To The Moon

Big Tech is pouring unprecedented capital into artificial intelligence infrastructure, and the market is watching closely for proof that the spending is paying off. With Microsoft, Alphabet, Amazon, and Meta all scheduled to report earnings next week, investors will scrutinise not just the headline numbers but the trajectory of AI-related expenditure versus measurable returns.So far in 2026, hyperscalers have shown no signs of slowing their build-out. Data centre construction, GPU clusters, and energy partnerships continue at a blistering pace. Nvidia and the broader semiconductor supply chain have ridden this wave higher in April, delivering strong performance as demand signals remain robust. Yet the critical question persists: are we still in the infrastructure phase where costs lead rev

It's a total scam and has been for many years. Still, so many private investors fall for the promises of Elon Musk that get amplified by reckless social media channels that promote the stock endlessly for their own personal profit (always check if money is the motivation for someone to do or say something!). As usual, timelines are missed, lofty promises including deliverables, new revenue streams from Robotaxis/Cybercabs and Optimus robots are missed. All still $0 and will be for 2026 again. When are people finally waking up that Musk is the biggest scam artist in the world? Next up, buy SpaxeX, a company that lost $23 Billion, on promises of a Starship rocket that never even reached orbit so far and data centers in space (an idea that defies physics)! Stay away from it

$Tesla Motors(TSLA)$  $NVIDIA Corp(NVDA)$  $Alphabet(GOOG)$  $S&P 500(.SPX)$   The strategic pivot of Tesla Motors (TSLA) toward semiconductor design and artificial intelligence (AI) justifies its premium valuation, with the success of proprietary chips and autonomous software crucial for maintaining investor trust and future profitability While delivery volumes are recovering, missing consensus estimates underscores the need for tangible progress in energy and robotics, which must now provide a financial cushion to avoid downward revaluation of the stock NVIDIA Corp (NVDA) rem

Q1 Earnings — What Story Are They Selling? 🚗🔋🤖 This quarter isn’t just about numbers — it’s about narrative. Here’s what to watch: 🚗 Cars (Weak Spot) Margins are under pressure from price cuts and competition. Expect this to be downplayed as “short-term strategy”. 🔋 Energy (New Star) High growth, high margin. Tesla will push this hard as the next profit engine. 🤖 AI / Robotaxi (Future Bet) This is the real hype driver. Even average earnings can be offset by strong future promises here. 💬 Overall Narrative “Short-term pain from EVs, but long-term upside from energy + AI.” ⚠️ Reality Check Energy growth is real But still not big enough (yet) to fully replace car profits AI / robotaxi = high potential, but still uncertain 📊 What this means: This is a story vs reality moment Stock reaction wil

On October 6th, a "transformative" partnership between OpenAI and $Advanced Micro Devices (AMD.US)$ drove the latter's share price to surge sharply in a single day, with an intraday peak increase of 36% and settling around 23% at close. After a brief consolidation, AMD's stock price surged again by 11% intraday on October 8th, breaking through $235 to reach a new all-time high. The rapid price spike of AMD has drawn the attention of options investors. Notably, AMD's Implied Volatility (IV) is now at the 98th percentile of its historical range, suggesting a potential decline in IV in the future. This presents a major opportunity for short-side option traders. ⚙️ The "Epic" Collaboration with OpenAI AMD and OpenAI signed a four-year GPU supply agreement for a computational capacity of 6 giga

My stock in focus today is $Texas Instruments(TXN)$ . The key takeaway from this earnings is not just the beat, but the strength across segments—industrial up over 30% and data center nearly 90% YoY, pointing to both cyclical recovery and AI-driven demand. It also suggests demand is broadening beyond hyperscalers into real economy use. Unlike names like $NVIDIA(NVDA)$ , TI plays a quieter but critical role in the AI stack through analog chips. As data centers scale, demand for power management and signal conversion rises alongside compute, making TI a “picks and shovels” beneficiary. This positioning is typically more resilient across cycles. With guidance above expectations and inventories normalizing,

This is the first time Google is clearly trying to close the loop across the entire AI stack. The key shift is not just “better chips” or “better models”, but alignment between training → inference → enterprise workflows (agents). --- 1) What Google actually changed (and why it matters) Split TPU into TPU 8t (training) + TPU 8i (inference) → mirrors how AI demand is evolving (training ≠ deployment anymore)  Big focus on inference efficiency (cost + latency) → critical because real-world AI = mostly inference, not training Launch of Gemini Enterprise (agent platform) → not just chat, but AI agents that execute workflows  Early enterprise traction (e.g. Home Depot, PepsiCo, eBay) → signals real GTM push, not just demos  👉 In short: Google is moving from “model company” → full-

You are right to question this. A clean break above $300 for Advanced Micro Devices is technically powerful, but the risk-reward has clearly tightened after such a sharp run. --- 1) What the market is pricing in now The move is not just momentum. It reflects a narrative shift: AMD is no longer “late to AI” → now seen as credible #2 to Nvidia MI-series GPUs gaining traction in: mid-tier cloud deployments cost-sensitive inference workloads Ecosystem expansion (hyperscalers, open software stack) Meanwhile, strength in Micron Technology reinforces: AI demand is broadening beyond GPUs Memory + storage + compute moving together 👉 This is why the breakout had fuel. --- 2) Why risk/reward is narrowing (a) Expectations have moved faster than fundamentals At $300+, AMD is now pricing: sustained MI30

Tesla — inflection or narrative stretch? The reaction you describe is consistent with a market at a narrative–execution crossroads. The earnings print was “good enough”, but the call raised forward uncertainty, which is why price reversed. --- 1) What actually changed this quarter Positive Revenue beat keeps core demand intact Reinforced pivot toward: Robotaxi Optimus robotics $25B capex signals serious commitment to AI/autonomy scale Negative (the real driver) HW3.0 limitation admission: Undercuts prior FSD expectations Introduces upgrade liability / trust risk Capex expansion → near-term margin compression 👉 Translation: Narrative strengthened long term, credibility weakened short term --- 2) When does the transformation realistically materialise? Be careful here. The market often pulls

Apple in the AI era Apple does not need a model builder like OpenAI or infra leader like Nvidia. It needs a product integrator. AI will be won at the interface layer: on-device intelligence privacy-first design seamless ecosystem experience John Ternus fits this. His Apple Silicon track record shows strength in hardware–software integration, which is exactly Apple’s edge. Risk: Apple moves too slowly while rivals iterate fast, and users default to external AI. Bottom line: Ternus can drive a new growth curve if he makes AI invisible, embedded, and daily-use. Otherwise, Apple risks becoming polished, but secondary.

OCBC has arguably become the most "promising" pick of the trio for Q1. While it traditionally played second fiddle to DBS in terms of aggressive growth, its conservative management is paying off in the current environment. Why it looks promising: OCBC’s share price recently touched record highs (surpassing S$22), making it the standout performer YTD. It is benefiting from the strongest loan growth among the three (nearly 7% YoY), fueled by a strategic push into ASEAN corporate lending and a resilient Singapore mortgage book.  The "Secret Sauce": Unlike its peers, OCBC has managed to keep its asset quality exceptionally clean, with Non-Performing Loans (NPLs) hitting multi-quarter lows. With its market cap crossing the S$100 billion mark, it is no longer just a "value play" but a pri

From my perspective, $NVIDIA(NVDA)$ can still reach new highs, but the path is less one-sided. The market is questioning its “one architecture fits all” GPU model, especially with Alphabet pushing specialized TPUs. Still, NVIDIA’s real moat is its full-stack ecosystem (CUDA, developer lock-in), so I see competition as gradual margin pressure, not a leadership break. On $Advanced Micro Devices(AMD)$ breaking $300, the re-rating feels justified but partly narrative-driven. AMD now captures both CPU resurgence and GPU spillover demand, which is powerful—but expectations are rising quickly. I see this as early-stage AI infrastructure upside, though I wouldn’t chase after now. For AI rally, capex trends lik

Quick thoughts on $TSLA Q1 2026 Earnings: It was a very impressive earnings report showing increasing gross margins, increasing demand, strong order backlog, FSD subscriptions, while topping Wall Street estimates. While top and bottom line beats are great, what matters is management commentary and outlook. Musk’s hesitation on Robotaxi/CyberCab and Unsupervised FSD showed a bit of uncertainty in timing. That was enough to fade the rally, retracing the entire post earnings rally. Now it looks like Tesla needs the rest of 2026 to scale Robotaxi as they are focusing on safety as a top priority to avoid accidents. Shared with subscribers that we don’t expect a V shape recovery due to the lack of significant Robotaxi scale, market skepticism, and many macro related headwinds. So this will most