To The Moon

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

$Micron Technology(MU)$   $SK hynix(SKHY)$   Buying the dip now, both Micron (MU) and SK Hynix (SKHY) likely to dip further towards the $880 mark. Micron shares were down 4.4% at $873.70 in premarket trading. A slide that began at the start of the week on news that China's CXMT was developing a new memory chip has been compounded by fears about the wider AI trade. South Korean memory companies Samsung Electronics and SK Hynix were even harder hit, dropping 9.5% and 11%, respectively, in local trading on Thursday.

$Micron Technology(MU)$   Showing how unusual the quarter was, Micron's adjusted free cash flow (the cash left after capital spending) reached $33.2 billion in the fourth quarter of fiscal 2026 (the period ended Sept. 3, 2026). And it's been climbing fast, from $803 million a year earlier and $18.3 billion in fiscal Q3. For all of fiscal 2026, free cash flow totaled $62.3 billion -- up from $3.7 billion in fiscal 2025. In other words, eight years of buybacks now equal around 24% of the free cash flow Micron generated during one quarter.

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

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 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

$NVIDIA(NVDA)$  | 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

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

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

$NVIDIA(NVDA)$ 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 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

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

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

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

$Direxion Daily Semiconductors Bull 3x Shares(SOXL)$ 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

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

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

$Micron Technology(MU)$   $SK hynix(SKHY)$   Buying the dip now, both Micron (MU) and SK Hynix (SKHY) likely to dip further towards the $880 mark. Micron shares were down 4.4% at $873.70 in premarket trading. A slide that began at the start of the week on news that China's CXMT was developing a new memory chip has been compounded by fears about the wider AI trade. South Korean memory companies Samsung Electronics and SK Hynix were even harder hit, dropping 9.5% and 11%, respectively, in local trading on Thursday.

$Micron Technology(MU)$   Showing how unusual the quarter was, Micron's adjusted free cash flow (the cash left after capital spending) reached $33.2 billion in the fourth quarter of fiscal 2026 (the period ended Sept. 3, 2026). And it's been climbing fast, from $803 million a year earlier and $18.3 billion in fiscal Q3. For all of fiscal 2026, free cash flow totaled $62.3 billion -- up from $3.7 billion in fiscal 2025. In other words, eight years of buybacks now equal around 24% of the free cash flow Micron generated during one quarter.