GOOGL — expert X mentions

A TON OF THINGS HAPPENED IN THE STOCK MARKET TODAY. Here's a full recap: 1. Google $GOOGL is developing a new AI chip that could run Gemini models 6x to 10x more efficiently than its latest TPUs, per The Information. The chip, internally called “Frozen v2,” would bake parts of Gemini’s architecture directly into silicon, reducing data movement and simplifying inference decisions. Google is targeting deployment as early as 2028 to help ease its AI compute shortage, though the design would trade flexibility for major gains in speed and power efficiency. 2. Microsoft $MSFT is expanding its partnership with AMD $AMD and will deploy AMD’s Helios rack-scale systems on Azure for frontier AI inference. The platform combines MI455X GPUs, Venice CPUs, Pensando networking, and ROCm software, with shipments to Microsoft beginning in the second half of 2026. Azure will also add new AMD-powered virtual machines for agentic AI, data pipelines, and semiconductor design, marking a broader adoption of AMD’s full AI infrastructure stack. 3. AUM in U.S. leveraged semiconductor ETFs has fallen $63B from the June peak to $100B, the lowest level since late April. That marks a 39% decline, the largest drawdown since April 2025, when assets more than halved from their August high. The semiconductor unwind accounts for 63% of the broader $100B drop in AUM across all U.S. leveraged ETFs over the same period. The selloff follows a massive ramp, with assets in these funds nearly tripling between late March and the June peak. Even after the pullback, leveraged semiconductor ETF assets are still up 400% from January 2023 levels. 4. Archer $ACHR and Anduril unveiled Thunder, an autonomous attack VTOL aircraft, with first flight planned for 2027. The runway-independent hybrid-electric aircraft is designed to operate autonomously alongside crewed attack and assault aircraft. The dual-use platform features tiltrotors and modular payloads for both defense and commercial missions. Full-scale surrogate flights have already been completed, and Archer plans to announce its first commercial customers later this week. 5. Chinese AI models are taking record share among U.S. firms on OpenRouter. The proportion of tokens used by American companies running through Chinese models has climbed to roughly 58%, a record high. OpenRouter lets developers access and compare models from multiple providers, making it a useful real-world signal of AI model adoption. Chinese model usage has tripled since mid-January, overtaking U.S. peers on the platform for the first time in March and briefly hitting 63% in early July. At the start of 2025, Chinese models were under 10% of usage, while U.S. models were around 80%. DeepSeek has become the most popular choice among American firms in recent months. 6. The top 10 most active options today by contracts traded were $NVDA with 3.1M contracts, $TSLA with 2.4M contracts, $AAPL with 1.8M contracts, $MU with 951K contracts, $MSFT with 884K contracts, $AMZN with 691K contracts, $INTC with 640K contracts, $SPCX with 606K contracts, $AMD with 506K contracts, and $GOOGL with 492K contracts. 7. BofA reiterated its Buy rating on CoreWeave $CRWV with a $140 price target. Analyst Tal Liani raised FY26 capex estimates to $34B from $29B, saying capex remains a key indicator of buildout progress and hardware pricing. BofA expects Q2 operating margin of 2.4%, slightly below the Street at 2.8%, but sees margins improving through the rest of the year as active power drives revenue recognition. By Q4, BofA expects operating margin to reach 14.6%, up from 1.0% in Q1, showing strong operating leverage. The firm also pushed back on competition concerns from SpaceX and Meta, arguing AI compute demand still far exceeds supply, making access to capacity the real bottleneck rather than provider choice. 8. IREN $IREN raised its 2026 AI Cloud ARR target to over $4B, up from its prior target of $3.7B. The company announced new AI cloud contracts representing $2.8B in total contract value, with approximately 85% of the updated ARR target now under contract. Goldman Sachs estimates the newly announced contracts represent an additional roughly $1B in contracted revenue with an average term of around 3 years. IREN also said recent agreements include customer prepayments covering about 45% of GPU capex, with customer contracts having a weighted average term of approximately 4 years. 9. UBS says Micron $MU could repurchase more than 40% of its shares by the end of 2028. The firm expects Micron to generate over $40B in free cash flow through 2028, and once its buyback restriction expires on December 9, 2026, UBS says the company could potentially use that cash to buy back more than 40% of its shares at the current price. Morgan Stanley said that memory stocks are trading at attractive prices but their best risk to reward names in the semi space are $NVDA Nvidia and $AVGO Broadcom. 10. Bloom Energy $BE shares are trading lower after New Mexico regulators rejected permits for a gas pipeline planned to supply Oracle’s Project Jupiter data center for the second time. The decision could delay the campus, which is expected to use up to 2.5GW of Bloom Energy’s gas-powered fuel cells. Energy Transfer may now pursue an alternative pipeline route. 11. Intel $INTC plans additional layoffs in its data center group as part of a broader effort to become a more focused and efficient company, CNBC reports. Intel said the unit is realigning roles and skills for long-term success, though the number of affected employees was not disclosed. 12. Trump signed three proclamations under Section 338 of the Tariff Act of 1930 imposing additional 50% tariffs on certain Canadian goods in response to what the White House calls Canada’s discriminatory treatment of U.S. products. The tariffs cover different categories of Canadian imports, including products ranging from wine to hockey sticks to cement, and apply even if goods originate under USMCA. Exemptions include energy, potash, goods already subject to Section 232 tariffs, fish, critical minerals, and certain other products. The tariffs take effect 30 days after signing. WALL STREET IS THE GREATST SHOW ON EARTH,

Although price action has been a bit weak today, some very bullish datacenter/capex news over the past 24 hours... - $IREN signed $2.8B of deals with AI labs, bullish compute - Kimi K3 said over the weekend they are pausing subscriptions because of demand which seems to be entirely consumer and not enterprise yet, bullish compute - $HUT got a 15-year $9.8B deal today, bullish compute - $MSFT is expanding their partnership with $AMD and buying more chips, bullish compute - The Information reported that $GOOGL is developing a new chip to use in-house called Frozen V2, they will have to use many of the chip suppliers in the stack to build more chips, bullish compute The CapEx sentiment shift hasn't gone back to normal and Google earnings this week will be the first test to reaffirm the market's expectations of capex, but plenty of new deals and announcements that continue to be bullish on compute constraints and the trade associated with them overall.

Hedge funds selling tech at a record pace... right into earnings season, days before the capex prints. The Mag 7 report this week and next. If Google raises Wednesday and the rest follow, they just sold the most telegraphed re rate of the year at the bottom.

Mizuho Securities: CPUs & GPUs Market Forecasts & Growth > Shipment Growth: Industry server CPU shipments are forecasted to reach 35 million units in 2026 and grow to 50 million units by 2027, representing a 40% year-over-year increase. > Long-Term TAM: The long-term Total Addressable Market (TAM) estimate for 2030 has been raised to $170 billion (up from the previous $107 billion forecast), driven by higher CPU-to-GPU ratio assumptions for AI inference servers. > CPU-to-GPU Ratios: The CPU-to-GPU ratio on AI servers is accelerating and is expected to approach 1:1 by the end of 2027 or 2028. Supply Chain & Technical Bottlenecks > DRAM Constraints: A critical bottleneck exists in DDR5/LPDDR5 supply, with a projected fulfillment ratio of only 70% over the next 12–18 months. > Demand vs. Supply Gap: Based on current models, the 2027 demand for DDR5/LPDDR5X (over 300 billion 1Gb equivalents) significantly exceeds the projected supply (220–250 billion 1Gb equivalents). > Potential Risks: The shortage of key materials—DRAM, substrates, and passives—is expected to persist through 2027 and could pose downside risks to downstream server assemblers, potentially leading to lower server rack output. Key Player Insights (2027 Forecasts) > Nvidia: Expected to reach 5.0–6.0 million units for the Vera CPU, including 2.0–3.0 million units specifically for agentic AI stack racks. > Google: Axion CPU production is projected to increase more than 2x year-over-year, aligning with the growth trajectory of TPU units. > AMD: The N2 Venice CPU is forecasted to exceed 6.0 million units. GPUs/ASICs Market Growth Projections > Rapid Expansion: The total AI ASIC market is projected to grow from 4.1 million units in 2025 to 24.0 million units by 2028. > Volume Drivers: The growth is driven by substantial increases in deployment by major hyperscalers including Google, Amazon (Annapurna), Meta, Microsoft, and OpenAI. > External Demand: The market for external (non-Google) AI ASIC units is expected to surge from 0.6 million in 2025 to 7.2 million by 2028. Key Hyperscaler Activity > Google (TPU): Continues to be a dominant player, with total shipment units increasing from 2.5 million in 2025 to 7.1 million by 2028. > Anthropic: Significant ramp-up is forecasted for their "TPU Ironwood/Sunfish" chips, moving from 0.6 million units in 2026 to 6.2 million units by 2028. > Amazon/Annapurna: Shipments for the Trainium line are projected to double from 1.5 million in 2025 to 3.6 million by 2028. > Meta: Rapid scaling of MTIA chips is expected, growing from 0.1 million units in 2025 to 2.7 million units by 2028. Technical Trends > Advanced Packaging & Nodes: There is a heavy reliance on sophisticated packaging technologies like CoWoS-L and CoWoS-S, and advanced foundry nodes including N2, N3, N4, N5, and A16. > HBM Integration: Nearly all listed high-performance ASICs utilize High Bandwidth Memory (HBM), with a transition toward newer generations such as HBM3E and HBM4/4E to meet performance demands. > ASP Variance: Average Selling Prices (ASP) range significantly, from approximately $2,000 for entry-level models to as high as $40,000 for top-tier specialized chips like the TPUv10. $DRAM $EWY $MU $GOOGL $AMKR $TSM $ASE $NVDA $AMD $AVGO $MRVL $INTC $MSFT $META

BofA: Kimi 3 The Kimi K3 Release & The Compute Race > New Chinese Open-Weight Model: Moonshot has unveiled Kimi K3, a massive 2.8-trillion-parameter Mixture of Experts (MoE) model with a 1-million-token context window. > U.S. Labs Pressured to Scale: With Chinese open-weight models closing the gap and media reports suggesting Google’s Gemini 3.5 Pro is months behind schedule, U.S. frontier labs (OpenAI, Anthropic, Google) must increase compute. They will need larger training runs, heavier reinforcement learning (RL), synthetic-data loops, and faster release cadences to stay ahead. > Business Over Leaderboards: Investors are cautioned not to confuse benchmark leadership with sustainable business models. The durable moat in enterprise AI is delivering accurate, low-latency, and high-uptime AI at the lowest cost. Bullish Outlook for AI Semiconductors > MoE Architectures Boost Hardware Demand: The shift toward Mixture of Experts (MoE) architectures highlights the critical importance of memory movement, routing, latency, and interconnects. > NVIDIA's Next-Gen Efficiency: NVIDIA's GB300 NVL72 provides up to a 25x performance-per-watt improvement over Hopper when serving leading open MoE models. > Expanding Silicon Demand: Open models are inherently bullish for semiconductors. Even as model value commoditizes, the infrastructure demands for GPUs, High-Bandwidth Memory (HBM), networking, and efficient inference will continue to expand. > EDA Resilience: BofA remains constructive on Electronic Design Automation (EDA) players like Cadence (CDNS) and Synopsys (SNPS). Despite mentions of "open-source EDA at 45nm" in Kimi K3, commercial EDA tools remain entirely mandatory for major foundries like TSMC to manufacture advanced chips. Surging Token Usage & Enterprise AI Adoption > Chinese Labs Leading Token Volume: Data from OpenRouter shows that weekly token usage is proliferating rapidly, with daily token usage on Chinese AI models now exceeding that of Western AI labs. > US Enterprise Adoption Rates: According to the Ramp AI Index, approximately 55% of US businesses now have paid subscriptions to AI tools (significantly higher than the US Census estimate of 21%). > Market Share & Spending: Anthropic leads enterprise model adoption at 42.4%, closely followed by OpenAI at 39.5%. While the median monthly AI spend per employee is just $11, the top 1% of enterprise spenders are averaging a massive $4,833 per employee monthly. $CDNS $NVDA $GOOGL $SNPS

BofA: Google $GOOGL Earnings Preview 2Q'26 Financial Estimates vs. Consensus > Net Revenue: Estimated at $102.1bn (up 25% y/y) vs. Street consensus of $101.0bn. > GAAP EPS: Estimated at $8.38 vs. Street consensus of $2.90. > Other Income Benefit: BofA's significantly higher EPS estimate includes a $80bn one-time mark-to-market benefit from the revaluation of Alphabet’s stake in Anthropic (Anthropic's valuation reportedly surged from $380bn in 1Q to $965bn in 2Q) Segment Performance & Model Revisions > Google Cloud Strength: BofA raised its 2Q Google Cloud growth estimate to 70% y/y ($23.2bn in revenue) driven by accelerating AI demand and a strong backlog. Anthropic has reportedly committed to spending $200bn on Google Cloud over the next 5 years. > Google Search: Expected to grow 17% y/y to $63.6bn. Strong retail search growth is being slightly offset by softness in travel and consumer packaged goods (CPG), alongside minor FX headwinds. > YouTube Advertising: Estimated at $10.8bn (up 10% y/y), which is inline with the Street. Growth is decelerating modestly due to tougher comparisons and automated tools (like PMax) shifting client budgets to Search. > Long-term Revisions (Full Year 2026): Net revenue estimates were raised by 1% to $427bn and full-year EPS estimates increased by 36% to $19.70. Capex Expansion & Infrastructure Leases > Capital Expenditures: BofA notes that higher component pricing (e.g., memory/DRAM) and accelerating AI demand could push Google to increase its CY26 capex range by ~5% to $190–$200bn (BofA models $196bn). 2Q capex is modeled at $50.1bn (up 123% y/y). > SpaceX GPU Lease: On June 5, 2026, Alphabet entered a multi-year agreement to lease 110,000 NVIDIA GPUs from SpaceX, committing to a payment of ~$920mn per month from October 2026 through June 2029 to secure immediate capacity. > Massive Capital Raise: Alphabet raised $85bn in capital ($44.75bn in equity capital/strategic investment and a planned $40bn ATM equity program) alongside issuing $17bn in Euro and Canadian dollar debt to fund AI infrastructure and tax obligations.

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

BofA has Google $GOOGL increasing CY26 CapEx by 5% to $190B-$200B due to higher memory costs...😅

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.

Bloomberg reports $GOOG engineers are hitting capacity constraints when they try to use AI internally. At a company guiding $180B to $190B of capex this year. Gemini 3.5 Pro is months behind schedule. Engineers are now required to use AI to write code and there isn't enough compute to go around. Q1 capex was $35.7B, more than double a year ago, and the CFO already said 2027 will significantly increase from there. $GOOGL reports on Wednesday. If Google can't feed its own engineers, do you really think they lower capex?

Seems $GOOGL is hitting some roadblocks in terms of model development, but in no universe would I bet against Demis.

Switzerland has launched an antitrust investigation into Alphabet $GOOGL over its sudden removal of the Android search choice screen. THE SQUEEZE: Regulators are probing if cutting the setup prompt—which remains active across the EU—unlawfully blocks rival search visibility and forces Google as the default. This comes right after Google lost its appeal against a record €4.1B EU antitrust fine. THE ENGINE: Despite the escalating legal scrutiny, Alphabet's financial fortress stands tall, generating over $422B in total revenue powered by an elite 37.92% net margin. THE RATING: While core operations remain highly efficient, rising global regulatory headwinds keep the Seeking Alpha Quant score locked at a neutral HOLD. Will local regulatory pressure force $GOOGL to bring back the choice screen, or can they defend their 82% Swiss market dominance?

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.

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

I remember when Brad @altcap said Warren was very skeptical about the AI infrastructure capex spending wave, yet Warren still bought Alphabet. Interesting.

CNBC: "Warren Buffett said he — not Berkshire Hathaway’s new CEO Greg Abel — was the driving force behind the conglomerate’s recent big investment in Alphabet" “I initiated it,” Buffett said in an interview with CNBC’s Becky Quick, “The trick in life is to find — I mean investing — is to find businesses that are going to earn high returns on capital for an extended period of time,” Buffett said." “I would say that I don’t like it as well as at least four or five other businesses that we own,” Buffett said." "Buffett also pointed to the enormous capital commitments required to compete in AI as a key issue facing Alphabet and its rivals." “The real question with Google and all of its competitors now, because they’re all laying out hundreds of billions, and that’s real money,” Buffett said."

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

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