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#美股AI概念股普涨
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1️⃣ Recent US stock AI concept stocks purchased on Gate and trading ideas
Recently, in Gate's US stock trading area, I mainly focused on three targets: Micron (MU), Intel (INTC), and a small amount of NVIDIA (NVDA). The specific ideas are as follows:
Micron (MU) — The strongest in storage logic
· Buying point consideration: Micron surged nearly 10% in a single day on June 8, but had been continuously retracing for three weeks prior. Observing that HBM capacity remains in tight supply, Micron's HBM capacity for 2026 has already been fully booked. On June 8, the semi-annual rebound was nearly 6%, with MU leading the storage sector, confirming a short-term sentiment turning point.
· Operation method: Use USDT on Gate to directly buy MU shares, building positions in two steps—first, a small amount within two hours after the rebound starts; second, add more after a slight intraday pullback.
· Risk control setup: Set a stop-loss 5% below the June 5 low point, with the intention to hold until the late June portfolio adjustment window.
Intel (INTC) — Order-driven reversal play
· Logic: Google’s 3 million AI chip orders are scheduled for delivery in 2028, with actual performance realization still distant, but the market has chosen to "believe first, see later." Intel previously experienced severe overselling, and the appearance of massive orders at low levels acts as a catalyst, making short-term odds attractive.
· Operation: Participate with a small position on Gate, adopting a quick in-and-out approach. After Intel surged 11% on the day, I did not chase; the next day, after observing that trading volume did not significantly shrink, I entered at a 3% pullback.
· Note: Do not view this as a long-term hold, more of an event-driven trading.
NVIDIA (NVDA) — Follow-up buying
· NVDA only rose 1.73% that day, underperforming the sector, but as the absolute leader in AI computing power, it exists as a "core holding" in Gate’s US stock portfolio. The core idea: not chasing NVDA’s short-term excess returns, but using Gate’s fragmented trading feature to invest small amounts weekly in USDT, smoothing costs.
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2️⃣ Analysis of AI concept stocks’ future trend under the strong alliance of giants
Short-term (1-3 months): Beware of "order false fire," inevitable divergence
After Intel announced 3 million chip orders and surged 11%, it’s important to note: these orders are scheduled for delivery in 2028, with minimal impact on Intel’s revenue and profit over the next two years. This kind of "distant water" rally to quench "near thirst" is essentially an emotional release in a liquidity-rich environment.
Possible divergence paths in the coming weeks:
· Stocks truly benefiting from current AI capital expenditure (NVIDIA, Broadcom, Micron, TSMC) are expected to maintain strength, especially on the storage side, where HBM capacity shortages are expected to last at least until 2027.
· Stocks relying on long-term orders or riding on concepts may experience sharp corrections if the market adjusts (e.g., CPI/PPI in June exceeding expectations, triggering rate hike concerns).
Mid-term (6-12 months): Energy and connectivity become "hidden champions"
Current discussions focus almost entirely on the chips themselves, but power bottlenecks in AI data centers and connectivity bottlenecks are becoming more critical than the chips:
· Power side: Traditional grid expansion takes 5-7 years, gas turbine orders are scheduled for 2029, GE Vernova has backlog orders worth $150 billion. Meanwhile, Bloom Energy’s fuel cell contracts for power supply only take 55 days, with Q1 revenue up 130%. These targets can be watched on Gate: GE Vernova (GEV), Bloom Energy (BE), with current capital attention far below chip stocks, offering a valuation gap.
· Connectivity side: Lumentum and other optical module manufacturers have gained over 145% this year, but their valuations are still below chip design companies, with room for catch-up.
Long-term (more than 1 year): Signals from Cathie Wood’s operations reveal important clues
Wood significantly reduced TSMC holdings and took profits on AMD in the first five months of 2026, while building positions in Cerebras (wafer-level AI inference chips). This conveys a key judgment: AI computing demand is shifting from large-scale model training to high-frequency, low-cost inference.
This implies:
· The "barbaric growth" phase of training chips may be ending, with growth slowing down.
· Inference chips, edge computing, and low-power solutions will become the next main battleground.
· For individual investors, it is still reasonable to hold major training chip leaders (like NVIDIA), but attention should start to shift toward early opportunities in inference, deploying small positions on platforms like Gate in segments that are not yet fully priced.
Overall assessment
I am optimistic about the medium- to long-term trend of AI concept stocks, but in the next 6 months, I lean more toward segments "beyond computing power"—storage (Micron, SanDisk), power (GEV, BE), optical connectivity (Lumentum)—which may have greater potential than the already soaring chip design giants. Meanwhile, closely watch the May CPI data; if inflation exceeds expectations, tech stocks may face valuation pressure in the short term, making it a good time for phased deployment rather than panic selling.
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The above is a personal investment idea sharing and does not constitute investment advice. The US stock trading feature on the Gate platform provides a convenient cross-market allocation tool, but leverage, options, and other derivatives carry higher risks. Ordinary users are advised to focus mainly on spot trading.
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1️⃣ AI-concept US stocks recently bought on Gate and the trading ideas behind them
In Gate’s US stock trading section, I mainly focused on three targets: Micron (MU), Intel (INTC), and a small amount of Nvidia (NVDA). The specific ideas are as follows:
**Micron (MU) — The hardest storage logic**
- **Buying point thinking:** Micron surged nearly 10% in a single day on June 8, but before that it had already been pulling back for three straight weeks. Seeing that HBM capacity is still in short supply and that Micron has fully booked its 2026 HBM capacity, on June 8, Feeiheng (Fed) rebounded nearly 6%. MU led the storage sector, confirming a short-term sentiment inflection point.
- **How to trade:** On Gate, use USDT to directly buy MU shares, building the position in two entries—first, chase in a small amount within 2 hours after the rebound starts; second, add after a slight intraday pullback.
- **Risk control:** Set a stop-loss 5% below the June 5 low, with the expectation of holding until the end-of-quarter rebalancing window in late June.
**Intel (INTC) — An order-driven reversal bet**
- **Logic:** Google’s order for 3 million AI chips will only be delivered in 2028. Realizing the actual performance is still far off, but the market has chosen to “believe first, verify later.” Intel was previously deeply oversold, and the appearance of a huge order catalyst at low levels makes the short-term odds attractive.
- **Trade plan:** Participate with a small position on Gate using a quick in-and-out approach. After Intel jumped 11% that day, I didn’t chase. The next day, after observing that trading volume wasn’t meaningfully shrinking, I entered at a 3% pullback.
- **Note:** Don’t treat it as a long-term holding—this is more of an event-driven trade.
**Nvidia (NVDA) — Momentum-following allocation**
- NVDA rose only 1.73% on the day, lagging behind the sector. But as the absolute leader in AI computing power, it exists as a “core holding” in Gate’s US stock portfolio. The key idea is not to chase NVDA’s short-term excess returns—instead, use Gate’s fragmented trading features to invest small amounts of USDT every week to smooth out the cost.
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2️⃣ With the big players joining forces, analysis of the future trend for AI-concept stocks
**Short term (1–3 months): Beware of “order-fueled hype,” divergence is inevitable**
After Intel announced orders for 3 million chips and surged 11%, it’s important to note: that order is not delivered until 2028, so the impact on Intel’s revenue and profit over the next two years is almost zero. This kind of “distant water quenches near thirst” rally is essentially a release of sentiment in an environment with abundant liquidity.
Possible divergence paths over the coming weeks:
- Stocks that truly benefit from current AI capital expenditure (Nvidia, Broadcom, Micron, TSMC) are expected to maintain strength—especially on the storage side, where the HBM capacity tightness is likely to continue at least through 2027.
- Stocks that rely on long-dated orders or are merely “riding the concept.” Once the broader market adjusts (for example, June CPI/PPI coming in above expectations triggering concerns about rate hikes), the pullback could be extremely sharp.
**Medium term (6–12 months): Energy and connectivity become “invisible champions”**
Most of the current discussion focuses on chips themselves, but power bottlenecks in AI data centers and connectivity bottlenecks are becoming even tighter constraints than the chips:
- **Power side:** Traditional grid expansion takes 5–7 years, gas turbine orders are already queued until 2029, and GE Vernova’s backlog reaches $150 billion. Meanwhile, Bloom Energy’s fuel cell contracts for power supply can go from signing to delivering power in just 55 days, and Q1 revenue growth is 130%. These names you can watch on Gate—GE Vernova (GEV), Bloom Energy (BE). Right now, capital attention is far lower than for chip stocks, which creates an expectations gap.
- **Connectivity side:** Optical module manufacturers such as Lumentum have already gained more than 145% within the year, but their valuations remain below those of chip design companies, leaving room for catch-up gains.
**Long term (1+ year): Key signals revealed by Cathie Wood’s moves**
Wood significantly reduced holdings of TSMC before the first 5 months of 2026 and realized profits on AMD, while building a position in Cerebras (wafer-level AI inference chips). This suggests a crucial judgment: AI computing demand is shifting from large-scale model training toward high-frequency, low-cost inference.
This means:
- The “barbaric growth” phase of training chips may be coming to an end, and the growth rate will slow.
- Inference chips, edge computing, and low-power solutions will become the next main battlefield.
- For individual investors, heavily weighting training-chip leaders (such as Nvidia) is still reasonable at present, but you should start paying attention to early opportunities on the inference side—using small position sizes on platforms like Gate to build exposure to sub-sectors that have not yet been fully priced.
**Overall judgment**
I’m positive on the medium- to long-term trend of AI-concept stocks, but over the next 6 months I’m more inclined to focus on segments “beyond computing power”—storage (Micron, SanDisk), power (GEV, BE), and optical connectivity (Lumentum). Their potential upside may be greater than that of chip design leaders that have already surged significantly. At the same time, closely watch May CPI data: if inflation comes in above expectations, tech stocks may face valuation pressure in the short term—at that point, it would be the time for phased entries rather than panic selling.
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The above is my personal sharing of investment ideas and does not constitute investment advice. Gate’s USDT trading feature for US stocks provides a convenient cross-market allocation tool, but risks in derivatives such as leverage and options are high. For ordinary users, it is recommended to focus mainly on spot trading.