$GOOGL Gemini 4 Argon benchmarks got released. Against GPT-6 Astra + Anthropic Fable 5.1 / Opus 5.5. Still coughing nonstop, so will comment on $MU / $JBL earnings later. I've always thought Google's internal models were stellar, but anecdotally, they seem to get hard nerfed shortly after public release... Maybe because of compute constraints? But yeah, looks like Google is back.

I’ve been running a barbell approach: cautious and aggressive at the same time. On the cautious side, I still want some relatively stable names with more manageable swings — $NVDA as one of my top two positions, plus $TSM, $GOOGL, $META, and $AMZN. Those give the portfolio ballast and long-term compounding. On the aggressive side, my biggest bets are $PLTR and $AMD, along with a few other high-volatility names I share with the community. That’s where I’m looking for asymmetric upside, knowing the swings can be much sharper. The goal isn’t to pick one style. It’s to keep enough stability that I can stay invested, while still putting real size into the names that can move the needle.

@dannycheng2022 Your story hit close to home. I subscribed in 2024 out of curiosity and honestly never left. At the time I was almost all-in $TSLA with a small $PLTR position on the side, plus a huge bunch of lottery stocks. I was stubborn. I held through everything. Watched my gains round-trip 5x over the past 2 years. Portfolio was a mess and I knew it. I don’t have multiple income streams like you. What I did have were your indicators. I used them to sell options for premium and stay in the game. Through you I also found a community of people who actually do the work — @cantonmeow, @sheslee and many others. That changed how I looked at this market. $PLTR slowly became my biggest position. I started following your signals and adding when it felt uncomfortable. Now I’m focused on building the core instead of chasing tickets. My only real regret is not buying more $PLTR and my core positions $AMD $NVDA $NBIS $HOOD $GOOGL earlier. These past few months the volatility has been insane. I used it to finally clean the book up. Somehow, even with all the noise, this portfolio has stayed pretty stable. I learnt that investing is 50% conviction and 50% patience when you are in the right stocks. Thank you, Danny. I am a small account but I am grateful I stayed and I will continue to stay!

$IREN CEO on Anthropic call for frontier slowdown: “Even if models never improved from here… just rolling out what they can already do would take more compute than the world can build for years” I agree, and current narrative is reminiscent of the $NVDA DeepSeek selloff or the $GOOGL TurboQuant scare. Guess what happened? These scares once or twice a year all turn out to be immaterial to the overall AI buildout. Especially when we have contracted demand all the way into the 2030’s now from advanced packaging to memory procurement.

Tech people in real life: I have shares in “ $TSLA, $GOOGL, $SPCX. “ People on my X feed/comments: - Leveraged Micron, Sk Hynix calls all the way from $1M to $28M down to $4M - calls on short dated tanker freight futures because $AXTI 3000% 1Y returns wasn’t enough. - Long $PLTR short $LULU because inverse Burry indicators - Long Swedish high beta CW laser suppliers for CPO because it reminds them of $NVDA bottlenecking EML - “AI is going to end human civilization” so this is a signal for longer AI capex duration + trade wars so long $EQR cause tungsten. Gap between finance X and normal finance/tech people is also insane. I can’t help but feel proud that I’m partly to blame.

Yep, I'm personally high conviction on the AI trade (especially photonics/memory) despite macro. - $NVDA gave forecasts for $1.3T hyperscaler capex ($100B+ above BofA analyst expectations) - $SPCX Wells Fargo forecasts are ~$263B for 2027. - $127B spend in 2027 for Anthropic/OpenAI model training + inference from internal investor documents (WSJ). - Even the Pentagon (US gov) is looking to fund the AI buildout, with $5B potentially into Fluidstack. What sectors do I think capex flows hit the hardest? Photonics + Memory. Trendforce for example est. DRAM and NAND to be 68% of hyperscaler capex in 2027. So when all that memory procurement spend hits the balance sheets of $MU, $SNDK, Samsung, $SKHY with 70-80%+ margins. I don't think these companies care about short term macro scares. And when your leading memory companies are all allocating capacity for DDR5/HBM or high end memory, with little visibility on legacy memory supply coming online. What does that say about the durability of ESMT/Etron/Winbond and others? And when your optical content/GPU goes up for rubin ultra + $META / $GOOGL TPU v9, etc. Alongside TAM eg. $131.4 billion (+81% revision) for 2027 optical module forecasts. Who benefits from supplying all that lasers during a shortage other than $LITE / $SIVE / $AAOI / $COHR? I think the overwhelming fundamentals + growth of some of the AI sector companies will outperform macro.

Anthropic's Economic Scenario publication was a pretty interesting read: 1. Anthropic's "extreme" scenario has GDP growth reaching 15.4% in 2030 So around 7.3x current rates (~2.1% Y/Y), which is consistent with what Elon Musk is saying about outgrowing the national debt with AI. 2. Almost all of the divergence happens after 2027. Their model shows relatively little separation in 2026-2027, then the curves bend sharply into 2028-2030. So my read is that it points to 2026-2027 as buildout years and 2028-2030 as economic acceleration. Kinda gets mapped as well when you look at $AMZN / $META / $GOOGL capex, and short term FCF headwinds (but massive projected profitability post 2028) 3. In an extreme scenario, unemployment of knowledge workers goes to 17.9%. With 11.9% economy-wide unemployment "At the individual level, it means coders and call service center agents may have to switch to jobs like electrician and nurse, which are less exposed to AI." GG computer science majors. 4. Non-cognitive wages: +33.6% vs. baseline in an extreme scenario. So your electricians/construction-type labor becomes extremely valuable? (but this isn't factoring in humanoids yet...) Whereas -11.5% for knowledge workers in 2030 vs. baseline. 5. Aggregate capital income is ~81% higher than it would have been without AI Productivity explodes -> aggregate labor income barely changes -> essentially all of the incremental GDP accrues to capital. So that makes ownership of capital rather than labor... so equities like compute, power, semis, networking, robotics, etc. become pretty important... TLDR: - Economic growth go brr - Jobs that require thinking = unemployment + lower wages - Physical labor = more important, like electricians. - AI equities go brrr.

Let me get this straight chat… you have: $NVDA 70% supply constrained revenue growth projections (would be 100%+) $AVGO AI revenue growing 100%+ Y/Y for next 2 years from mid ~$50B -> $230B OpenAI Astra blowing away AGI benchmarks and starting to train itself. $MSFT / $GOOGL / $AMZN stating compute demand imbalances into next year, with Nvidia projecting $1.3T spend for 2027. You’re seeing this flow through supply chains from Samsung 70% capacity LTAs into 2031 to Powertech advanced packaging capacity 100% booked into 2030. Even your legacy players like Winbond are starting 2029-2030 allocations. Markets always have temporary drawdowns and macro scares… but… How can anyone not think AI stock go brrr?

The 100x was made in the dips you sold. Why do so many people fixate on daily price swings when a stock is already in a long-term uptrend and its fundamentals keep improving every quarter and every year? U.S. stock market history makes the cost of that habit clear. Over the past 2 decades, several major technology companies delivered more than 100x: $NVDA: roughly 500x $NFLX: roughly 275x $AMZN: roughly 150–160x $AAPL: from about $2.30 to around $325, or roughly 140x on price and about 150x with dividends reinvested $GOOGL and $MSFT still compounded powerfully over that stretch — closer to 25–35x — but the true 100-baggers were the names people kept selling because they “looked expensive” or had dropped 30–40% that year. If you simply trade in and out, you are likely to miss the parabolic part of the move. I don’t trade in and out because my goal is to create wealth, not to make pocket money! I keep dollar-cost averaging, and I add more when institutions are willing to offer huge discounts — usually 2 times a year — and when retail fear is at its peak! @cantonmeow @sheslee @tonylee80 @Jimmy_tesla_01

Just some TLDR news I found interesting: 1. $GOOGL (missed this) also invested in Mediatek alongside $NVDA for their $3.9B raise. Google/Nvidia are goats with investments you look at $SPCX to Anthropic. 2. Samsung Electro-Mechanics discloses $778.9M MLCC deal / $CAPA (new MLCC ETF) also gives exposure now for folks without Korea/Japan/Taiwan market access. But thing is more accelerators x MLCCs per accelerator might indicate a more future extreme bottleneck than people expect. 3. China channel checks state: planetary roller screws, 6D force sensors, and dexterous hands resist domestic substitution. Then planetary roller screw as the top with lowest domestic substitution rate. eg. $SHA0.DE for planetary. Just interesting to hear moats I guess. 4. Samsung reportedly has ~70% of memory production capacity committed through 2031 / commodity DRAM has also fallen into short supply - Seoul Economic Daily. TrendForce expects server DRAM contract prices to rise 13-18% QoQ in 3Q26 SK Hynix also publicly stated the memory shortage lasts through 2030. 5. $CXMT has begun producing HBM3E in small quantities and reportedly claimed mass production of LPDDR6. Implications are even more positive for legacy DRAM shortages. 6. Cisco at SEMICON Taiwan said CPO is ready for mass deployment; pluggable modules will remain the market mainstay. $MRVL also said customers are actively planning scale-up optics deployments as early as 2027 7. Wingtech -> bought Nexperia -> Netherlands effectively removed Wingtech’s control -> Wingtech is fighting back through Chinese courts. But Nexperia got $300m of their assets frozen. More geopolitical drama of course, always entertaining. $AAPl also explicitly accused OpenAI of destroying crucial evidence... (for more fun) 8. Not much description around ASP hikes regarding SOI substrates $SOI, but they now have 10+ customers involved with LTAs, $200m revenue described as a "floor", comments about customers more concerned about obtaining wafers than where they are manufactured. So basically moving into capacity reservation now stages as silicon photonics takes off in 2027. 9. Some channel checks put lead times for high power MOSFETs and large area TVS diodes as high as ~52 weeks. ($STM also reportedly implemented its 3rd 2026 price increase on August 23) 10. Traditional packaging capacity could face a deficit exceeding 20% by 2027" with "wire bonding equipment" emerging as the primary bottleneck", covered this earlier this week with beneficiaries like 11. Claims that all six major ABF suppliers are booked for 2026, with 12-14 month lead times and some suppliers auctioning remaining capacity; $NVDA, $AMD and hyperscalers locking ABF capacity through 2028 and pushing suppliers to plan 2029–30 expansions. Names like Kinsus (3189), Unimicron (3037), Nan Ya PCB (8046), Ibiden (4062), etc are all probably happy. 12. CCL leading laminated board products increased by another 10%-20%, 7th price hike this year (eg. Kingboard). Industry estimates put the HVLP4 copper-foil shortage at ~48% in 2026 / 43% in 2027, while Low-Dk/T-Glass lead times have stretched beyond 30 weeks. 13. "(GaAs) substrate materials and gallium epitaxial source materials are also facing another round of price increases in the third quarter of 2026, reportedly 5 to 6 times higher than at the early stage of the restrictions." "China has recently eased some substrate export controls" but there's a "severe InP substrate shortage" per digitimes. Just some $AXTI related updates 14. $AMD and $AVGO reportedly booked most of Powertech's planned FOPLP capacity ahead of mid-2027 mass production 15. $INTC considering $INTC foundry for HBM4E base dies. But $SKHY responded directly that "some of the content is different from the facts". 16. "OpenAI Hoarding Tens Of Thousands Of $AAPL Mac mini and Mac Studio" for reinforcement learning. Anthropic has been renting mac mini units from $AMZN as well. Kinda sad Tim Cook retired, but dude had a goated run. Just random interesting notes

“Memory is a bubble.”Explain this then, KOSPI bears: Samsung has reportedly reserved ~70% of its memory production capacity through 2031 via LTAs with $NVDA, $MSFT, and $GOOGL as main counterparties. Five years of demand visibility… https://t.co/GUGWTkXkMc

Sometimes when people say “I bet big on stock A or B,” I wonder what “big” actually means—everyone seems to have a different standard. My father once told me an uncle had bet quite heavily on $TSLA and $GOOGL. Later I discovered he only held 400 shares for both, which is insignificant by most measures. Even though I own 24,888 shares of $AMD, I still consider it a modest position rather than a big bet. What’s your definition of betting big on a stock in terms of money?

After watching clips of China's humanoid Olympics... I think we're cooked chat. Still can't believe $GOOGL sold Boston Dynamics, don't think we have another humanoid that can backflip. https://t.co/uERCqW85F5

RT @dannycheng2022: 8 Persistent Myths That Keep Retail Investors Poor (While the Smart Money Gets Richer) After 15+ years in the markets and watching thousands of retail accounts, most retail traders lose money not because they’re stupid, but because they believe myths that are the exact opposite of how real wealth is built. Here are the 8 biggest ones — and the truths that actually make people rich. Myth 1: “I just need to find the next 100× small-cap rocket” Reality: True market-beating wealth is almost always made by owning the undisputed leaders of each cycle, not by gambling on unknown micro-caps hoping for an overnight moonshot. In every bull market, a handful of industry leaders capture 80-90% of the gains. The rest fight for scraps. $NVDA, $TSLA, $AAPL, $MSFT, $GOOGL, $META, , —these names dominate their sectors and ride the narrative waves for years. Small stocks might give you a quick 5×, but they also give you permanent loss of capital 9 times out of 10. Stick to the kings and queens. Let the leaders do the heavy lifting. Myth 2: “When the market drops 10-50%, I must sell or stop buying” Reality: The biggest opportunities are handed to you on a silver platter during drawdowns. Whales accumulate aggressively when retail panics.Remember these dates? April -May 2024 July–August 2024 April 2025 November 2025 Retail was selling in panic, succumbing to market noises telling us the start of Great Depression and the end of the bull market this cycle. Smart money was buying hand over fist. In fact, true wealth is created in bear markets and drawdowns, not in euphoria. The bull market just reveals the wealth that was quietly built when nobody wanted to buy. Myth 3: “Diversification is king " Reality: You only need to focus on 5-10 world-class leaders in the 3-4 sectors driving the current cycle. Concentrated bets on the right narrative crush shotgun diversification. The people who went “all in” (responsibly concentrated, not all-or-nothing) on the right themes made life-changing money. The people with too many positions made market returns or less. Concentrated bets on the right narrative > shotgun diversification. Myth 4: “The more I trade, the richer I’ll get” Reality: The wealthiest investors I know barely trade at all—and the greatest example of all is Warren Buffett. He’s worth $140B+ holding Coca-Cola, AmEx, and Apple for decades while barely trading. The wealthiest investors on earth treat the market like owning pieces of great businesses, not like a video game. They buy exceptional companies, add on weakness, and let time and compounding do the work. Frequent trading is just a hidden tax on your future wealth. Myth 5: “Options are the fast lane to millions" Reality: In 15 years I have never seen a single client build tens or hundreds of millions consistently with options. Zero. I have seen many who started with $1-3M, ignored options, and turned it into $20-100M+ by simply owning great stocks for a decade. Slow beats exciting every time. Myth 6: “If it’s trending on X or in the headlines, I have to buy now" Reality: By the time something is screaming across headlines and social media, the easy money has already been made. Headlines are lagging indicators. Noise on X is intentionally juicy because it drives clicks, volume, and liquidity for institutions to distribute or accumulate quietly. If everyone is talking about it, you’re the exit liquidity. Myth 7: “I need to follow the right guru who can time the exact top and bottom” Reality: Nobody—no one—consistently times the market 100% accurately or perfectly. Not Cathie Wood, not Michalel Burry, not Tom Lee. not your favorite X account with the rocket emojis. Even the best have spectacular wins and painful losses. The difference between them and the crowd? They have an edge, a process, and the emotional control to stick to it when they’re wrong half the time. Stop looking for the perfect entry and exit. Start looking for the highest-quality businesses you can own for the next decade. Myth 8 “I can supercharge my returns with 2× or 3× leveraged ETFs like TSLL, CONL, NVDL, SOXL" Reality: These products are mathematically engineered to destroy retail capital over anything longer than a few weeks or months—and most holders don’t even understand why. They are not designed for all retail to win. Final Thought The stock market is the greatest wealth-creation machine ever invented — but only if you stop playing it like a casino. Do less. Own better assets. Wait longer. That’s how quiet millionaires and billionaires are actually made! @cantonmeow @matthughes13 @gabz_investing @sheslee @tonylee80 @Nagetheworld @chad_ventures @Hiteshp99

$MRVL gives $GOOGL options to buy $12.2B of the company. "The Marvell-Google deal covers a broad range of technologies used ​with TPUs, including processors that run AI models, manage data storage ​and move information ⁠across networks." Which could translate into ~$120 billion ​in revenue through 2033. Marvell also has separate warrants with $AMZN after their Celestial acquisition (for purchases of photonic fabric). Remember the good times when Jensen said Marvell would be the next $1T+ company? Seems Nvidia knew Marvell was "networking" its way into all the hyperscalers with warrants.

RT @dannycheng2022: How I Time Bottoms Using the Volatility Hole + Descending Blue Ribbon 😄😁😃😀😊 (August 14, 2026) I identify potential market bottoms by combining the Volatility Hole with a descending blue ribbon on my weekly charts. For strong stocks, one Volatility Hole is typically enough, while weaker stocks usually need 2 to 3 Volatility Holes. Once these signals appear, I begin dollar-cost averaging (DCA) into my highest-conviction stocks gradually and aggressively! This is a reliable setup which usually takes 6 weeks to 6 months to fully play out — patience is the key! Further Examples for Illustration 1. $RBRK – Volatility Hole marked the bottom at $49–$50 in the week of April 24, 2026. 2. $HOOD – Volatility Hole marked the bottom at $66–$77 in the week of April 10, 2026. 3. $GOOGL – Volatility Hole marked the bottom at $166–$174 in the week of May 23, 2025. 4. $MSFT – Volatility Hole marked the bottom at $367–$400 in the week of March 20, 2026. @cantonmeow @sheslee @Hiteshp99 @tonylee80 @matthughes13

How I Time Bottoms Using the Volatility Hole + Descending Blue Ribbon 😄😁😃😀😊 (August 14, 2026) I identify potential market bottoms by combining the Volatility Hole with a descending blue ribbon on my weekly charts. For strong stocks, one Volatility Hole is typically enough, while weaker stocks usually need 2 to 3 Volatility Holes. Once these signals appear, I begin dollar-cost averaging (DCA) into my highest-conviction stocks gradually and aggressively! This is a reliable setup which usually takes 6 weeks to 6 months to fully play out — patience is the key! Further Examples for Illustration 1. $RBRK – Volatility Hole marked the bottom at $49–$50 in the week of April 24, 2026. 2. $HOOD – Volatility Hole marked the bottom at $66–$77 in the week of April 10, 2026. 3. $GOOGL – Volatility Hole marked the bottom at $166–$174 in the week of May 23, 2025. 4. $MSFT – Volatility Hole marked the bottom at $367–$400 in the week of March 20, 2026. @cantonmeow @sheslee @Hiteshp99 @tonylee80 @matthughes13

Today I'm writing a weekend guide on how to do DD when shorting $NBIS: First, you look at hyperscaler earnings for AI cloud read through: > $GOOGL: reports record AI cloud demand + backlog + margin increases from earnings > $AMZN: reports record AI Cloud demand + backlog + margin increases from earnings > $META: reports higher than expected prices for available capacity from earnings. Now, time to look at Nebius: -> $NBIS: Growing hundreds of percent to $7-9B ARR by Q4. Growing margins, and guided 4GW+ contracted power. -> Sees Uber/Waymo splitting, putting more focus on Avride -> Sees Clickhouse growing rapidly every quarter. Okay looks bad! But next, you need a hedge? -> Wow! A $NIKE brand executive, after the stock dropped 75% over the past 5 years, went to $LULU to save that brand next? Lululemon seems good. Conclusion: Short Nebius and go long on $LULU

As a earnings recap: $AMZN, $META, $GOOGL, and $MSFT guided a 2026 combined capex forecast to ~$720-$745 Billion. Up from $695-$725B Billion previously. Amazon: $220B Google: $195B-$205B Meta: $130B-$145B Microsoft: $175B We've already seen significant deleveraging and retail/institutional margin liquidations (maybe it continues for more time, who knows). But medium-long term, I'm not quite sure how anyone can be bearish the upstream semis or neoclouds. Given each hyperscaler has flagged either compute shortages, rising cloud demand + pricing power, or increased spending for chips/networking. My "bottleneck" thesis with many of these upstream semi supply chains is that when trillions in capital flows into things from InP substrates or memory (which were both treated as cheap commodities) or even energy. Lot of these current AI names that were treated as useless before in telecom cycles or even toilet sellers. Gets rerated when their inflection period hits and capex flows into their balance sheets. As seen with $NVDA GPUs past few years, memory this year, CPUs/MLCCs next few years, CPO in 2027, Glass Substrates in 2027, 800V in 2027, and so on.

Just a TLDR of this week: Media: Hyperscalers overbuilt and are selling excess compute. -> $GOOGL, $MSFT, $META, and $AMZN: Demand for compute far exceeds capacity. Capex go brrr. Institutions: Emergency rate hike or 3x rate hikes, it's all over. -> Kevin Warsh: No rate Hike. Retail/Media: AI is crashing because it's a bubble. -> Citadel looking to buy AI leveraged hedge funds positions: 👀 Jim Cramer: Sell all your leveraged DC stocks. -> Koreans: SK Hynix +30%, Samsung +26.81%

Few earnings TLDRs with my favorite $AXTI and $AMZN: Amazon: - Raised 2026 capex to $220B vs. prior $200B (partly due to higher memory costs, which is bullish on $MU to Samsung) - Even at $220B, Amazon will not have enough capacity to meet all 2026 demand; Jassy expects the same in 2027. - Most incoming 2027 capacity is already reserved, with substantial 2028 capacity also reserved. Mostly read through on upstream semis. $GOOGL, $META, $AMZN, and $MSFT all identified compute shortage. All the narratives a few weeks earlier was "excess compute" from Meta and others + hyperscalers cutting back on spend... All BS. Amazon earnings was very bullish on AI semi trade. AXTI: - AXT to double InP capacity during 2026. Then double again in 2027. This is expected to make AXT "by far the largest indium phosphide producer in the world." - LFG - Q2 rev was $47.6M, the highest quarterly revenue in AXT history (InP revenue reached a record $30.7M, from DC applications.) - Revenue increased 77% sequentially and 164% year over year. - InP revenue-capacity targets: $60M per quarter exiting 2026. - $130M per quarter exiting 2027 That $130m target could be hiked too since management stated they find "whatever ways to increase that capacity expansion" - Management said the reported backlog remains well above $100M, but that number no longer reflects all available demand. "Customer demand continues to outpace supply, no matter how fast we add capacity." 800G/1.6T is driving the current cycle, while NPO/CPO extends it beyond 2027. Also they're targeting 50%-plus gross margin: "We should definitely be targeting a number that begins with a five." China demand more than doubled, and their agreements with Casela, $COHR and $LITE did not materially drive Q2. This is not even considering my projected massive ASP hikes yet as InP substrates get more bottlenecked. TLDR: - Amazon too much compute demands, needs capex to fufill it, so upstream semis go brrr. - AXT world largest InP substrate supplier, high gross margins, expansion, and supply can't keep up with demand. Bullish on demand side from Amazon + capex. Bullish on upstream optical supply chains from too much demand.

Just some takeaways from $META | $MSFT earnings calls: Microsoft: - Expected to be FCF positive in 2027, despite the increase in capex (extremely positive for AI buildout that it's funded by operating income) - "Free cash flow was $19.6 billion, reflecting higher capital expenditures" - Quartely capex was $41B, roughly 2/3rds were "short lived assets, primarily CPUs and GPUs" - Expects capex spend will be over $50 billion for next quarter - Capex Guidance at ~$175 billion and 2027 capex roughly the same. Spending plans unchanged and in line. - "Extending the estimated useful life of our data centers from 15 to 25 years" - "We will be among the first cloud providers to deploy next generation rack-scale AI infrastructure based on $AMD Helios and $NVDA Vera Rubin" - "Customer demand continues to exceed available capacity" Meta: - Capex $130-$145 billion (narrowed range), from $125B-$145B. - Meta is receiving offers at a "significant premium" to what they paid for it (compute scarcity, positive for neoclouds like $IREN / $NBIS ) - Expects significant portion of compute (like the 1 GW DC in El Paso) to develop internal models. - Meta has multiple ROI-positive uses for additional compute across its core business (internally, not Meta Compute) - "Finally, we believe that overall industry capacity is going to remain tight for the foreseeable future" - "The industry has under-built historically for the wave of AI adoption, making existing capacity, including our own, extremely valuable" - Susan Li TLDR: - $MSFT and $GOOGL largely sustaining AI capex buildout while remaining FCF positive or through operating incomes. - $META flags available compute materially below demand at least through 2027. And $MSFT also flags compute demand far exceeds supply. - All three hyperscaler capex largely in line with Google hiking capex figures. AI selloff seems extremely overblown now, hyperscalers continuing capex in line (with Microsoft being FCF positive) or even hiked with $GOOGL. Compute scarcity is visible throughout every single hyperscaler ER.

I personally see it as extreme short term deleveraging that overshot many individual names. - $BE to $TER reported blowout results, with Bloom reporting 166% Y/Y rev growth + expanding margins + raised 2026 guidance... Teradyne reported 104% Y/Y revenue growth with 300%+ EPS growth. Your leading optical players over in China reported amazing preliminary earnings + extremely strong read through for the Western photonics sector. Think earnings season tend to remind markets about continued AI acceleration. I'm expecting $LITE, $SNDK / SK Hynix, and sector leader ERs to continue that trend. But it does feel like markets are rewarding existing acceleration more rather than future growth a year out over near-term revisions as seen with $AMKR. But as a TLDR, looks very positive for the themes I'm tracking. - Then you have $GOOGL capex raised to $195-$205B, which is typically the biggest AI demand signal from hyperscalers. - 77% 0bps change est. next FOMC decision from prediction markets. Trump administration on Monday called for the Fed to lower interest rates. So your 3x rate hikes fears this year seem kinda overblown. - Chinese fears from DUV to $CXMT overflooding are extremely overblown as well. We see this with every sector from time to time until people remember that lasers or HBM bottlenecks for a reason. As for personal thoughts, it was unhealthy seeing everything rise up or down together, especially with these themes. But I'm personally not worried since I have full conviction in my names, especially optical interconnects like $SIVE or $AAOI. $META compute and $GOOGL GCP margins/growth shows increasing demand for $NBIS and similar neocloud business models. $META + other hyperscaler notes around LTAs with $SNDK and Samsung/SK Hynix, $MU point to structural memory demand. Can go on and on... But when you have Jim Cramer telling every margined DC trader to "sell everything" at market open and news saying there's an AI bubble. I do hate it when others say "it's dropping so sell". My belief is that the important thing to look is accelerating revenue/EPS growth. And if that thesis stays in-tact with revenue acceleration in line with hyperscaler capex. TLDR: I see signs of AI demand / revenue acceleration, hyperscaler capex is one of the most important things to track. And my guess is that we'll see the theme recover broadly. But I can't predict what hour, day, or week that happens.

There you have it, $GOOGL Waymo to explore split with $UBER per FT. My view last year was that Uber partnering with Waymo was a bad choice… since Uber would just serve as a distribution funnel that Google needed as they scale up. And that $NBIS Avride, other neutral players, or vertical integration would be the optimal path forward. Now their own partner Waymo looks to be the strongest disruptor to Uber.

$GOOGL updates FY 2026 capex guidance: To $195B-$205B. Up from $180B-$190B. Google is also expected to significantly increase capex in 2027. This is perhaps the most bullish read through on upstream semis from a hyperscaler. https://t.co/dXiI0Ien8X

$GOOGL now has 950M monthly Gemini users and processes 22B API tokens/min. Compared to 750M back in February. Absurd growth adding 200 million more users in a few months. Kinda explains why they ran out of compute, then cut allocations to $META and others. Very unlikely AI capex will slow down given.

$GOOGL reported earnings today: EPS: $9.11 actual vs $2.91 expected - retail reactions to EPS blowout is kinda just accounting noise, since $SPCX, Anthropic, and others were likely large contributors. Revenue: $119.7B actual vs. $116.98B expected Google Cloud Revenue: $24.77B +82% Y/Y, vs. 63-65% expected ($22.2-$22.6B) - this is a very large beat and most material part so far. Cloud Operating Income: ~$8.81B, implying 35.6% margin vs. 32.9% Q1. Capex: $44.92B vs ~$44.15B (basically in line). So initial read through is Google Cloud accelerating growth with expanding margins is genuinely bullish for AI demand. Their former $180-$190B capex guidance is already extremely large, and as long as we get around these numbers in the earnings call + forward projections... Should be good to go for $LITE and the other optics/networking trade. (eg. last earnings, they said DC and networking would be ~40% of capex spend). Hyperscaler earnings transcripts are probably the most important thing to pay attention to with the AI capex trade. And that should be in 3 minutes.

Contrarian take, but Sam Altman / OpenAI is doing something right if he's pissing off every Mag7 like $AAPL. By building their own ecosystem instead of being sucked into another. It's been awhile since $GOOGL, Apple, Microsoft, and others had some genuine disruptors.

There’s a lot of disinformation going around about $META “cutting capex” because they “overbuilt”. This is an “if” they have excess capacity. And it looks like the opposite right now: Hyperscalers like $GOOGL are so compute constrained that they had to cut allocations to Meta back in March. Since Meta was using too much for internal projects. Meta was immediately constrained so it looks like they were forced to immediately sign massive $48B+ contracts with Neoclouds like $CRWV and $NBIS. Meta is selling excess capacity if there’s any, especially since their large contracts are take or pay from the Neoclouds. If anything, I’m expecting their guided capex to go up as they build out more independent capacity.

Just a random thought, leading US humanoid players strangely me of the current LLM dynamics: Agility ( $CCXI ) kinda feels like Anthropic for robotics. With $AMZN and $NVDA heavily backing it, ingrained with $GOOGL Deepmind (like TPUs). And it starts off with enterprise commercialization. Optimus is kinda off doing its own thing like xAI. Supported by Tesla/Elon and his visionary roadmap as usual. Figure is like ChatGPT With Microsoft/OpenAI investing (kinda like Microsoft), then ended up kinda competing them by building their own VlA and setting them behind. But ends up top 2 leaders anyway. Boston Dynamics is Gemini Kinda started the entire humanoids thing like transformers with backflip videos. With R&D supported by $GOOGL but somehow let everyone else leapfrog them in commercialization. And then there’s $NVDA just chilling, silently powering the entire humanoids ecosystem.

Hard to see a world where US AI hyperscaler capex drops dramatically from $GOOGL to $META. When China entities like 360 go and claim: They now have a "AI cyber nuclear weapon" that can hack Western companies and governments. (Zhou claimed Mythos was like an AI era cyber nuclear weapon, then claimed they built a Chinese equivalent). We're probably witnessing the modern cold war. But instead of nuclear stockpiles, it's racing to build superintelligence both offensively and defensively. With many different "battles" happening concurrently like supply chain export controls between China -> Japan -> US hyperscalers. The funny thing is that everyone still depends on one another: - US with things like rare earths and feedstock from China. - China with EUV to EDA and engineered substrates. So there's still give or takes trades to build up capabilities like Nvidia/AMD AI chips access for rare-earth/magnets access. Which is exactly why it's important for the US to build up rare earths supply chains ASAP. And not piss off allied supply chain chokepoints like European EUV partners with $ASML to Japanese vacuum/furnace makers like Ulvac with things like tariffs, if the US wants to use it as leverage for negotiations. But we're getting dangerously closer to a point where supply chain interdependence is not a deterrent against escalation. Especially as China grows closer to becoming self-reliant. And that might be the tipping point.

Guess we finally found why $META signed massive agreements with Neoclouds like $NBIS back in March... And why Gemini got super nerfed. $GOOGL reportedly restricted Meta's capacity in March 2026 because of compute restraints. Google's CEO said from last earnings computing power restrictions prevented Google Cloud from taking on more customer needs and made the department's backlog nearly double the previous quarter. This is probably positive for the AI DC capex buildout since hyperscalers capacity is way below what is needed, and especially so if they can't rely on one another.

Don’t quite think “siphoned off” is the correct term. It’s capex for massive revenue increase or margin increase down the line. $AMZN is probably my favorite hyperscaler right now and example to give. Amazon’s headcount is absurd, like ~1.57M. If the capex goes into automating their workforce with LLMs. Then transitioning into physical AI: - things from self driving (deliveries) - robotics (Amazon warehouses, shipping automation). + revenue increase from building out AWS compute with Trainium and possibly selling chips too with the Neocloud strat. It’s probably the clearest path forward compared to every hyperscaler out there. $TSLA optimus use case targets is extremely broad as a pitch, but Amazon already has a specific reason to scale robotics for internal opex optimization. As for $GOOGL, probably 2nd right now, AI capex was necessary for defending its Google Search moat Gemini from ChatGPT They also have Google Cloud revenue with efficient TPUs + can sell TPUs like Nvidia GPUs. Gemini user volumes keep going up (despite the lack of contention in frontier benchmarks); and AI strategy to be working for ad optimization too. But there’s less clear paths with physical AI stuff ig? Microsoft and Meta are still trying to convince the market why capex is necessary, (we’re kinda seeing that in effect with Meta’s 30%+ Y/Y revenue growth), but doesn’t look like they’re convinced. As for market narratives, Microsoft Maia seems to be behind, their AI development was stunted from OpenAi investments, so sentiment is kinda in the ground. But think that will change down the road like the 180 with Google. I’m sure all the hyperscalers are seeing the leader effect right now: If you have the leading LLM, people will keep using it. That LLM gets smarter from all the training data; and that gap might be structural. Which is why everyone is kinda rushing the buildout right now, but for some the immediate incentives seem obvious.

Just some random thoughts, I do think AI is the most disruptive technology in human history. To the level of agricultural or industrial revolution. Since Anthropic, OpenAi, XAI, and others are racing to build superintelligence. The amount of economic impact can't be measured if AI helps find cures for cancer or accelerates discovery for Quantum Computing. Or if AI end up displacing the workforce, which increases profitability for companies. The US Gov has every incentive to keep the buildout going too, as the implications from Warfare, Cybersecurity, is also immeasurable if China takes the lead. So there's likely to be incentives and subsidies to win, even if there's not enough profit derived LLM training/inference. As for sustainability, when you look upstream, $GOOGL is able to fund it majorly with their own cashflow, same with $AMZN, $MSFT. More lukewarm on $META. Very iffy about $ORCL. But I do see some bubbles forming around debt interest like $CRWV. Maybe circular valuations that's happening with OpenAI backlog agreements or $NVDA / $AMD agreements with Neoclouds to buy their GPUs. But as seen with $MSFT and having OpenAI be a major part of the backlog, it did correct off the information, so "bubbles" like that do pop despite the overall markets increasing. Definitely don't see a bubble in upstream semiconductors from $LITE to Sk Hynix though since the amount of profit they get from the buildout would likely be insane to make up for capex decreasing. OpenAI was actually my biggest fear from contagion, eg. $CRWV, $CBRS and others, but they just raised a lot. So think it will be fine for another 1 1/2 years of capex, especially if they IPO this year. I also don't think we'll get massive Fed tightening despite "predictions" since this will trigger a contagion since many of these players rely heavily on debt. And although the Fed is independent, don't think Trump would have supported someone who is against his administration goals. As for semiconductor valuations going up every day like $AMD or $MU, there's probably going to be some corrections here and there. Everything going up together is kinda unhealthy. Can't time the capex peak but just from $AVGO and other projections, it just keeps accelerating exponentially into 2028. Especially as everyone is starting to sign multi year agreements as well. OpenAI contagion / hyperscaler capex decreasing / fed tightening was what I'm looking out for, and no blaring signs of any of those yet. So I think the music will keep playing for this year at the bare minimum.

$NVDA and $GOOGL lead 800V DC ahead of schedule. "Ahead of schedule", pulled up to Q3 2026 with small volume shipments starting . - Delta Electronics (2308), $VRT - Song Chuan Precision (7788) - Schneider Electric, Eaton, Siemens. All flagged as beneficiaries. "Market sources indicate that Nvidia’s Vera Rubin platform and Google’s next-generation AI data centers will be the first to adopt the technology" Source: Commercial Times The power semi trade should be happy to hear this.

I do see a lot of comments about "harvesting the leeks". And I hope my picks like LeaderDrive can help change that perspective around certain equities being good long term holds. I think my only Chinese listed pick was Innolight last year, and that's up triple digits to ATH? All my ideas come from a Western perspective (eg. institutional research from JP Morgan / Goldman Sachs I synthesize) and what US hyperscalers like $GOOGL or $MSFT require. And I do consider about geopolitical tensions + game theory all the time, such as with $AXTI. I think a foreigner's perspective brings a different kind of alpha here, and I'm excited to share how this plays out. Regardless, I'm excited to see how adventures in Chinese equities go! (also, I'm just 1 person posting thoughts throughout the day. there's a lot of conspiracy theories going around saying I'm some Chinese institution. and yes, English is my primary language, i typo sometimes since I post 20+ a day on mobile mostly).

$GOOGL (June 8, 2026-weekly chart) I was a buyer of $GOOGL between $290 and $305 and shared it with my community. It is holding up very well above the previous all-time high at $348.754. I will be a buyer again if the whales offer a discount, and I’ll double down when my two systems flash bullish signals again.

Yeah… I think all your upstream semi supply chain companies are going much higher. Goldman now expects a combined $5.3 trillion of capex spending for the four largest hyperscalers $GOOGL / $META / MSFT / $AMZN from 2025 to 2030. Revised up from $4.5T from Q1 earnings. “Aggregate capex est. $7.6 trillion between 2026 and 2031.” And it flows upward to these tiny chokepoints like $SIVE for CPO lasers/ $SOI for Silicon Photonics substrates. Leaderdrive/Harmonic for Humanoids components. And so on… Ai names don’t move in a straight line up, but is just the beginning of the next Industrial Revolution as we move from R&D/compute buildout into commercialization from Agents -> Physical AI -> discovery.

I never thought I’d see the day where $GOOGL needs to raise $80b for AI capex… Then Warren Buffet’s $BRK.A is funding the hyperscaler AI buildout. - $40B ATM, $30B offerings, Berkshire $10B Upstream ecosystem from $LITE to $AVGO to Mediatek to $TSM to $MU should go brrr. Not sure if the Google holders are though, given this massive capex scale isn’t as funded by FCF.

Kudos keep coming @dannycheng2022 @cantonmeow Here is my brother Ritchie’s account in 🇮🇳 He invests in both 🇮🇳 and 🇺🇸 5x in $ASTS He did very well in $GOOGL and $AMD He follows @dannycheng2022 charts diligently. Infact, he has outperformed me by following Danny. So, proud of him!!!

Ayar’s announcement today with Wiwynn is potentially very material for $SIVE regarding CPO -> rack scale deployments. As Wiwynn cloud clients include $AMZN, $META, $MSFT. And they’ve been in talks for $GOOGL TPU deployments. I think just for some reference architectures it’s around 512+ supernova light sourc a rack. So if $SIVE is the primary laser array supplier (which we expect, given Macom + Lumentum was removed from Ayar’s site). Even modest rack deployments would be very meaningful for revenue. This is just rack scale commercialization potential right now from $SIVE / Ayar / Wiwynn, which won’t show up in revenue financials yet.

Feels like $FUTU and $TIGR are kinda screwed? The Chinese Gov is going after their historical revenues. There's basically no fair law in China (esp. with IP), so if Gov wants something done, courts will be rigged against them. So no chance of an appeal, unless they make a hidden deal. Also don't think the brokerages are able to pull a $GOOGL like their 20 decillion fine, given local operations So TLDR: Good lesson learned to avoid Chinese exposure from $BABA to $PDD as much as possible... And (as seen with $META + Manus + this case), even if something looks cheap. There's a reason why all the US equities have premiums, even if a little high.

Taiwan financial sector rules are hilariously stupid. They literally dispositioned Mediatek, one of their largest companies lmfao. It's like if the US stopped letting people buy $GOOGL because the stock went up. Then that caused Google's stock dropped after. Wouldn't they want their companies to appreciate in value, so their economy benefits? Especially during one of their largest bull-runs from the semi sector, it's actually hindering their own growth where every week matters. Interesting to see such backward rules hurting their own high-tech economy.

Not sure if people realized this but unless a thesis completely breaks, companies like $NBIS can keep growing. Just look at $AMZN or $GOOGL over the past 15 years. If people "trim" it often triggers taxes. And a lot of corrections are typically less than those taxes paid. By the time a "50% crash happens", it's probably already compounded hundreds of even thousands of percent. If people need to pay expenses, once you hit 7-8-9 figures, you can always borrow against those assets and keep letting them appreciate. NFA, just personal opinion. You all do you, but it's highly, highly, dependent on the companies you pick. Can't do this with something trash like $IREN. But I do believe $NBIS is positioned to be the next hyperscaler.

I actually think $FLNC should be a lot higher. The implications of having 2 incoming direct hyperscaler contracts in 1 quarter is enormous. $MSFT to $AMZN don't sign tiny deals. Obviously markets like to wait more until actual news/purchase order numbers come out... in the off-chance it doesn't go through or lower than expected. But a company doesn't just randomly announce 2 hyperscalers MSas and an expectation of the orders to hit Q3. Also winning multiple hyperscaler deals, in a single quarter is a leading indicator for more, especially as Fluence BESS becomes standardized. Given short interest is around 27.69%, I'm not sure if pre-earnings short sellers are very comfortable to take a risk... I think there's a chance for a generational run if a hyperscaler like $GOOGL signs a massive contract.

I think $MU would hit my first target (in the video) very soon. I’ll keep sharing my target prices through cartoon videos (mostly for fun). Hope you guys enjoy them! I’ve done this before with $AMD, $GOOGL, and $MU.

Agreed high-level directionally, $FLNC compelling at $3B valuation post-earnings after taking a closer look. Very rare to see a US energy player that small get 2 direct Hyperscaler deals... The $5.6B+ backlog derisks the company growth, not including new hyperscalers backlog like $GOOGL or $MSFT. The hyperscaler deals were framework agreements, which are likely to convert "soon" Q3 this year, and aren't included in numbers. Once that's released it's major positive catalyst, similar to qualification -> volume ramp in semi players. Citi Analyst: "The possibility of a hyperscaler order will likely overshadow everything else in the quarter. We expect a positive reaction to the announcement" I'm going to go ahead and guess they'll likely rerated once they announce their hyperscaler orders maybe anytime in the next 3 months so I jumped on the boat as a short term catalyst trade. (not just 1 but 2) Also, if they hit ~$288M net income off gross-margin expansion ($6B revenue, 13.0% gross margins) from their software segment expansion, ~11.6x fwd p/e for 2027. The current stock price is -50% Feb's prices despite hyperscalers + backlog de-risking the company looks like a great entry point to me (NFA).

Wait a sec… This feels so weird I talk about Faker and Aespa and suddenly they’re doing $GOOGL ads together. https://t.co/U9TJ1XHUDj

Bullish on $ARM, given the new bottleneck shifting back to CPUs. MS shows stuff like Orchestration/RAG requiring CPUs. But I'm predicting parts of localized inference to be handled by CPUs more and more... as models like Gemma get lightweight in the future. Not every robot needs to be able to solve the mysteries of the universe. Data centers will need an astronomical amount of traditional CPU compute (AWS Graviton, $GOOGL Axion, and $MSFT Cobalt), which are all ARM based. $META + OpenAI are also buyers of the AGI CPU. And AI will flow down to edge. $15B annual revenue target.. Starting to look reasonable?