150–200B+ $1.8–2.5T+
My base case would be ~$1.2–1.6T if OpenAI enters the public market with $40B+ run-rate revenue and demonstrates continued acceleration.
I would not automatically call $2T irrational—but at that level the IPO becomes a bet that AI agents fundamentally reshape the economics of knowledge work. You're paying today for several years of extraordinary future growth.
The key signal I'd watch
Ironically, Anthropic going public first could help OpenAI rather than hurt it.
If Anthropic successfully lists at something approaching $1.5–2T and trades well, it establishes a public-market valuation framework for frontier AI.
Then OpenAI can effectively say:
"We're at $40B+ revenue, we're growing rapidly, we have the largest consumer distribution, and here's our enterprise/agent opportunity."
If Anthropic's IPO instead gets hammered because investors discover that $100B+ revenue projections don't translate into attractive free cash flow, OpenAI's valuation case gets much harder.
So my bottom line:
$40B revenue makes a $1T OpenAI IPO defensible. It does not, by itself, justify $2T.
For $2T, I would want to see evidence that AI agents are becoming a new software/infrastructure category with rapidly improving unit economics, not simply that companies are spending more on AI during the current boom.
And that's why I think the next 12–18 months could be one of the most consequential periods in the history of the technology industry.
#StockTradingShareChallenge
#我的七夕交易分享
#MyQixiTradingShare

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By realization, your money is gone.
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