To The Moon

The three indices diverged on Tuesday: the $Dow Jones(.DJI)$ rose 1.02 per cent to 52,495.88; the $S&P 500(.SPX)$ rose 0.28 per cent to 7,712.57; the $NASDAQ(.IXIC)$ was nearly unchanged, closing down 0.02 per cent at 26,424.82. The 10-year Treasury yield settled at 5.12 per cent. The Dow–Nas

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Mengniu Group and YXT.com Group Holding Limited ( $云学堂(YXT)$ ), jointly developed a Smart Learning Platform that has expanded to serve Mengniu and its upstream and downstream ecosystem users since launch. It has become an important foundation for Mengniu’s digital transformation in human resources. Drawing on YXT’s expertise in AI, intelligent knowledge systems, and enterprise learning, the two companies are integrating AI into knowledge creation, learning operations, and performance evaluation to explore new ways of strengthening organizational capabilities through digitalization and intelligent technologies. For large enterprises, knowledge must not only be captured and preserved but also flow efficiently across departments, organizational levels

The market: AI shares rose first, then earnings moved the question from demand to returns The $Invesco QQQ(QQQ)$ gained 1.05 per cent to US$725.20 on Wednesday, while the $S&P 500(.SPX)$ rose 0.58 per cent to 7,757.17. $SpaceX(SPCX)$ gained 7.79 per cent, $SUPER MICRO COMPUTER INC(SMCI)$ 9.55 per cent, N $NVIDIA(NVDA)$ 2.54 per cent and $Advanced Micro Devices(AMD)$ 3.36 per cent. These were regular-session moves before Meta and Tesla repor

$NVIDIA(NVDA)$ rose 2.54% after CEO Jensen Huang outlined a broader vision for the AI economy, spanning energy, computing infrastructure, AI factories, models and applications. One part of this vision deserves more attention: telecommunications. Most AI investment discussions focus on massive data centres packed with advanced GPUs. But as AI becomes part of everyday services, could the next opportunity involve bringing computing closer to users through telecom networks? Nvidia’s next growth opportunity may not be limited to building bigger data centres. It could also involve expanding where AI computing happens. 📡 1. Why Telecom Networks Could Matter AI applications do not all work in the same way. Some tasks can be processed in large, centra

$NVIDIA(NVDA)$  | AI Infrastructure | Telecom Edge Computing Nvidia’s next growth opportunity may extend beyond the giant data centres powering today’s AI boom. At GTC Berlin, Jensen Huang outlined a broader vision of the AI economy, spanning energy, computing, AI factories, models and applications. One particularly interesting development is the potential transformation of telecommunications networks into distributed AI computing platforms. This could open a new market for Nvidia, bringing AI processing closer to users rather than concentrating almost everything in centralised data centres. But there is an important question: Can telecom companies turn their existing networks into profitable AI infrastructure quickly enough to create a

Nvidia rose 2.54% after Jensen Huang outlined a much bigger AI economy spanning energy, compute, AI factories, models and applications. $NVIDIA(NVDA)$ But one part caught my attention: Telecom networks. The first AI infrastructure boom concentrated enormous computing power inside hyperscale data centers. The next phase could push intelligence outward, closer to where data is actually created and consumed. Phones. Factories. Robots. Autonomous machines. Enterprise networks. 5G infrastructure. If that happens, Nvidia's opportunity may become considerably larger than simply selling more GPUs to hyperscalers. 🔵 WHY TELECOM AI COULD MATTER Traditional cloud AI works largely like this: Device → Network → Data Center → AI processing → Net

That 50% threshold makes me much less willing to call the Tesla-SpaceX merger a done deal. It is not 50% of votes cast, but 50% of ALL Tesla shares, meaning abstentions and shareholders who simply do not vote effectively make the hurdle harder to clear. Musk himself called it “quite a high hurdle”, while the independent committees have not even agreed on transaction terms yet. I think the deal is credible and clearly being explored seriously, but “inevitable” is too strong. The eventual valuation and exchange ratio will be crucial. If Tesla shareholders feel they are giving SpaceX too generous a valuation, even investors who like the strategic AI, robotics and infrastructure synergies could reject it. For me: serious possibility, yes. Certainty, definitely not yet.

Can the Chip Rebound Continue Without Nvidia Leading? Yes $Advanced Micro Devices(AMD)$ is transitioning from an Nvidia alternative proxy to a standalone rack-scale AI platform story. While Nvidia ( $NVIDIA(NVDA)$ ) remains the primary benchmark for monolithic GPU hardware, AMD is carving out an independent growth trajectory centered on rack-scale architecture and enterprise diversification: The Helion & Rack-Scale Shift: AMD's introduction of integrated rack-scale architectures (such as Helion for agentic AI workloads) establishes that hyper-scalers are buying complete AI data center solutions rather than just discrete silicon. This reduces direct "GPU-to-GPU" pricing friction against Nvidia's Black

You are superstar ⭐️

I see the 50% approval threshold as a significant hurdle. Even if Elon Musk supports the $Tesla Motors(TSLA)$ $SpaceX(SPCX)$ merger, he still needs to convince shareholders that the deal will create real long-term value. This makes the outcome far from certain. Personally, I think valuation and potential dilution are the key concerns. SpaceX’s AI growth and Starlink business are attractive, but Tesla shareholders need to understand what they will receive in return. Strong business synergies alone do not guarantee a good deal if the valuation or exchange ratio is unfavourable. I am optimistic about Musk’s AI ecosystem

The indices: Dow up, Nasdaq flat, a split that maps onto earnings week The three indices diverged on Tuesday: the $Dow Jones(.DJI)$ rose 1.02 per cent to 52,495.88; the $S&P 500(.SPX)$ rose 0.28 per cent to 7,712.57; the $NASDAQ(.IXIC)$ was nearly unchanged, closing down 0.02 per cent at 26,424.82. The 10-year Treasury yield settled at 5.12 per cent. The Dow–Nasdaq split tracks the shape of this week's reporting calendar: technology names started spreading risk before the numbers are in, some moving forward, some pulling back. Memory: the CXMT overhang still has not cleared

$Direxion Daily Semiconductors Bull 3x Shares(SOXL)$ happily allowed put option to be assigned at $95. Pocketed premium, gained when SOXL rebound, now selling covered call to pocket premium again until call gets assign

GTC can strengthen my conviction in Nvidia’s long-term story, but I would still want earnings numbers before becoming significantly more bullish. Jensen Huang’s keynote could provide important signals on the next computing roadmap, AI infrastructure demand, agents and physical AI. However, announcements and partnerships ultimately need to translate into revenue, margins and sustained data-centre growth. The recent pullback being driven by leveraged-position unwinding rather than deteriorating fundamentals would be encouraging, but valuation still matters after Nvidia’s strong run. So I’m watching GTC for the direction of the next growth cycle, while earnings remain the real confirmation. A compelling roadmap may improve sentiment quickly, but numbers showing strong demand and monetisation

$NVIDIA(NVDA)$ is back in the spotlight, but this time the question is bigger than whether Jensen Huang can deliver another exciting presentation. Nvidia fell 0.29% on Tuesday to $216.47 as investors looked ahead to GTC Berlin, running from October 20 to 22. Huang’s keynote is expected to cover accelerated computing, AI infrastructure, open-source models, AI agents and physical AI. These are important areas for the next stage of AI development. However, after a powerful run in AI-related stocks, investors are increasingly asking a different question: How much of the future growth is already reflected in today’s share prices? I think that is the real issue facing Nvidia. 💡 1. The AI Story Is Expanding Beyond Chatbots The first phase of the AI

Nvidia rebounded 1.38%, with Marvell +4.06%, AMD +1.76% and Broadcom +1.78% as attention shifts to Jensen Huang's 21 October GTC Berlin keynote. NVDA is around $217. But I do not think another impressive GPU announcement is enough to move the stock materially. The market already believes Nvidia has great chips. What it now wants is proof that AI demand is broadening beyond hyperscaler training into inference, agents, enterprise AI and physical AI. That is what could reignite the trade. 🔵 THE NUMBER BEHIND THE KEYNOTE I am watching for evidence that falling inference costs are creating more total demand, rather than simply making existing AI workloads cheaper. That is the next Nvidia flywheel: Better compute → cheaper inference → more AI applications → more tokens → more infrastructure dema

AI chip stocks are moving higher ahead of Nvidia CEO Jensen Huang’s October 21 keynote at GTC Berlin. Nvidia gained 1.38%, Marvell climbed 4.06%, AMD rose 1.76%, and Broadcom advanced 1.78%. The market is looking for fresh signals about accelerated computing, AI infrastructure, AI agents and physical AI. But rather than focusing only on which company launches the most powerful chip, I think another question deserves attention: What happens when AI becomes cheaper to run? Lower inference costs could make AI applications more economical for businesses, potentially expanding demand beyond today’s biggest technology companies. That could create opportunities across the semiconductor industry, although each company faces different challenges. 🟢 $NVIDIA(NVD

AI chip stocks are rebounding ahead of Nvidia CEO Jensen Huang’s October 21 keynote at GTC Berlin. Nvidia gained 1.38%, Marvell rose 4.06%, AMD climbed 1.76%, and Broadcom advanced 1.78%. The market is watching for new signals about AI infrastructure, accelerated computing, AI agents and physical AI. But there is a bigger question behind the excitement: Can the next phase of AI investment deliver enough business value to justify the enormous spending? Rather than focusing only on Nvidia, it is worth examining how four chipmakers could benefit from different parts of the AI expansion. 🔹 1. $NVIDIA(NVDA)$ :Can AI Demand Keep Expanding? Nvidia remains at the centre of the AI accelerator market, benefiting from demand for GPUs, networking and its

The market: Amazon led as QQQ rebounded faster than SPY $Invesco QQQ(QQQ)$ rose 1.21 per cent to US$718.36 on Monday, $SPDR S&P 500 ETF Trust(SPY)$ gained 0.42 per cent to US$766.48, and the $S&P 500(.SPX)$ added 0.41 per cent to 7,690.73. Amazon rose 4.98 per cent, lifting technology and the data-centre supply chain and giving the Nasdaq-100 its best performance in almost a month. The advance went beyond one large-cap rebound. Money spread from Amazon into memory, semiconductors and networking equipment, showing that Friday's selling had cooled. The questions around rates and investment returns remain. Result

Memory Crushed, AI Chips Rallied. Is Semiconductor Money Rotating Internally? The Answer Came Three Days Later Written Saturday 17 Oct, SGT, using Friday's US closes. First, check the date on the numbers The figures in this topic are real, but they come from Tuesday, Oct 13. That day Nvidia closed up 0.97% at $228.52, AMD rose 1.90% to $605.53 and Intel gained 1.44% to $102.81. Micron fell 3.62% to $953.19, its fourth straight loss, after China's CXMT said it plans to launch a 4F2 DDR5 server memory module by year-end. On that one session, it did look like rotation: money leaving memory and moving into compute. Now look at what happened over the next three sessions. The scoreboard: Tuesday close to Friday close - Nvidia: $228.52 to $214.13, -6.30% - Micron: $953.19 to $878.84, -7.80% - Bro

The three indices diverged on Tuesday: the $Dow Jones(.DJI)$ rose 1.02 per cent to 52,495.88; the $S&P 500(.SPX)$ rose 0.28 per cent to 7,712.57; the $NASDAQ(.IXIC)$ was nearly unchanged, closing down 0.02 per cent at 26,424.82. The 10-year Treasury yield settled at 5.12 per cent. The Dow–Nas

The market: AI shares rose first, then earnings moved the question from demand to returns The $Invesco QQQ(QQQ)$ gained 1.05 per cent to US$725.20 on Wednesday, while the $S&P 500(.SPX)$ rose 0.58 per cent to 7,757.17. $SpaceX(SPCX)$ gained 7.79 per cent, $SUPER MICRO COMPUTER INC(SMCI)$ 9.55 per cent, N $NVIDIA(NVDA)$ 2.54 per cent and $Advanced Micro Devices(AMD)$ 3.36 per cent. These were regular-session moves before Meta and Tesla repor

Nvidia rose 2.54% after Jensen Huang outlined a much bigger AI economy spanning energy, compute, AI factories, models and applications. $NVIDIA(NVDA)$ But one part caught my attention: Telecom networks. The first AI infrastructure boom concentrated enormous computing power inside hyperscale data centers. The next phase could push intelligence outward, closer to where data is actually created and consumed. Phones. Factories. Robots. Autonomous machines. Enterprise networks. 5G infrastructure. If that happens, Nvidia's opportunity may become considerably larger than simply selling more GPUs to hyperscalers. 🔵 WHY TELECOM AI COULD MATTER Traditional cloud AI works largely like this: Device → Network → Data Center → AI processing → Net

$NVIDIA(NVDA)$ rose 2.54% after CEO Jensen Huang outlined a broader vision for the AI economy, spanning energy, computing infrastructure, AI factories, models and applications. One part of this vision deserves more attention: telecommunications. Most AI investment discussions focus on massive data centres packed with advanced GPUs. But as AI becomes part of everyday services, could the next opportunity involve bringing computing closer to users through telecom networks? Nvidia’s next growth opportunity may not be limited to building bigger data centres. It could also involve expanding where AI computing happens. 📡 1. Why Telecom Networks Could Matter AI applications do not all work in the same way. Some tasks can be processed in large, centra

Mengniu Group and YXT.com Group Holding Limited ( $云学堂(YXT)$ ), jointly developed a Smart Learning Platform that has expanded to serve Mengniu and its upstream and downstream ecosystem users since launch. It has become an important foundation for Mengniu’s digital transformation in human resources. Drawing on YXT’s expertise in AI, intelligent knowledge systems, and enterprise learning, the two companies are integrating AI into knowledge creation, learning operations, and performance evaluation to explore new ways of strengthening organizational capabilities through digitalization and intelligent technologies. For large enterprises, knowledge must not only be captured and preserved but also flow efficiently across departments, organizational levels

$NVIDIA(NVDA)$  | AI Infrastructure | Telecom Edge Computing Nvidia’s next growth opportunity may extend beyond the giant data centres powering today’s AI boom. At GTC Berlin, Jensen Huang outlined a broader vision of the AI economy, spanning energy, computing, AI factories, models and applications. One particularly interesting development is the potential transformation of telecommunications networks into distributed AI computing platforms. This could open a new market for Nvidia, bringing AI processing closer to users rather than concentrating almost everything in centralised data centres. But there is an important question: Can telecom companies turn their existing networks into profitable AI infrastructure quickly enough to create a

The indices: Dow up, Nasdaq flat, a split that maps onto earnings week The three indices diverged on Tuesday: the $Dow Jones(.DJI)$ rose 1.02 per cent to 52,495.88; the $S&P 500(.SPX)$ rose 0.28 per cent to 7,712.57; the $NASDAQ(.IXIC)$ was nearly unchanged, closing down 0.02 per cent at 26,424.82. The 10-year Treasury yield settled at 5.12 per cent. The Dow–Nasdaq split tracks the shape of this week's reporting calendar: technology names started spreading risk before the numbers are in, some moving forward, some pulling back. Memory: the CXMT overhang still has not cleared

Nvidia rebounded 1.38%, with Marvell +4.06%, AMD +1.76% and Broadcom +1.78% as attention shifts to Jensen Huang's 21 October GTC Berlin keynote. NVDA is around $217. But I do not think another impressive GPU announcement is enough to move the stock materially. The market already believes Nvidia has great chips. What it now wants is proof that AI demand is broadening beyond hyperscaler training into inference, agents, enterprise AI and physical AI. That is what could reignite the trade. 🔵 THE NUMBER BEHIND THE KEYNOTE I am watching for evidence that falling inference costs are creating more total demand, rather than simply making existing AI workloads cheaper. That is the next Nvidia flywheel: Better compute → cheaper inference → more AI applications → more tokens → more infrastructure dema

$NVIDIA(NVDA)$ is back in the spotlight, but this time the question is bigger than whether Jensen Huang can deliver another exciting presentation. Nvidia fell 0.29% on Tuesday to $216.47 as investors looked ahead to GTC Berlin, running from October 20 to 22. Huang’s keynote is expected to cover accelerated computing, AI infrastructure, open-source models, AI agents and physical AI. These are important areas for the next stage of AI development. However, after a powerful run in AI-related stocks, investors are increasingly asking a different question: How much of the future growth is already reflected in today’s share prices? I think that is the real issue facing Nvidia. 💡 1. The AI Story Is Expanding Beyond Chatbots The first phase of the AI

The market: Amazon led as QQQ rebounded faster than SPY $Invesco QQQ(QQQ)$ rose 1.21 per cent to US$718.36 on Monday, $SPDR S&P 500 ETF Trust(SPY)$ gained 0.42 per cent to US$766.48, and the $S&P 500(.SPX)$ added 0.41 per cent to 7,690.73. Amazon rose 4.98 per cent, lifting technology and the data-centre supply chain and giving the Nasdaq-100 its best performance in almost a month. The advance went beyond one large-cap rebound. Money spread from Amazon into memory, semiconductors and networking equipment, showing that Friday's selling had cooled. The questions around rates and investment returns remain. Result

AI chip stocks are rebounding ahead of Nvidia CEO Jensen Huang’s October 21 keynote at GTC Berlin. Nvidia gained 1.38%, Marvell rose 4.06%, AMD climbed 1.76%, and Broadcom advanced 1.78%. The market is watching for new signals about AI infrastructure, accelerated computing, AI agents and physical AI. But there is a bigger question behind the excitement: Can the next phase of AI investment deliver enough business value to justify the enormous spending? Rather than focusing only on Nvidia, it is worth examining how four chipmakers could benefit from different parts of the AI expansion. 🔹 1. $NVIDIA(NVDA)$ :Can AI Demand Keep Expanding? Nvidia remains at the centre of the AI accelerator market, benefiting from demand for GPUs, networking and its

AI chip stocks are moving higher ahead of Nvidia CEO Jensen Huang’s October 21 keynote at GTC Berlin. Nvidia gained 1.38%, Marvell climbed 4.06%, AMD rose 1.76%, and Broadcom advanced 1.78%. The market is looking for fresh signals about accelerated computing, AI infrastructure, AI agents and physical AI. But rather than focusing only on which company launches the most powerful chip, I think another question deserves attention: What happens when AI becomes cheaper to run? Lower inference costs could make AI applications more economical for businesses, potentially expanding demand beyond today’s biggest technology companies. That could create opportunities across the semiconductor industry, although each company faces different challenges. 🟢 $NVIDIA(NVD

Something very interesting is happening inside semiconductors. Memory stocks are being crushed. Yet Nvidia, AMD and Intel have shown relative strength. At first glance, that looks contradictory. If investors are worried about AI spending, should the entire semiconductor complex not be falling together? I do not think so. The market is beginning to separate AI compute scarcity from memory scarcity. And that distinction could determine where I put my next dollar. 🔥 WHY MONEY IS ROTATING FROM MEMORY INTO COMPUTE For much of 2026, the semiconductor trade was beautifully simple: AI demand rises → chips become scarce → memory becomes scarce → pricing rises → margins explode → almost everything semiconductor goes up. That simplicity is disappearing. Memory now faces a new question from China's CX

Asian semiconductor stocks just experienced a sharp selloff, with SK hynix, Samsung and Kioxia coming under heavy pressure as investors reassessed future memory supply and pricing power. Now, ASML is set to report its Q3 earnings, offering another important signal about the future of the AI infrastructure cycle. The key question is not simply how much ASML earned this quarter, but whether chipmakers are still willing to spend heavily on capacity they may not need until 2027 or 2028. ASML's fundamentals remain strong. In Q2, the company reported €9.33 billion in revenue, a 54% gross margin and approximately €2.9 billion in net income. Management previously guided for Q3 revenue of €11 billion–€12 billion and gross margins of 55%–57%. Analysts surveyed by Visible Alpha expect roughly €11.71

The indices: barely moved, but chips and memory went in opposite directions The three indices were nearly flat on Tuesday: the $S&P 500(.SPX)$ fell 0.02 per cent to 7,805.45; the $NASDAQ(.IXIC)$ fell 0.15 per cent to 27,204.38; and the $Dow Jones(.DJI)$ fell 0.35 per cent to 51,670.10. The 10-year Treasury yield eased from 5.24 per cent to 5.22 per cent. The compute chips that had been falling since last Thursday bounced: $NVIDIA(NVDA)$ rose 0.97 per cent to US$228.52 and AMD rose 1.90 per cent to US$605.53, with the specific AMD driver in the next sect

Last Thursday looked ugly for semiconductors. AMD fell 3.9% to $620.68. Nvidia lost 2.94%, Broadcom dropped 4.35%, while Intel fell 5.34%. AMD then weakened again on Friday, closing around $608. Normally, when stocks fall this hard, I ask whether the fundamental story changed. This time, Lisa Su gave us an unusually useful answer. AMD is planning a substantial increase in supply, yet management still sees demand exceeding what the industry can currently produce. Advanced wafers, HBM, packaging and other parts of the AI supply chain remain constrained. That creates a fascinating divergence: The stocks are pricing fear while the supply chain is still pricing scarcity. For me, that is not automatically a sell signal. It is a signal to become much more selective. Why Did Chips Sell Off Then? T

Comparing the changes in open interest on October 8 with October 7, the market’s collective positioning was far from aggressive: put open interest in crude oil and the Nasdaq-100 expanded significantly faster than call open interest, suggesting that market participants were paying for downside protection. Gold, by contrast, continued to see calls dominate both open interest and trading volume. Increases in options open interest can reflect hedging, premium collection by option sellers, or spread strategies, making them more useful for assessing risk appetite and identifying key areas of positioning. WTI Crude Oil: Stronger Demand for Downside Protection, with a Cautious Near-Term Outlook The defensive positioning in crude oil options strengthened further on October 8. Put open interest ros

Chip stocks sell off but AMD says demand still outstrips supply but does that apply to all the big chip makers? or only certain genre of chip makers are seeing demand outstripping supply? In this article, we would like to discuss a comprehensive institutional analysis of sector divergence, sub-genre supply dynamics, and investment strategies for $NVIDIA(NVDA)$, $Advanced Micro Devices(AMD)$, $Broadcom(AVGO)$, and $Micron Technology(MU)$. 1. The Semiconductor Sell-Off vs. Fundamental Reality The global semiconductor sector has recently experienced sharp equity pullbacks driven by macroeconomic tightening, rising geopolitical

Nvidia authorized its historic $235 billion buyback program, it created a massive, structural safety net for its stock. The behavior of a buyback would be when a stock trades at or near all-time highs and a company implements a massive buyback, the entity "buying the highs" is primarily the stock itself, in this case, it is $NVIDIA(NVDA)$, we would also see alongside institutional forces which would be seen to mechanically required to follow. 1. Introduction: The Magnitude of $235 Billion Corporate capital allocation reaches rare milestones when scale, profitability, and market valuation intersect at historic magnitudes. Nvidia’s announcement of an additional $150 billion share buyback authorization, cementing a total remaining repurchase capacity

The indices: a weak jobs report, and all three still closed higher All three indices closed higher on Friday: the $NASDAQ(.IXIC)$ Composite rose 1.19 per cent to 27,190.86, having reached 27,353.68 at its intraday peak; the $S&P 500(.SPX)$ rose 0.73 per cent to 7,722.72; and the $Dow Jones(.DJI)$ rose 0.49 per cent to 51,176.96. The September employment report came out that morning: non-farm payrolls added 29,000, where the market had looked for somewhere between 85,000 and 90,000, and the unemployment rate went from 4.1 per cent in August to 4.2 per cent, where a flat reading had been expected. The previous tw