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@burrytracker You didn’t need to find Nvidia. You just needed to buy Microsoft, let it compound at ~15% a year plus dividends, and get rich slowly over 25 years. Buying quality and being patient pays off.
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Emma Stock Notes
1.2K posts
Emma Stock Notes
@EmmaStockNotes
20 years in global banks taught me what matters in investing and how much noise surrounds it. Bringing simplicity to find great companies and understand markets
Katılım Şubat 2026
185 Takip Edilen888 Takipçiler
@oguzerkan Cisco is the right warning, but maybe not the full comparison.
$NVDA today sits in rare territory fundamentally. And the valuation doesn’t look wildly detached relative to business quality.
The bigger question is whether Nvidia keeps expanding across the broader AI ecosystem.
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Michael Burry still thinks $NVDA today is $CSCO in 2000.
No wonder why he couldn’t make money by actually running his fund and had to start a blog..
unusual_whales@unusual_whales
Michael Burry has said: "I stand by my analysis. I am not claiming Nvidia is Enron. It is clearly Cisco."
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@StockMKTNewz @fiscal_ai This is what happens when a business becomes a true outlier.
NVIDIA is now operating in a different league of business performance.
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This is how you become worth more than the total market cap of every stock in some of the largest countries in the world
Evan@StockMKTNewz
Nvidia $NVDA is larger than the total market cap of every stock in both Taiwan 🇹🇼 and India 🇮🇳
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@InvestmentGuru_ Interesting that many of the stronger movers are not pure single-point bets.
The companies touching multiple parts of the space stack seem to be capturing more attention.
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@zerohedge AI was already the loudest theme in the SpaceX IPO prospectus.
Interesting how much of the narrative is now about AI infrastructure, and how little is about profit and returns.
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Musk: SpaceX Is Actively Seeking More AI Compute Customers, After Anthropic Deal zerohedge.com/energy/musk-sp…
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@MMatters22596 Interesting one for me here is TE.
Not an energy generation play, but a connectivity and infrastructure components supplier that can benefit as AI data centres scale.
The fundamentals have also been moving back toward top-tier quality.
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The AI boom is ultimately becoming an ENERGY STORY
- and an energy shortage is already inevitable.
These 4 companies could become some of the biggest beneficiaries over the next years — and all of them offer 10x upside.
$OKLO — Building next-generation micro nuclear reactors and already partnered with hyperscalers like $META to power the AI era.
$SMR — The only SMR company with U.S. NRC-certified reactor technology, giving it a massive strategic advantage.
$TE — A hidden backbone of the electrification boom, supplying critical components for solar systems, AI infrastructure, and industrial power networks.
$EOSE — Developing zinc-based long-duration energy storage systems, avoiding lithium dependency and targeting future grid stability.
What’s your top pick?
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@SpecialSitsNews Interesting reminder of how much AI memory is driving the story.
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EM equity returns vs EM Ex $TSM , Samsung, SK Hynix $EWY $DRAM $MU
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@aussiExau @InvestingVisual Thanks, for me this is a way to understand business positioning better and ask better questions. I then review fundamentals and look for improving trends.
If you mean specific names, Coherent stands out given its positioning across the stack and improving fundamentals.
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@InvestingVisual @EmmaStockNotes Love this, Emma! I'm the same. Visuals make everything click for me. Really liked your breakdown. Keen to hear what investing takeaways you got?
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I love breaking down complex tech into visual bits and pieces.
My latest research piece on photonics covers:
• How it all works
• The 5 layers of the value chain
• Core businesses per layer
• A business quality tier list
And much more. I hope you find it useful!
Investing visuals@InvestingVisual
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Thanks. I really enjoyed your work and your content certainly helps with building my understanding.
On your question, I usually try to understand how niche a company’s position is and how many different roles it can play within the ecosystem.
Then I look at fundamentals and find companies where unique positioning and improving business quality start to overlap.
So far, lasers and light sources have been standing out the most to me.
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@EmmaStockNotes Thanks Emma, I can definitely relate. I’ve always been a visuals learner and putting the pieces together visually, helps me understand all the moving pieces.
Really like your breakdown as well! And investing take-aways you got from it?
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@JonErlichman Amazing how many of the market’s highest-quality businesses are still in decline.
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Software stocks this year:
Intuit: -52%
Asana: -51%
HubSpot: -50%
Atlassian: -47%
Monday: -46%
Workday: -40%
Figma: -39%
Duolingo: -38%
Bill: -34%
UIPath: -33%
ServiceNow: -33%
Salesforce: -32%
Adobe: -30%
GitLab: -29%
Docusign: -28%
SAP: -27%
Freshworks: -26%
Snowflake: -22%
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@MikeZaccardi Amazing how quickly probabilities change once you stop thinking in days and start thinking in years.
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Stocks are up 85% of the time in a 1-year period JPMAM
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As earnings season starts to wind down, a few interesting names are still left that touch on some important market debates:
Cybersecurity, custom AI silicon, enterprise AI monetisation and AI infrastructure demand.
Here are the 4 earnings I’m watching this week:
$ZS $MRVL $CRM $DELL
$ZS
(Tue, after close):
Cloud security platform increasingly positioned around AI and securing enterprise data flows.
Last earnings reaction: -5.6%.
Question: can AI-driven security demand keep accelerating, or are expectations getting ahead of growth?
$MRVL
(Wed, after close):
Semiconductor company exposed to custom AI chips, networking and optical infrastructure.
Last earnings reaction: +1.0%.
Question: can Marvell prove the AI opportunity is becoming broader than just custom silicon demand?
$CRM
(Wed, after close):
Enterprise software leader pushing aggressively into AI agents through Agentforce.
Last earnings reaction: +7.6%.
Question: is Agentforce becoming a meaningful growth driver, or mainly strengthening the existing platform?
$DELL
(Thu, after close):
Infrastructure provider benefiting from AI server demand and enterprise hardware spending.
Last earnings reaction: +19.9%.
Question: can AI server momentum continue, or are expectations now becoming too aggressive?
Earnings are where narratives get audited
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@StockSavvyShay Interesting read-through from this.
If performance starts coming more from packaging and system design, not just smaller transistors, companies like ASE may become more important too.
Its fundamentals have already been moving back toward top-tier quality.
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Huawei claims its new LogicFolding approach can help narrow the gap with $TSM by improving chip density, latency & power efficiency without relying only on smaller transistors.
TSMC already attacks this problem through CoWoS-L & SoIC packaging with $NVDA, $AMD, $AVGO, $QCOM & hyperscaler custom silicon programs all building on those leading-edge capabilities.
Huawei can innovate around any single piece of that stack but replicating the entire system requires either lifting the export controls (unlikely) or building a parallel ecosystem from scratch (a 15-20 year project).
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Profit.
Profit, profitability and related words appear 24 times combined.
AI / artificial intelligence appears 1,029 times.
The prospectus gets top marks on vision.
But that also frames the IPO debate:
how much of that vision can turn into durable profitability?
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The SpaceX IPO prospectus is fascinating for its scale of vision.
AI, infrastructure, satellites, launch and scale dominate the language.
But one key theme, pretty relevant for an IPO, is barely visible.
Can you spot it?
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@NoLimitGains One of the first businesses AI genuinely broke.
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@oguzerkan The AI bottleneck is moving further upstream.
If power takes years to secure, the opportunity spreads across generation, distribution and cooling too.
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Mark Zuckerberg: “Energy is the biggest bottleneck for scaling AI.”
This is why $META signed over $14 billion worth of deals to secure 6.6 GW of power by 2035.
If you want the compute, you need to secure the power first.
$BE $FPS $SEI $PWR $FLNC
Sam Badawi@Sam_Badawi
$IREN co-founder Daniel Roberts said if someone wanted to build a 1GW AI factory TODAY, they likely would not get first compute online until 2030, reinforcing how severe the power bottleneck has become across AI infrastructure. That is exactly why energy and power infrastructure in $BE and $FPS continue becoming increasingly important to support the expanding compute footprint tied to the builders $NBIS, $WULF, and $APLD.
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@KobeissiLetter Interesting how memory went from one of the most cyclical parts of semis to one of the key AI bottlenecks.
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A memory chip fund is now the fastest-growing ETF in history:
The Memory ETF, $DRAM, accumulated $6.5 billion in assets in just 27 trading sessions since its April 2nd launch, faster than any ETF in history.
By comparison, the Bitcoin ETF, $IBIT, which previously held this record, took 30 trading sessions to cross this threshold.
$DRAM is now up +84% since April 2nd, topping a record $10 billion in assets over 30 trading sessions.
Furthermore, the fund ranks among the top 10 US ETFs by year-to-date inflows, out of over 5,000 listed funds.
$DRAM is also now in the top 20 most traded ETFs by volume, up from the 34th most traded at the start of May.
The memory chip trade is hotter than ever.
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@royscott87 @StockSavvyShay Fair point on AI capex. All the big tech companies still need to show the returns from these bets.
The comparison here is based on 30+ financial statement metrics. On that basis, Microsoft has been one of the strongest businesses in the market.
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@EmmaStockNotes @StockSavvyShay It really isn’t. Microsoft executive leadership is some of the worst in the industry just making the same big bet as every other major tech company.
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$MSFT two years ago:
• ~$420/share
• Azure growing ~30% with $235B commercial RPO
• AI revenue barely measurable
$MSFT today:
• ~$420/share
• Azure re-accelerated to 40% growth with $627B Commercial RPO (+99% YoY)
• $37B AI ARR (+123% YoY) with 20M+ Copilot seats (+250% YoY)
• Maia 200 custom silicon in production
Same stock price two years later but AI business behind it is unrecognizable.
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@wliang Micron is now one of the strongest businesses in the market on fundamentals.
Memory used to be a sharp cycle story.
The question is whether AI/HBM demand is big enough to change that.
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$MU thesis continues to validate itself.
Since I last posted about Micron...
> Manassas Virginia $2B+ expansion just started 1α DRAM production. The most advanced memory tech ever produced in the US. $MU is officially the ONLY US manufacturer of DRAM.
> Quadruples DDR4 wafer supply for automotive, defense, aerospace, industrial sectors. Part of their broader $200B US investment plan creating 90,000 jobs.
And remember, HBM is sold out through 2026 under binding contracts. HBM4 in high-volume production for $NVDA Vera Rubin. HBM4e ramps in 2027. Custom HBM for $NVDA Feynman GPU (2028).
$MU's "Nvidia Moment" is playing out. Makes sense... bottleneck supplier in an AI supercycle catches institutional attention as supply constraints become structural.
It's a different kind of peace investing in companies like $AMD, $SNDK, $NVDA, or $MU long-term.
Wayne Liang@wliang
So I posted $MU back in August 2025 when it was sitting around ~$118, calling a soon-to-come reversal from that choppiness. Two weeks later, the first Startup.io buy-signal came in at ~$130. We're sitting at $746 today (~570%). Not a bad 8 month return on a large cap... Back in August, $MU was sitting near 52-week lows around $130B MC. CHIPS Act funding was still uncertain, and this whole AI memory thesis was still pretty speculative. Again, sometimes technicals come in faster than fundamentals... so let's see what fundamentally changed after our buy signal: > HBM3E became the dominant growth driver, and HBM4 ramping into 2026. Huge shortage, and hyperscalers (+ $NVDA and $AMD) were literally fighting for allocations. > DRAM/NAND prices surged 4-10x. Capacity got pulled toward HBM and the rest of the market got squeezed. > Big Tech started locking in 2027 NAND allocations... $MU's CEO confirming customers receive only "50% to two-thirds of their requirements." Reaffirming the structural supply deficit until 2027. > CHIPS Act delivered $6.1B in finalized funding for $MU. > Agentic AI workloads tripled CPU demand overnight. GPU-to-CPU ratio went from 8:1 toward 1:1, sending HBM demand for $NVDA and $AMD GPUs through the roof. Very little of this was priced in back then. > $725B in confirmed Mag 7 AI capex for 2026 alone as mentioned in previous posts - $META, $GOOGL, $MSFT, and $AMZN. Now, $MU is at an ~$840B MC and one of the top 10 most valuable U.S. tech companies in the world. People buying here might still be early (DA Davidson just set a $1,000 price target)... But anyone who followed me back then absolutely printed. I told you before, it pays to pay attention. As usual, I'll do my best to explain the fundamental thesis and technical alignment on any trades taken. Don't miss the next run.
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