GOOGL — expert X mentions

The next trillion dollar opportunity in stocks isn't building AI. It's FIXING it. McKinsey just surveyed 496 companies. These companies are spending billions on • Fixing AI inaccuracy. Up 14 points from last year. • Fighting AI cybersecurity threats. Up 6 points. AI is being deployed everywhere. But it hallucinates, it gets hacked, and it makes mistakes that cost real money. The companies solving this will print. 1. AI Inaccuracy - every enterprise deploying AI needs this fixed. Wrong outputs, bad decisions, compliance failures. One hallucination in healthcare or finance can cost millions. Every company using AI is now a buyer of accuracy tools. Companies like $PLTR, $SNOW, $MDB, $DDOG, $ESTC, $CFLT, $BRZE and $AUR are trying to fix AI inaccuracies. Platform plays like $MSFT and $GOOGL are also embedding accuracy guardrails directly into Azure AI and Vertex. Every enterprise using their cloud is a customer. 2. AI Cybersecurity - every AI agent deployed is a new attack surface. Every model is a new vulnerability. Every data pipeline is a new target. Companies can't deploy AI without securing it first. Cybersecurity companies like $CRWD, $PANW, $ZS, $FTNT, $S, $VRNS, $TENB, $RPD are the pure plays. And security infrastructure like $ANET, $AKAM are also applying security at scale. 88% of companies are deploying AI. Most haven't solved accuracy or security yet.

Given that Google is already telling people to look ahead to Gemini 4 (likely still many months away) it’s obvious that 3.5 Pro is a failure. Someone should ask Sundar tomorrow why Google now ranks an embarrassing SEVENTH in the world in AI models, why 3.5 Pro flopped, why Google is DOA in the most important AI agentic coding market, and why they keep losing key talent to OpenAI and Anthropic.

A TON OF THINGS HAPPENED IN THE STOCK MARKET TODAY. Here's a full recap: 1. Rocket Lab $RKLB won a $266M U.S. Air Force contract, extending its momentum in defense. The launches are expected to take place in Alaska and be completed by the end of 2028. The award adds to Rocket Lab’s growing streak of defense contract wins as the company continues expanding its role in national security space missions. 2. BofA is staying bullish on the memory trade, arguing that Chinese open-source AI models strengthen the long-term demand case for $MU, $SKHY, $SNDK, $STX, and $WDC. The firm reiterated its Buy rating on Micron $MU with a $1,550 price target, saying cheaper Chinese model pricing does not mean lower hardware intensity. BofA notes Kimi K3 API pricing is reportedly 5x–350x below Western models, but says that reflects business-model choices rather than the true cost of compute infrastructure. The firm also highlights that Kimi K3 needs roughly 1.4TB of HBM per serving instance, while larger AI models should require the same or even more memory as weights and active parameters grow. BofA also sees CXMT focused on commodity DRAM rather than advanced HBM, and notes Micron’s CHIPS Act restrictions may expire around December 2026, potentially opening the door for $50B–$60B in annual buybacks. 3. Moonshot AI is reportedly targeting a valuation of up to $50B in a final pre-IPO funding round after launching Kimi K3. The company is expected to close its current round at a $31.5B valuation before starting another round of fundraising talks in August, ahead of a potential Hong Kong IPO that could come as soon as this year. 4. Tesla $TSLA detailed its 2026 Summer software update, with rollout expected soon. The biggest change is deeper Grok integration, letting drivers use voice commands to place calls, control music, change climate settings, and open the glovebox. Tesla is also bringing self-driving stats into the mobile app, making them viewable and shareable, while navigation will get smarter by surfacing routine destinations and favoring routes the driver has taken before. The update also adds the ability to set a preferred arrival battery level from the app, upload custom vehicle wraps without a USB drive, and lock rear-screen controls from the front display. 5. Nvidia $NVDA says it could eventually produce up to 1,000 Vera Rubin racks per day. If reached, that scale would imply more than $630B in quarterly revenue for Nvidia and its manufacturing partners, based on estimates cited in the post. Nvidia’s hardware engineering SVP Andrew Bell said the company’s manufacturing partners should be able to make up to 1,000 racks per day once production ramps, highlighting the massive revenue potential tied to Vera Rubin if AI data center demand continues scaling. 6. Sam Altman is expected to brief the Trump administration and members of Congress next week on OpenAI’s next family of models, including their capabilities and potential impact on jobs. A new release may be getting closer, though OpenAI has not officially named the models GPT-6 or announced a launch date. 7. Jefferies came away impressed after testing Meta’s $META AI glasses, highlighting the camera quality, seamless setup, and normal-glasses form factor. The firm says Meta has a first-mover advantage as the only player currently shipping AI glasses at scale. Jefferies estimates the category could become a $14B–$18B hardware revenue opportunity within the next few years, assuming Apple Watch-like adoption at an average selling price of $400, or roughly 35M–45M units. The firm also sees upside from AI subscriptions, advertising, and commerce over time. Jefferies noted Meta AI now has around 1B monthly active users, daily glasses users are tripling YoY, and more than 7M units were sold in 2025. Jefferies says the bigger opportunity is commerce, as AI glasses could capture user intent at the point of discovery if agentic AI shifts behavior from browsing to delegation. units in 2026. 8. Supermicro $SMCI gave a major preliminary update after hours. Fiscal Q4 revenue is expected to land near the low end of its $11B–$12.5B guidance range, but the bigger surprise is gross margin, now expected at 15%–17% versus the prior 8.2%–8.4% forecast. Last quarter, SMCI was guiding gross margins around 8.4%–8.7%, and its TTM gross margin is only 8.83%, making this a dramatic improvement in just 90 days. The company also said it received more than $60B in new orders during the quarter, pushing backlog to a record high, though some orders could still be delayed or canceled. Full results are due August 11 9. Google $GOOGL is rolling out Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and a new limited-access cybersecurity-focused model. Gemini 3.6 Flash is designed to be more efficient, using up to 17% fewer tokens while also lowering cost per token. Flash-Lite is aimed at faster, high-volume use cases where speed and scale matter most. Google is also introducing Gemini 3.5 Flash Cyber, a model built to find and help fix software vulnerabilities, though access will initially be restricted to governments and trusted partners. 10. The top 10 most active options today by contracts traded were $NVDA with 2.3M contracts, $AAPL with 1.1M contracts, $MU with 977K contracts, $TSLA with 887K contracts, $SPCX with 752K contracts, $INTC with 656K contracts, $AMZN with 511K contracts, $NFLX with 509K contracts, $AMD with 410K contracts, and $MSFT with 387K contracts. 11. CoreWeave $CRWV says near-term profitability is being weighed down by a timing mismatch in its AI infrastructure rollout. New capacity starts depreciating roughly six weeks before contracted customer revenue begins coming in, creating pressure on reported earnings. The company is carrying about $30B of debt to fund 49 operating data centers and future deployments, with depreciation and interest equal to 81% of Q1 revenue. CEO Michael Intrator expects that drag to lessen as more installed capacity converts into revenue. CoreWeave’s financing is supported by long-term customer contracts, where clients must pay for reserved capacity whether they use it or not. 12. Short interest across U.S. equities is climbing to extreme levels. In the S&P 500, short interest has risen to roughly 3.7% of free float, near the highest level in data going back to 2010. For the Russell 3000, short interest is around 6.1%, also close to an all-time high, with both measures steadily moving higher since the start of 2025. Across all NYSE-listed stocks, short interest reached a record 9.0% of shares outstanding in late June. For context, that same metric peaked near 5.0% during the 2008 Financial Crisis and around 6.0% during the 2020 pandemic. WALL STREET IS THE GREATEST SHOW ON EARTH.

Google: "Beyond today’s releases, Gemini 3.5 Pro is currently testing with partners and we plan to make it broadly available as soon as it’s ready." Gemini 3.5 Pro is NOT READY

Google releases smaller Gemini 3.6 models before 3.5 Pro? Yikes. https://t.co/psn6nfW2CJ

Google Is a Secular Short https://t.co/gYqTUFh50D

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