To The Moon

$先科电子(SMTC)$  Earnings: The AI Data Center Inflection Is Accelerating $SMTC delivered a much stronger quarter than many expected. Revenue came in at $341.9M vs $328M guidance, with EPS at $0.71 vs $0.61 expected. But the real story is not just the beat — it is the acceleration in Data Center. Data Center revenue trajectory: • Q1: $71.6M • Q2: $100M+ • Q3 guidance: ~$145M That represents roughly 45% sequential growth and a significant year-over-year acceleration. Management also highlighted that FY27 Data Center capacity is already fully booked, while FY28 demand visibility has exceeded 70%. This shows hyperscaler demand for AI infrastructure continues to expand. The biggest catalyst: 1.6T optical connectivity. $SMTC reached 1.6T qualification

‌$英伟达(NVDA)$  ‌AI dominance is creating a massive opportunity well beyond Nvidia itself as billions flow through foundry, HBM, testing, packaging and server assembly Here’s who has the most exposure to Nvidia today: •‌$台积电(TSM)$  ‌37% •‌$SK海力士(SKHY)$  ‌27% •‌$美光科技(MU)$  ‌14% •‌$泰瑞达(TER)$  ‌8% •‌$日月光半导体(ASX)$  ‌3% •‌$Fabrinet(FN)$  ‌1% •‌$艾马克技术公司(AMKR)$  ‌1% •‌$思科(CSCO)$  ‌

‌$英伟达(NVDA)$  ‌’s earnings report is not just about one company. It is a report card for the entire AI infrastructure cycle. Wall Street expects another record-breaking quarter: 📌 Revenue estimate: ~$92 billion 📌 EPS estimate: ~$2.09 📌 Revenue growth: ~97% YoY 📌 EPS growth: ~99% YoY 📌 Next quarter revenue expectation: above $104 billion But the market is not asking whether NVIDIA can beat estimates. The market is asking: Can NVIDIA continue to grow at an extraordinary pace? 1. Data Center Demand Remains The Key AI infrastructure investment is still expanding. ‌$微软(MSFT)$  ‌,‌$亚马逊(AMZN)$  ‌,‌$谷歌(GOOG)$  </

Especially the swing trading and small-position opportunities I shared in the community. Yesterday, market panic reached extreme levels. Many quality companies experienced sharp declines due to overall sentiment rather than a change in fundamentals. During moments of fear, we don’t just see risk — we see opportunities created by emotional selling. That’s why I shared a list of stocks in the community with solid fundamentals but significant short-term pullbacks, allowing members to consider small-position entries: ‌$Applied Optoelectronics Inc.(AAOI)$  ‌105 ‌$AXT Inc(AXTI)$  ‌63 ‌$闪迪(SNDK)$  ‌1450 ‌$NEBIUS(NBIS

Since the beginning of this year, my account has gained around 1,000 new followers from Hong Kong. I truly appreciate every one of you for your support and trust. I don’t often publicly share my Hong Kong stock strategies, but many Hong Kong investors have reached out to me through the community, and I’m always happy to share my views on the market, industries, and investment opportunities. The Hong Kong market continues to offer many opportunities, especially in areas such as AI, semiconductors, and technology supply chains. Earlier this year, we started building a position in ‌$南方东英SK海力士每日杠杆最多 (2x) 产品(07709)$  ‌ at an early stage. At that time, it was one of the few leveraged ETFs globally related to SK Hynix. Beyond ETFs, our researc

Asian markets faced broad pressure today, with both Japan and South Korea closing lower. U.S. futures also showed weakness overnight as risk appetite declined. The biggest sell-off came from the memory sector. $005930 (Samsung Electronics) became the focus of the market after its shareholder return plan failed to meet investor expectations. While Samsung announced a record-scale return program, investors were looking for a more aggressive buyback strategy rather than a dividend-heavy approach. The disappointment triggered a sharp decline in Samsung shares and pressured the entire memory sector. The weakness also spread across other memory names: ‌$美光科技(MU)$  ‌— Micron Technology ‌$SK海力士(SKHY)$  ‌—

Over the past two years, investors have focused primarily on AI models, large language models, and software applications. However, a deeper challenge is becoming increasingly clear: The biggest bottleneck for AI is no longer algorithms — it is physical infrastructure. The future of AI depends not only on smarter models, but on the ability to provide massive amounts of computing power, memory capacity, networking speed, and energy. AI is entering a new infrastructure investment cycle, similar to the early stages of the internet. The entire AI ecosystem can be divided into several critical layers: 1. AI Compute — The Engine of the AI Era Training and running advanced AI models require enormous computing power. Key players: ‌$英伟达(NVDA)$  ‌ The l

Recently, I’ve received many portfolio updates from new followers in Singapore, and I noticed something interesting: A large number of Singaporean investors hold the three major local banks: ‌$星展集团控股(D05)$  ‌ ‌$华侨银行(O39)$  ‌ ‌$大华银行(U11)$  ‌ These companies reflect the unique characteristics of the Singapore market: Stability, lower volatility, and strong dividend returns. For long-term investors, high-quality bank stocks can provide steady cash flow and portfolio stability. At the same time, I’m glad to see that many investors have also started adding high-quality technology stocks based on my suggestions. This creates a more balanc

‌$Moderna, Inc.(MRNA)$  ‌

‌$迈威尔科技(MRVL)$  ‌ has reached a custom AI chip agreement with Google, marking another major step in the expansion of AI-specific silicon.