MSFT — expert X mentions

I just published my Q2 channel check and alternative data report. 1. $AMZN, $MSFT, and $GOOGL data. One cloud provider has seen significant momentum this quarter. 2. $MSFT Copilot usage trends and headwinds facing SaaS. 3. Usage on ad tech platforms ( $META ) showing strong acceleration. https://t.co/QpomSOsHkP

The Kimi K3 release shakes the dynamics of the AI value chain once again and is a dream scenario for the cloud providers ( $AMZN, $GOOGL $MSFT ) Companies will want hyperscalers to serve as the orchestration layer for multiple models & model providers while also squeezing more tokens out of existing infrastructure, as cost per intelligence declines rapidly.

Some AI stocks move on speculation. $MSFT moves on execution. Microsoft continues to expand its AI ecosystem across Azure, Copilot, and enterprise solutions while maintaining one of the strongest business models in technology. The market may rotate, but companies with real AI monetization potential remain in focus. Keep building, Microsoft. $MSFT $GOOGL $AMZN #ArtificialIntelligence #TechStocks #LongTermInvesting

Earnings are coming up for hyperscalers. What does that mean? More CapEx spending on the way for 2027. I suggest you read my article if you haven't already on memory and how it may impact the earnings season for Google, Microsoft, and Amazon.

$MSFT $400 psych level approaching. Room to run above it.

There are 3 avenues I explored for hyperscalers in the coming months and how memory costs may impact their earnings. Hardware is a small part of their overall business, but has the potential to create the same impact as Samsung's mobile business did in their preliminary earnings. Check it out 👇 $GOOGL $AMZN $MSFT $NVDA $MU $DRAM $EWY

$MSFT The chart is starting to look constructive again. Price defended a key demand area, volume expanded near the lows, and now we're seeing higher lows with buyers gradually taking control. That's usually where sentiment begins to shift. Still needs a clean break above resistance, but the rotation into quality names is hard to ignore. Keeping this one on watch. 📈

Top five tech positionS seeing steady rise $META $AMZN $NVDA $MSFT $NOW after being in the penalty box for weeks $SOFI $RDDT slow recovery as well

Morgan Stanley: AI/Data Center Debt Issuance > Massive Year-Over-Year Surge: Total global credit market debt issuance for AI and data centers is growing at a rapid pace. YTD 2026 issuance has already reached $336bn, easily eclipsing the $217bn total for the entirety of FY 2025. > Aggressive Projections: The full-year FY 2026 forecast stands at $580bn, representing a 167% increase compared to FY 2025. $GOOGL $AMZN $META $ORCL $MSFT

A TON OF THINGS HAPPENED IN THE STOCK MARKET TODAY. Here's a full recap: 1. June U.S. inflation came in much cooler than expected. Headline CPI was 3.5% YoY vs 3.8% expected, while CPI fell 0.4% MoM vs expectations for 0.0%. Core CPI was 2.6% YoY vs 2.9% expected, with Core CPI flat at 0.0% MoM vs 0.2% expected. This marks the first negative monthly inflation reading since 2020. 2. President Trump said he has decided to replace the proposed 20% United States Reimbursement Fee on cargo through the Strait of Hormuz with trade and investment deals from Gulf States into the U.S. He said those investments will be “massive” while also being “extraordinarily good” for the Gulf States and their future. 3. IBM $IBM went down 24% after preliminary Q2 results came in well below expectations. Revenue was $17.2B vs $17.86B expected, up just 1% YoY, with consulting revenue flat and infrastructure revenue down 7% YoY. CEO Arvind Krishna said that in the last few weeks of June, clients shifted quarterly capex toward servers, storage, and memory to secure supply-constrained infrastructure ahead of expected price increases, while cybersecurity concerns also distracted customers. IBM said it did not anticipate the magnitude of the capex reprioritization. The stock has lost roughly $65B in market cap. 4. Palantir $PLTR moved from $122 in the premarket to $135 as the market opened. The stock opened down on the $IBM news around software spend shifting toward capex spend and recovered into the open, closing up 3%. $MSFT Microsoft CEO Satya Nadella quoted Alex Karp yesterday in his piece about why the market needs to focus on true enterprise transformation, not just tokens, while Chamath said on CNBC today that Karp “deserves a medal” for being on the right side of history in calling out foundation model companies that take IP without delivering customer value. 5. Fed Chair Kevin Warsh today said in his congressional testimony that he is “doubling down” on the 2% inflation target and believes this Fed will deliver 2% inflation. He added that a broader price stability objective is still in the back of his mind and said the Fed will see if further reforms are needed. Warsh also said he is prepared to do everything he can to ensure the independent conduct of monetary policy. 6. New York is set to enact the first statewide data center moratorium in the U.S., per NYT. Gov. Kathy Hochul will pause approvals for new hyperscale data centers using 50MW+ of power for one year while the state studies energy, water, and environmental impacts. The order takes effect immediately, but does not impact projects that already have required permits. Hospitals, universities, and back-office financial services are not expected to be affected. 7. The top 10 most active options today by contracts traded were $NVDA with 3.1M contracts, $TSLA with 1.4M contracts, $AAPL with 707K contracts, $PLTR with 646K contracts, $INTC with 562K contracts, $MU with 551K contracts, $IBM with 494K contracts, $AMZN with 492K contracts, $MSFT with 478K contracts, and $WULF with 420K contracts. 8. Nebius $NBIS agreed to sell $1B+ of AI compute to Reflection AI through 2029, giving the company access to Nvidia GB300 chips. Reflection AI, founded by two former Google DeepMind researchers, also signed a multibillion-dollar compute deal with SpaceX last month and has reportedly discussed raising $2.5B at a $25B valuation. Nebius already has compute agreements with Microsoft and Meta. 9. OpenAI is developing a screen-free, battery-powered smart speaker designed as a humanlike AI companion and a new home AI computer. The first consumer product is reportedly focused on voice interaction and ambient presence, giving users an AI assistant they can build a connection with. The device includes a camera and other sensors to understand surroundings and context, while tapping into ChatGPT for richer assistance than conventional smart speakers. It can control smart-home appliances, play media, answer questions, respond to messages, help with chores, assist with cooking, and play music as it moves around the home. 10. Aehr $AEHR reported a strong Q4 beat and guided well above the Street. Q4 EPS came in at $0.11 vs -$0.01 expected, while revenue was $18.8M vs $18.69M expected. The company also received $8M+ in new silicon carbide wafer-level burn-in orders as EV programs ramp, including a follow-on WaferPak order from its lead SiC production customer and a direct order from one of the world’s top two automakers to qualify SiC suppliers for next-gen EVs. Aehr said its lead customer indicated additional capacity needs this fiscal year. Most importantly, $AEHR guided FY27 revenue to $130M–$150M, far above the Street at $85M. 11. Big banks reported a very strong Q2, with Goldman Sachs $GS, Bank of America $BAC, JPMorgan $JPM, and Wells Fargo $WFC all beating expectations. Goldman was the standout, with revenue of $20.34B vs $16.35B expected and EPS of $20.98 vs $14.45, driven by a massive 53% YoY jump in Global Banking & Markets and a 72% YoY surge in Equities S&T. Bank of America beat on revenue and EPS, with trading revenue ex-DVA up 33% YoY. JPMorgan posted revenue of $58.02B vs $51.39B expected and EPS of $7.70 vs $5.72, though NII was roughly in line. Wells Fargo also beat, with revenue up 9% YoY, EPS up 25% YoY, and net loan charge-offs coming in better than expected. Overall, the quarter showed stronger trading, resilient credit, and better-than-expected earnings power across the big banks. 12. South Korea is seeing an unprecedented foreign investor pullback. Overseas investors have dumped $110B of Korean equities so far this year, already far beyond the prior 7-year full-year high of $22B in 2021. The selling intensified in June, when foreigners unloaded $31B, the biggest monthly outflow ever recorded. At the same time, local buyers have stepped in aggressively, with domestic retail investors purchasing $60B and institutions adding $15B since May began. The pressure is now spilling into leveraged retail accounts: as of July 13, 1.2M Korean margin accounts had triggered margin calls, with roughly 320K–360K accounts fully liquidated by brokers. WALL STREET IS THE GREATEST SHOW ON EARTH.

BofA: Optical Devices > 800G & 1.6T Outlook: 800G demand is expected to reach 50–60 million units in 2026, while 1.6T demand is projected at 30 million units. The industry is anticipated to satisfy 70–80% of 800G demand and 50–60% of 1.6T demand in 2026. > 2027 Projections: 800G demand is predicted to flatten, whereas 1.6T demand is expected to grow by at least 50%. > Silicon Photonics (SiPh) Penetration: SiPh penetration is forecasted to hit 50% for 800G and 60% for 1.6T by 2026. > Dominant Form Factors: Pluggable optical transceivers are expected to remain the mainstream technology through 2030, holding the vast majority of the market share. > Next-Gen Tech Rollouts: Near-packaged Optics (NPO)/Extra-dense Pluggable Optics (XPO) volume shipments are anticipated to start in 2027. Meanwhile, 3.2T pluggable transceivers (currently in R&D) are expected to see volume take-off in 2028. AI Architecture and Component Constraints > Copper vs. Optics (Scale-Up vs. Scale-Out): Mainstream scale-up architectures (specifically Nvidia’s GPU-to-GPU connections) are expected to rely heavily on short-reach copper through 2028 due to lower power consumption, reliability, and cost-effectiveness. Optics will continue to dominate in scale-out architectures. > Active Electrical Cables (AEC): AECs are becoming critical, especially at the 1.6T node for intermediate reaches of 5 to 7 meters where Direct Attach Copper (DAC) loses signal integrity. > Component Shortages: The industry is experiencing tight supply across EML, DSP, and faraday rotators, with laser shortages expected to last into 2027. However, BofA experts note that tier-1 suppliers with scale and prepayment resources could see supply situation easing in the latter half of 2026. Hyperscaler Profiles & Supplier Dynamics > AWS: Known for demanding low-cost solutions, AWS is a massive deployer of 400G and is ramping up 800G. They have distinct requirements, such as utilizing I3C for management interfaces and partnering with STMicroelectronics for Silicon Photonics. > Google: Leads in newer optical switching architectures (Optical Circuit Switches - OCS). They began shipping 1.6T modules in Q4 2025 and are expected to triple or quadruple their optical volume in 2026–2027. > Meta: Actively ramping up 800G in 2026, which is expected to contribute over 10 million units in volume. Meta is also uniquely open to testing Co-Packaged Optics (CPO) and Linear Pluggable Optics (LPO) due to power sensitivities. > Microsoft: Focuses on a highly distributed data center model with links spanning 70 to 80 kilometers. They purchase heavily from Nvidia and are pioneering the "slow and wide" macro LED approach for GPU connections. > China Cloud: Hyperscalers like Alibaba and ByteDance are estimated to be 2 to 3 years behind US counterparts, remaining heavily centered on 400G due to regional regulations and US DSP limitations. > Supplier Landscape: Despite a growing number of smaller entrants, tier-1 leaders like Innolight, Coherent, and Eoptolink are expected to continue dominating, maintaining over 50% of the market share through strict CSP bidding caps. $MSFT $GOOGL $AMZN $NVDA $TSEM $BABA $STM $CRDO $SMTC $APH $AAOI

In Ackman's latest interview he divides the AI market, stating that it is not a bubble at the foundational layer, but highly risky at the software/model layer. He sees "near infinite demand" for compute. He believes infrastructure providers such as Microsoft, Amazon, Meta, and even SpaceX will earn massive returns on their data center investments. He is highly skeptical of pure model layer businesses like OpenAI and Anthropic. He notes they face massive capital burn rates and an existential threat from open-source models such as Chinese model and SpaceX that are driving the cost of AI access effectively to zero. A business model reliant on charging for proprietary models will collapse if open-source alternatives are essentially free. $AMZN $META $MSFT $SPCX

Clearly, being long good value companies is like being short the meme stocks. Every time the meme stocks go up, my stocks go down and my stocks do really well when the meme stocks sell off. That tells me I am in the perfect sectors to profit from when the bubble pops. $MSFT or $SOFT trading at low valuations while some meme space stock trades at 250x sales. There is a famous line in Forrest Gump that expresses this idea.

Microsoft vs. NVIDIA: Which AI Stock Is the Better Buy Right Now? https://t.co/JDcVBlJKF8

85% of the time when $MSFT tags this support, it bounces and makes new all‑time highs within 12 months. We’re back there now. I opened a position today. New video: the exact level I’m using, my target, and where I’m out if I’m wrong. https://t.co/OBvLzIQZqF

$MSFT Smart Money Zone held and long term support is confirming. Not in a Bull Cycle yet That said, looking to get long tomorrow morning. https://t.co/KDA5LXmJWD

Did not hear many people talking about Microsoft dropping a physical enterprise wearable platform to bypass smartphones entirely last month. This is their strategy to expand enterprise TAM. $MSFT https://t.co/8GvFUOLf5e

Sometimes the market gives you a second chance. $MSFT was around $381 in late 2023. Since then: 📈 Revenue: $211.9B → $281.7B (+33%) 📈 EPS: $9.68 → $13.64 (+41%) Yet the stock is still trading around the same price. That's what multiple compression looks like. When fundamentals improve faster than the share price, I start paying closer attention. $MSFT remains one of the highest-quality businesses in the market.

AI is not a bubble. Lazy AI bears point to $NVDA's market cap and through PTSD, claim it resembles $CSCO in March 2000. However, any useful bearish analysis should look at what actually made the 1990s market a bubble from a macro sense, and whether those conditions exist today. I now refer you to the attached chart. In the late 1990s the two lines veered apart. Tech investment went vertical toward ~4.5% of GDP, while the economy-wide profit share rolled over from its 1997 high and fell hard into 2000. Investment surged while profitability eroded...bubble! Today, the lines rise in tandem. Tech investment has pushed to roughly 4.9% of GDP, above the dotcom peak and climbing more steeply, while pre-tax corporate profits sit near 14% of GDP. Meanwhile leverage has (mostly) stayed contained and the US current account deficit is shrinking. However, bears point to record levels of investment in isolation, choosing to ignore the growing profitability in addition. Are they dumb, or are they ignorant? Probably both. In the run up to March 2000, share prices rose and multiples exploded. The market paid more and more for each dollar of invisible earnings. This time, forward P/Es have barely moved even as share prices rocketed, because earnings expectations rose alongside them. For example, the Nasdaq 100 trades around 23x forward earnings, near its own 10Y average versus ~60x in March 2000. But...but....the market is so concentrated!!1!1! Yes, the ten largest S&P 500 companies account for ~40% of the index, above the dotcom peak. But those ten companies contribute around 30% of total market earnings, compared to under 20% in 2000, and trade at roughly a 50% premium to the rest of the market against a premium north of 100% at the prior peak. Now, bears will say: "If the rally is earnings driven, everything depends on whether the earnings persist!" Correct. But unfortunately for the bears, this is where things get uncomfortable. AI type names have added on the order of $27 trillion in market value since late 2022, up from roughly $19 trillion just seven months earlier. Set that against any weak attempt to discount the additional profit streams AI can plausibly generate for US companies (estimates cluster in the trillions) and the market has capitalised a multiple of the realistic prize. Not all of that $27 trillion is AI (the hyperscalers run enormous non-AI businesses), and more aggressive assumptions on adoption and productivity can lift the number. But closing the gap requires increasingly heroic assumptions: - that recent shifts in earnings shares are highly persistent - that the boom's suppliers capture an outsized slice of AI's total economic gains - that the economy-wide profit share keeps climbing indefinitely Alright, cool. But what about all the circular financing?! - Nvidia has committed tens of billions to OpenAI while remaining its primary chip supplier - OpenAI has signed a cloud commitment with $ORCL reported around $300B - Oracle in turn buys from Nvidia - $MSFT is simultaneously OpenAI's largest investor and one of its largest vendors True, this somewhat resembles the dotcom vendor financing where Cisco booked loans to cash stricken carriers as revenue (roughly a tenth of sales at the peak), much of it later written off. However, today's arrangements are mostly equity stakes in counterparties with genuinely fast growing revenue rather than disguised loans to fund purchases, and Nvidia has lately been unwinding parts of its ecosystem book. And according to analyst reports, even the AI labs like Anthropic have now turned profitable. A feat many thought would be impossible only a year ago. Personally, I treat this circularity as risk rather than a point to build a bear case around since it's all ultimately leading to greater earnings across the board. Even for fronteir labs. Shock! This then leaves the one key question: Will barriers to entry protect today's profits from erosion? This entirely depends on each company's position in the AI supply chain. - At the model layer, barriers are relatively fragile where frontier models will almost certainly converge longer-term, and open source alternatives have the ability to reset price floors. However, AI soverignty will ultimately result in the likes of OpenAI/Anthropic winning. - At the hyperscaler layer, $AMZN, $GOOGL, $META, and $MSFT are set to spend (currently) $750B for 2026 AI capex where falling behind is not an option. These companies are led by people smarter than you or I - do you think they'll risk their entire business collapsing for AI? No. In fact, you can already see that AI is boosting their earnings measurably in recent earnings. - Going further down, you've got irreplaceable companies such as $ASML (EUV machines), $TSM (CoWoS packaging), and HBM with $MU, SK Hynix and Samsung who are gated by long qualification cycles and multi year LTAs where demand > supply up to the 2030's. The risk of a 2000 style valuation bubble is massively lower than the bearish consensus believes. The world is revolving around AI, and that'll continue for the forseeable future.

$MSFT Satya becoming more and more vocal about hyperscalers being the enterprise “defense layer” from AI model providers. I do agree with him that the hyperscalers are the natural orchestration layer, at the same time it seems every big tech CEO has become more vocal. The AI race has become a capital race and stock price matters now.