To The Moon

U.S. and Global Market Updates $NVIDIA(NVDA)$   Key Points Europe’s largest rare earth magnet plant, Neo’s new facility in Narva on Russia’s border, is ramping up toward supplying roughly 10% of EU demand, signalling a strategic push to reduce dependence on Chinese critical minerals. Japanese government bond yields have climbed to their highest levels since the late 1990s–2000s, sharpening the Bank of Japan’s dilemma between continuing rate normalization and protecting growth in an already heavily indebted economy. Asia-Pacific equities mostly gained, led by a strong rally in Japan’s Nikkei, as weaker U.S. jobs data reinforced expectations of a Fed rate cut next week even while AI-linked U.S. tech names remain u

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We saw Amazon (AMZN) showing a dip in recent trading while Nvidia seek to make an upside move, as I hold both $NVIDIA(NVDA)$ and $Amazon.com(AMZN)$, I might consider to buy the dip at the same time, play option to take advantage of any potential upside. as the market often presents contrasting movements between major stocks like Amazon (AMZN) and Nvidia (NVDA). For Amazon (AMZN), the recent dip is viewed by some analysts as a potential buying opportunity, especially given its accelerating cloud (AWS) and AI momentum. For Nvidia (NVDA), analysts are also widely bullish, with a recent pullback being highlighted as an enticing buy-the-dip target ahead of expected strong earnings. In this article, I would lik

If you’re considering buying the dip in NVIDIA (NVDA) or Amazon (AMZN), it really comes down to your risk tolerance and investment goals. NVIDIA is a leader in GPUs and AI chips, with enormous growth potential due to the AI boom, but its stock is highly volatile and priced for high growth, meaning it can swing dramatically on earnings or news. Amazon, on the other hand, is a more diversified and stable company, dominant in e-commerce and cloud computing (AWS). While its growth is slower than NVIDIA’s, its stock tends to be steadier and less susceptible to extreme swings. Essentially, NVDA offers higher potential upside but comes with higher risk, whereas AMZN provides steadier growth with moderate risk. For many investors, a balanced approach—buying smaller amounts of both—can capture grow

✅ Why this competition matters — and why I’m optimistic (in part) • Diversified hardware architectures are appearing. The acquisition of Celestial AI by Marvell Technology signals a shift toward optical‐interconnect technology for AI infrastructure — not just traditional GPUs or electrical interconnects. By replacing copper/electrical links with photonic (optical) fabric, you can get far higher bandwidth, lower latency, and materially better power/thermal efficiency at scale.  • Hyperscalers want choices and cost-effective alternatives. For example, Amazon Web Services (AWS) recently unveiled Trainium 3 — their latest in-house AI training chip — and positioned it as a lower-cost alternative to GPU-based solutions (essentially aiming to reduce “Nvidia tax”).  • Long-term architecture flex

✅ Why this competition matters — and why I’m optimistic (in part) • Diversified hardware architectures are appearing. The acquisition of Celestial AI by Marvell Technology signals a shift toward optical‐interconnect technology for AI infrastructure — not just traditional GPUs or electrical interconnects. By replacing copper/electrical links with photonic (optical) fabric, you can get far higher bandwidth, lower latency, and materially better power/thermal efficiency at scale.  • Hyperscalers want choices and cost-effective alternatives. For example, Amazon Web Services (AWS) recently unveiled Trainium 3 — their latest in-house AI training chip — and positioned it as a lower-cost alternative to GPU-based solutions (essentially aiming to reduce “Nvidia tax”).  • Long-term architecture flex

It will be both for me. Sorry I don't want to choose between these 2 mags. Both are great in what they do and I don't think I have to make a singular choice here. 

Amazon and Google didn’t just poke the Nvidia bear this week—they walked right into its cave with new silicon and big customers in tow. So if you’re eyeing the dip, do you reach for NVDA…or AMZN? At AWS re:Invent (Dec. 2), Amazon launched Trainium3, a new in-house AI accelerator. Amazon says Trn3-powered UltraServers pack 144 chips, deliver ~4.4× the compute of its prior generation, and use ~4× less energy—claims paired with customer case studies citing up to 50% lower training/inference costs. Google, meanwhile, keeps scaling its TPU line. Its v5p hardware—now generally available—clusters into massive pods (docs list up to 8,960 chips), and Google is courting external buyers. Meta is reportedly in talks to rent TPUs in 2026 and buy them starting 2027—an explicit challenge to Nvidia’s domi

Let's go to the moon. 

Tell me again how there is no AI bubble, nvda is propped up by demand from OpenAI (and many others like it), both companies announce a collaboration with 500B, nvda invests a further 100B into OpenAI. Now OpenAI faces strong and competent rivals who put the squeeze on them, and the market expects it to have a domino effect on nvda... This circular funding (with constant expectations - that looks like borderline begging - of further input from overly eager and naive investors) literally creates an AI bubble waiting to pop if one player goes down, and we know it is not only OpenAI that nvda is relying in for further growth. The AI chips are starting to look like gambling chips where everyone is pushing them around and fueling an unsavoury habit.

🌟🌟🌟The dominance of Nvidia $NVIDIA(NVDA)$ in the AI market is facing its most credible threat yet as tech giants $Amazon.com(AMZN)$ $Alphabet(GOOG)$ & Marvell push forward with their own custom chip solutions.  This is driven by a desire for cost savings, greater efficiency & a reduced reliance on a single supplier. Is Nvidia still a Buy at USD 180? I believe it is a great buy because: Nvidia's proprietary CUDA software platform remains the industry standard for AI developers, creating a powerful ecosystem that competitors have struggled to replace. Nvidia has recently reported robust growth numbers, with demand for its data center GPUs continuin

I would consider 180 a reasonable buy given that 220 would be a fair evaluation. could easily see 300+ in 12 months

Competitive Landscape The surge in alternative accelerators reflects a maturing AI hardware market. Google’s TPU, Amazon’s Trainium/Inferentia, Broadcom’s ASICs and Marvell’s optical-centric roadmap all target specific workloads where efficiency, cost and scale matter more than sheer versatility. These entrants erode the peripheral segments around Nvidia, but none yet match Nvidia’s combined ecosystem of CUDA, software libraries, developer base and proven scalability. Most firms still adopt Nvidia first, then optimise with in-house silicon only for stable, repetitive workloads. Amazon’s AI Chip Amazon’s claim of better cost efficiency is plausible for internal workloads. The chip is designed for Amazon’s own data-centre patterns, so it can reduce AWS’ operational cost and improve margins o

The challenge is bad news to Nvidia. Think not a good buy for now.

Amazon is my favourite of magnificent seven by producing its own AI chips compounding its growth price target $360

From my view, the chip battle between Nvidia, Google, and Amazon is heating up, but Nvidia’s CUDA $NVIDIA(NVDA)$ ecosystem still gives it a strong edge. Even so, Google’s TPU $Alphabet(GOOGL)$ and Amazon’s $Amazon.com(AMZN)$ Trainium have scaled enough that they’re clearly pulling some workloads away and putting real pricing pressure on Nvidia. I also think Amazon’s AI chip progress is still undervalued. With over a million Trainium units deployed and Trainium2 ramping fast, AWS is positioning itself as a major alternative. Combined with Marvell’s photonics move and Broadcom’s ASIC wins, the industry is clearly shifting toward more diversified AI compute. A

Buy and keep long term 

$NVIDIA(NVDA)$ is the largest driver of the data centres and ai construction boom and is a buy at $180 1. While there is an ai chip war, nvda’s cuda is the dominant Gpu in this war 2. Nvda’s revenue is growing not shrinking 3. $180 is a buy not a sell, there aren’t many other ai stocks

$Alphabet(GOOG)$ > $NVIDIA(NVDA)$ 

Let’s see who wins this Chip war and then celebrate being on the same side

We saw Amazon (AMZN) showing a dip in recent trading while Nvidia seek to make an upside move, as I hold both $NVIDIA(NVDA)$ and $Amazon.com(AMZN)$, I might consider to buy the dip at the same time, play option to take advantage of any potential upside. as the market often presents contrasting movements between major stocks like Amazon (AMZN) and Nvidia (NVDA). For Amazon (AMZN), the recent dip is viewed by some analysts as a potential buying opportunity, especially given its accelerating cloud (AWS) and AI momentum. For Nvidia (NVDA), analysts are also widely bullish, with a recent pullback being highlighted as an enticing buy-the-dip target ahead of expected strong earnings. In this article, I would lik

U.S. and Global Market Updates $NVIDIA(NVDA)$   Key Points Europe’s largest rare earth magnet plant, Neo’s new facility in Narva on Russia’s border, is ramping up toward supplying roughly 10% of EU demand, signalling a strategic push to reduce dependence on Chinese critical minerals. Japanese government bond yields have climbed to their highest levels since the late 1990s–2000s, sharpening the Bank of Japan’s dilemma between continuing rate normalization and protecting growth in an already heavily indebted economy. Asia-Pacific equities mostly gained, led by a strong rally in Japan’s Nikkei, as weaker U.S. jobs data reinforced expectations of a Fed rate cut next week even while AI-linked U.S. tech names remain u

Amazon and Google didn’t just poke the Nvidia bear this week—they walked right into its cave with new silicon and big customers in tow. So if you’re eyeing the dip, do you reach for NVDA…or AMZN? At AWS re:Invent (Dec. 2), Amazon launched Trainium3, a new in-house AI accelerator. Amazon says Trn3-powered UltraServers pack 144 chips, deliver ~4.4× the compute of its prior generation, and use ~4× less energy—claims paired with customer case studies citing up to 50% lower training/inference costs. Google, meanwhile, keeps scaling its TPU line. Its v5p hardware—now generally available—clusters into massive pods (docs list up to 8,960 chips), and Google is courting external buyers. Meta is reportedly in talks to rent TPUs in 2026 and buy them starting 2027—an explicit challenge to Nvidia’s domi

✅ Why this competition matters — and why I’m optimistic (in part) • Diversified hardware architectures are appearing. The acquisition of Celestial AI by Marvell Technology signals a shift toward optical‐interconnect technology for AI infrastructure — not just traditional GPUs or electrical interconnects. By replacing copper/electrical links with photonic (optical) fabric, you can get far higher bandwidth, lower latency, and materially better power/thermal efficiency at scale.  • Hyperscalers want choices and cost-effective alternatives. For example, Amazon Web Services (AWS) recently unveiled Trainium 3 — their latest in-house AI training chip — and positioned it as a lower-cost alternative to GPU-based solutions (essentially aiming to reduce “Nvidia tax”).  • Long-term architecture flex

✅ Why this competition matters — and why I’m optimistic (in part) • Diversified hardware architectures are appearing. The acquisition of Celestial AI by Marvell Technology signals a shift toward optical‐interconnect technology for AI infrastructure — not just traditional GPUs or electrical interconnects. By replacing copper/electrical links with photonic (optical) fabric, you can get far higher bandwidth, lower latency, and materially better power/thermal efficiency at scale.  • Hyperscalers want choices and cost-effective alternatives. For example, Amazon Web Services (AWS) recently unveiled Trainium 3 — their latest in-house AI training chip — and positioned it as a lower-cost alternative to GPU-based solutions (essentially aiming to reduce “Nvidia tax”).  • Long-term architecture flex

I. December 2 Mag 7 AnomaliesDoes Trading Volume Expose Institutional Intentions?CompanyCodeClose PriceChangeVolumeCapital Flow InterpretationNVIDIANVDA$181.46+0.86%$33.33BReal Buying: Volume leader, genuine capital betting on AI hardware dominanceTeslaTSLA$429.24-0.21%$29.72BIntense Battle: Positive sales but stock closed down, fierce long-short showdownAppleAAPL$286.19+1.09%$15.33BSafe Haven: After EU defeat, some capital trading technical reboundAmazonAMZN$234.42+0.23%$10.70BInstitutional Building: AWS industry落地, volume gradually expandingMicrosoftMSFT$490.00+0.67%$9.59BStabilizer: Reasonable valuation, allocation-driven buyingMetaMETA$647.10+0.97%$7.50BLack of Confidence: Debt risk unresolved, low turnoverGoogleGOOGL$315.81+0.29%$7.80BWait-and-See: Price target raised, but market awai

If you’re considering buying the dip in NVIDIA (NVDA) or Amazon (AMZN), it really comes down to your risk tolerance and investment goals. NVIDIA is a leader in GPUs and AI chips, with enormous growth potential due to the AI boom, but its stock is highly volatile and priced for high growth, meaning it can swing dramatically on earnings or news. Amazon, on the other hand, is a more diversified and stable company, dominant in e-commerce and cloud computing (AWS). While its growth is slower than NVIDIA’s, its stock tends to be steadier and less susceptible to extreme swings. Essentially, NVDA offers higher potential upside but comes with higher risk, whereas AMZN provides steadier growth with moderate risk. For many investors, a balanced approach—buying smaller amounts of both—can capture grow

Recently, $NVIDIA(NVDA)$ hasn’t had an easy time. In addition to last month’s impact from $Alphabet(GOOG)$’s TPU, $Amazon.com(AMZN)$ yesterday announced a new in-house AI chip, which it claims is more cost-effective than Nvidia’s. $Marvell Technology(MRVL)$ jumped nearly 10% after reporting announcing a $3.25B acquisition of AI-chip startup Celestial AI. This move pushes Marvell another step closer toward becoming a viable Nvidia alternative.1. “Three-way battle”: Nvidia vs. Google TPU vs. Amazon AWS (Trainium)Nvidia has established a nearly unshakable de-facto standard with its GPU hardware + CUDA ecosystem.Google, thro

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Amazon, Marvell, Google vs. NVIDIA — The AI Throne Is No Longer Safe. At $180, Is NVDA Finally a Sell? For two years, NVIDIA $NVIDIA(NVDA)$  has been the undisputed king of AI chips. Every earnings report smashed expectations. Every dip was bought. Every analyst raised targets as if the chart only went one direction. But something important is happening in the background — the challengers have arrived, and they’re not small players. They’re trillion-dollar hyperscalers with one shared goal: break free from NVIDIA’s pricing power. And the market is not pricing this shift correctly. --- 🚨 Amazon Just Drew First Blood — and Others Are Following Amazon’s new in-house AI chip isn’t just another press release. It’s a strategic declaration: “We

The AI chip wars are heating up, and it feels like every month there’s a new contender stepping into the ring to challenge Nvidia’s throne. Amazon just dropped its game-changer: an in-house AI chip that the company claims is “cost-effective” compared to Nvidia’s offerings. Meanwhile, Marvell has made a bold move by acquiring Celestial AI, positioning itself as a contender in next-generation optical interconnect technology. Google isn’t sitting idly either—its TPUs have already carved out a niche, and Broadcom’s ASIC chips add another layer to this increasingly crowded field. Broadcom (AVGO) Alphabet (GOOGL) Marvell Technology (MRVL) Amazon.com (AMZN) Personally, I’m bearish on Nvidia at the moment, though I’ll admit—I often get it wrong when it comes to AI or tech-related stocks. On the su

When I look at the wave of new AI chip announcements — from Amazon's in-house silicon to Google's TPU upgrades and Marvell's acquisition of Celestial AI — I actually see this as a natural and healthy phase of the AI cycle. Competition was always going to intensify once Nvidia opened the floodgates, and now everyone wants a piece of the infrastructure stack. But to me, these developments challenge Nvidia at the margins, not at the core. Nvidia still owns the ecosystem, the CUDA moat, and the developer mindshare that others can't easily replicate. As for Amazon's new chip, I think it's interesting and definitely worth watching. Amazon has scale, data, and a massive installed customer base — so even a moderately successful internal chip can move the needle for AWS margins. That said, I don't

$NVIDIA(NVDA)$   Key Points AI Hardware Squeeze: Nvidia’s pivot toward advanced memory and the AI data center buildout are straining global chip and storage supply, raising component costs and increasing the risk of price hikes and shortages in consumer electronics. AI Rally & FOMO Risk: The ECB warns that elevated AI stock valuations and heavy index concentration may be partly FOMO-driven, yet strategists still see upside where earnings justify prices, emphasizing selective exposure over broad de-risking. Fed Leadership in Focus: National Economic Council director Kevin Hassett has emerged as frontrunner for Fed chair, with markets expecting a more rate-cut-friendly regime at a time when the central bank i

Competitive Landscape The surge in alternative accelerators reflects a maturing AI hardware market. Google’s TPU, Amazon’s Trainium/Inferentia, Broadcom’s ASICs and Marvell’s optical-centric roadmap all target specific workloads where efficiency, cost and scale matter more than sheer versatility. These entrants erode the peripheral segments around Nvidia, but none yet match Nvidia’s combined ecosystem of CUDA, software libraries, developer base and proven scalability. Most firms still adopt Nvidia first, then optimise with in-house silicon only for stable, repetitive workloads. Amazon’s AI Chip Amazon’s claim of better cost efficiency is plausible for internal workloads. The chip is designed for Amazon’s own data-centre patterns, so it can reduce AWS’ operational cost and improve margins o

It will be both for me. Sorry I don't want to choose between these 2 mags. Both are great in what they do and I don't think I have to make a singular choice here. 

🌟🌟🌟The dominance of Nvidia $NVIDIA(NVDA)$ in the AI market is facing its most credible threat yet as tech giants $Amazon.com(AMZN)$ $Alphabet(GOOG)$ & Marvell push forward with their own custom chip solutions.  This is driven by a desire for cost savings, greater efficiency & a reduced reliance on a single supplier. Is Nvidia still a Buy at USD 180? I believe it is a great buy because: Nvidia's proprietary CUDA software platform remains the industry standard for AI developers, creating a powerful ecosystem that competitors have struggled to replace. Nvidia has recently reported robust growth numbers, with demand for its data center GPUs continuin

Let's go to the moon. 

Competitive landscape Nvidia is facing the broadest wave of challengers it has ever seen. Amazon, Google, Marvell and Broadcom are not simply competing on price; they are building vertical ecosystems optimised for their own cloud workloads. This shifts part of the market from general-purpose GPUs toward specialised accelerators. Even so, Nvidia still holds decisive advantages in software (CUDA), developer lock-in and a strong lead in training performance. Competitors reduce its long-term dominance but do not dismantle it quickly. Amazon’s new AI chip Amazon’s in-house chip aims to reduce its dependence on Nvidia and lower the cost of training and inference for AWS customers. It is likely cost-effective within Amazon’s own architecture, although it does not replace Nvidia at the high end of

From my view, the chip battle between Nvidia, Google, and Amazon is heating up, but Nvidia’s CUDA $NVIDIA(NVDA)$ ecosystem still gives it a strong edge. Even so, Google’s TPU $Alphabet(GOOGL)$ and Amazon’s $Amazon.com(AMZN)$ Trainium have scaled enough that they’re clearly pulling some workloads away and putting real pricing pressure on Nvidia. I also think Amazon’s AI chip progress is still undervalued. With over a million Trainium units deployed and Trainium2 ramping fast, AWS is positioning itself as a major alternative. Combined with Marvell’s photonics move and Broadcom’s ASIC wins, the industry is clearly shifting toward more diversified AI compute. A

$NVIDIA(NVDA)$   Nvidia's circular deals, such as its potential $100 billion investment in OpenAI and $10 billion commitment to Anthropic, could impact its valuation multiples, but the effect depends on how these deals are perceived by the market and their long-term financial implications. Key Considerations: Market Sentiment and Perception: Positive View: If investors believe these deals will solidify Nvidia's dominance in the AI ecosystem and drive future revenue growth, valuation multiples (e.g., P/E, EV/EBITDA) could expand. Negative View: Concerns about circular deals (where investments flow back to Nvidia's own customers) might raise questions about the sustainability of revenue growth, potentially compre