$DLR 0.57 Developing

Notable posts

• @StockSavvyShay neutral 1587 eng

  THE NEW AI INFRASTRUCTURE STACK Piper Sandler mapped the new AI infrastructure stack across 8 layers from the power grid all the way to the agent as AI scaling creates bottlenecks across power, cooling, networking, storage, cloud & inference: Layer 1 | Power, Grid & Real Estate • $NEE building renewable power backbone hyperscalers need to scale AI • $CEG monetizing 24/7 nuclear power AI data centers increasingly require • $TLN building behind the meter nuclear power model for AI campuses • $IREN turning scarce power & interconnects into hyperscale AI capacity • $DLR owning physical real estate underneath global AI infrastructure • $EQIX owning interconnection layer where AI networks & clouds meet Layer 2 | Physical Datacenter, Shell & Cooling • $VRT building 800V DC powertrain needed for next jump in AI rack density • $SMCI assembling liquid cooled rack systems that turn GPUs into usable compute Layer 3 | Silicon & Hardware • $NVDA building compute platform underneath AI economy • $AMD building second full stack accelerator platform at hyperscale • $AVGO designing custom AI silicon behind Google TPUs & Meta MTIA as hyperscalers move deeper into proprietary compute • $GOOGL turning TPUs from an internal advantage into a hardware business sold directly into customer data centers • $INTC turning 14A into a real external foundry business with $TSLA as an anchor customer and its largest reported foundry deal yet • $ARM moving into full server CPUs & capturing the full value of the chip instead of dollars per core Layer 4 | Scale Up & Scale Out Networking • $ANET building Ethernet backbone connecting hyperscale AI clusters • $CSCO extending enterprise networking into AI data center fabric • $CLS manufacturing physical networking hardware connecting AI clusters Layer 5 | High Performance Storage • $PSTG using DirectFlash to reclaim power & rack space for AI infrastructure • $DELL bundling servers & storage into an integrated enterprise AI stack • $NTAP connecting enterprise data estates to cloud AI workloads • $HPE bringing enterprise storage into an infrastructure as a service model Layer 6 | Orchestration & Workloads • $IBM turning Red Hat OpenShift into enterprise control plane for private & hybrid AI deployments • $NTNX bringing AI infrastructure stack into private & on prem environments Layer 7 | GPUaaS & Cloud • $CRWV proving GPU residual value with fully priced A100 capacity contracted through 2029 • $NBIS building an AI cloud around 5GW of contracted power with customers prepaying 50% of capex • $DOCN bringing AI compute & inference below hyperscale cloud layer • $MSFT turning Azure into one of largest distribution layers for AI compute • $AKAM pushing AI inference closer to where users consume it • $AMZN monetizing AI through hyperscale cloud infrastructure & its own silicon • $ORCL building AI cloud capacity against a heavily concentrated backlog of large customer commitments Layer 8 | Model Execution, Tokens & Agents • $NET becoming distribution layer between AI agents and the internet as non human traffic crosses more than 50% of its network • $FSLY moving inference closer to the end user through edge compute

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• @StockSavvyShay neutral 961 eng

  WHO GETS PAID IN THE AI CLOUD STACK AI clouds are becoming the middle layer between scarce AI infrastructure and companies that actually need compute: Who supplies the AI clouds • $NVDA sits at center of compute layer by supplying the GPUs that determine how much capacity these platforms can actually bring online. • $MU & $SKHY supply HBM required to keep those GPUs fed as model sizes and inference workloads continue scaling • $DLR, $EQIX, $CORZ & $APLD provide physical data center infrastructure underneath the cloud layer giving AI clouds another path to scale without owning every building themselves. Who turns that infrastructure into compute • $CRWV, $NBIS & $IREN sit directly in middle of the stack by combining GPUs, power, networking and software into usable AI compute that customers can rent. Who buys the compute • $MSFT, $META & $GOOGL are unique because they are both customers and competitors by renting external capacity when internal supply is constrained while continuing to build their own • $SHOP & $CRWD show where next leg can come from as enterprise demand broadens customer base beyond a handful of hyperscalers and AI labs. • OpenAI & Anthropic represent AI lab customer base where demand can scale really quickly as training and inference requirements grow.

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• @StockSavvyShay bullish 743 eng

  THE AI STACK AT ~$8T ARR BY 2030 Truist sees the AI economy shifting where value is captured as hardware monetizes buildout, cloud monetizes compute, models monetize intelligence and applications monetize the work AI ultimately replaces or improves: CLOUD LAYER • $AMZN selling AI infrastructure through AWS while pushing its own Trainium & Inferentia silicon to lower cost of training & inference inside its cloud • $MSFT using Azure to sell GPUs, model access & AI services while distributing OpenAI workloads through one of largest enterprise cloud footprints in the world • $GOOGL selling GPUs & TPUs through Google Cloud turning years of internally developed AI infra into an external compute business • $ORCL building OCI around large GPU clusters & dedicated AI campuses while winning workloads where customers want enormous blocks of compute rather than traditional cloud services • $CRWV is essentially selling Nvidia infrastructure as a specialized cloud by using large GPU clusters & long-term contracts to compete for highest intensity AI workloads • $NBIS is building an AI-native cloud around Nvidia GPU capacity, power & data centers with business becoming more designed around selling large dedicated compute deployments to model builders & enterprises • $IREN starts with the scarce asset most AI clouds need first, energized power & is converting that infrastructure into GPU clusters plus contracted AI cloud capacity • $NSCL is building vertically integrated AI infrastructure around GPU clusters, data centers & sovereign compute deployments HARDWARE LAYER • $NVDA owns accelerator platform at center of the stack through GPUs, NVLink, networking & CUDA which is why almost every cloud & model company above ultimately depends on Nvidia capacity • $TSM manufactures leading-edge logic behind Nvidia, AMD & custom AI accelerators making advanced process capacity one of most important physical bottlenecks in AI • $AMD is building primary merchant alternative to Nvidia through Instinct accelerators & EPYC CPUs giving hyperscalers another full-scale compute platform • $MU supplies HBM & high-performance DRAM where every increase in accelerator performance requires a ton more memory capacity & bandwidth • $SKHY has become one of most important HBM suppliers in AI supply chain by supplying high-bandwidth memory packaged alongside leading accelerators • $DLR owns & develops physical data center campuses where cloud providers & enterprises deploy increasingly power-dense AI infrastructure APPLICATION LAYER • $PLTR turning foundation models into production workflows through Foundry & AIP with value coming from deploying AI against an enterprise’s actual data & operations • $SNOW & Databricks sit at enterprise data layer using Mosaic AI & Snowflake Cortex to turn proprietary company data into the models, agents & AI applications enterprises actually deploy MODEL LAYER • $META building Llama underneath Meta AI & Muse by using its own models to power consumer agents across WhatsApp, Instagram & Facebook while Muse pushes Meta further into an agent that can actually take actions for users • $GOOGL developing Gemini through DeepMind while simultaneously distributing it across Search, Workspace, Android & Google Cloud • $SPCX sits in model layer through Grok & now owns a major application layer after acquiring Cursor for $60B giving it a vertically integrated path from massive GPU infrastructure to models to an AI coding product developers actually use • OpenAI & Anthropic are pushing model layer using GPT, Claude, reasoning, agents & products like Claude Code to turn foundation models into systems that can actually complete work

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• @wallstengine mixed 698 eng

  ROTHSCHILD REDBURN LAUNCHES COVERAGE ACROSS AI DATA CENTER NAMES $NBIS: SELL, $84 PT Says Nebius has a demanding valuation and questions the sustainability of its unit economics. Upside could come from newer-generation GPUs, faster growth of its Token Factory inference business and stronger capacity execution. Risks include customers bringing compute in-house and higher funding costs. $CRWV: SELL, $54 PT Redburn questions CoreWeave's unit economics and ability to convert its pipeline into attractive returns. Key risks include hyperscalers or AI labs bringing capacity in-house, falling GPU pricing and higher financing costs. $DLR: BUY, $227 PT Highlights Digital Realty's global wholesale and colocation footprint, long-term tenant contracts and expansion into larger, higher-density facilities built for AI workloads and hyperscale customers. $EQIX: BUY, $1,261 PT Points to Equinix's global interconnection ecosystem as a key advantage, with AI, HPC, enterprise and cloud customers increasingly needing high-density compute close to networks and other infrastructure. $IRM: BUY, $132 PT Iron Mountain has expanded beyond its legacy records-storage business into data centers, information management and IT asset lifecycle services, while developing more power-dense capacity for AI workloads. The miner-to-AI names were treated much more cautiously: $APLD: NEUTRAL, $22 PT Says unit economics and pipeline-conversion risks are already well priced in. Upside comes from lower build/operating costs and additional large tenant signings. Risks include local opposition, construction delays and tenant insolvency. $IREN: NEUTRAL, $40 PT Sees upside from additional large-scale AI tenants and better execution at existing sites. Risks include difficulty securing tenants, higher funding costs and delays or cancellations. $WULF: NEUTRAL, $15 PT Potential upside comes from securing additional U.S. capacity and signing more major tenants. Permitting issues and state-level opposition are key risks. $CIFR: NEUTRAL, $18 PT Sees better or faster grid-capacity allocation and more major tenant deals as upside. Tenant pullouts and buildout delays are the main downside risks. $HUT: NEUTRAL, $96 PT Upside depends on faster data-center execution and securing additional grid capacity. Delays or cancellations in the buildout remain the key risk. $CORZ: NEUTRAL, $16 PT Core Scientific has been shifting capacity from Bitcoin mining toward AI/HPC hosting after emerging from bankruptcy, while continuing its mining business. Its proposed acquisition by CoreWeave collapsed last year after shareholders rejected the deal.

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• @wallstengine neutral 74 eng

  Today's Key Events (All EST) — 07/23/2026 08:30: US Initial Jobless Claims 08:30: Chicago National Activity Index 13:00: US 10-Year TIPS Auction Before Open 👇 06:00: Thermo Fisher $TMO 06:00: Honeywell $HON 06:00: Cleveland-Cliffs $CLF 06:00: PG&E $PCG 06:30: Lockheed Martin $LMT 06:30: Ameriprise $AMP 06:30: Lazard $LAZ 06:45: Quest Diagnostics $DGX 06:55: RTX $RTX 06:55: Tractor Supply $TSCO 06:55: Dover $DOV 06:55: Roper Technologies $ROP 07:00: American Airlines $AAL 07:00: Comcast $CMCSA 07:00: Nasdaq $NDAQ 07:00: Harley-Davidson $HOG 07:00: Pool $POOL 07:15: Mobileye $MBLY 07:30: Albertsons $ACI 07:30: IMAX $IMAX 07:35: T-Mobile $TMUS 07:45: Union Pacific $UNP 08:00: Freeport-McMoRan $FCX 08:00: Norfolk Southern $NSC 09:30: Infosys $INFY Before Open: Blackstone $BX Before Open: RELX $RELX After Hours 👇 16:00: Intel $INTC 16:05: Comfort Systems USA $FIX 16:05: Deckers Brands $DECK 16:05: Newmont $NEM 16:05: Boyd Gaming $BYD 16:05: RingCentral $RNG 16:05: Digital Realty $DLR 16:05: Robert Half $RHI 16:05: Hartford Financial $HIG 16:05: SS&C Technologies $SSNC 16:05: VeriSign $VRSN 16:10: Kinsale Capital $KNSL 16:15: Edwards Lifesciences $EW 16:15: Boston Beer $SAM 16:30: Sallie Mae $SLM 17:00: Ovintiv $OVV Follow @wallstengine for detailed earnings highlights from many of these companies throughout the day.

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• @wallstengine bullish 43 eng

  DIGITAL REALTY $DLR Q2’26 EARNINGS HIGHLIGHTS 🔹 Revenue: $1.9B (Est. $1.66B) 🟢; +29% YoY 🔹 Adj. EPS: $2.13 (Est. $0.52) 🟢; +14% YoY 🔹 Adj EBITDA: $978M; +19% YoY 🔹 Record Backlog: $1.9B in annualized GAAP base rent Raises FY26 Guide: 🔹 Revenue: $6.85B-$6.95B (Est. $6.76B) 🟢 🔹 Core FFO/Share: $8.15-$8.20, from $8.00-$8.10 🔹 Net CapEx: $4.25B-$4.75B (Est. $4.01B) Other Metrics: 🔹 Rental Rate Increase (Cash Basis): 25.4% 🔹 Cash Rental Rate Growth: +25.4% 🔹 Total Bookings: $307M 🔹 Net Debt/Adj. EBITDA: 4.7x Comments: 🔸 “Digital Realty delivered record Core FFO per share in the quarter, reflecting robust customer demand and strong execution across our core pillars of growth.” 🔸 “We signed more than $100 million of 0-1 MW plus Interconnection bookings for the first time, demonstrating the strength of our connectivity-rich portfolio and boosting near-term growth. We also continued to make strides in our hyperscale and strategic private capital verticals, as we added powered land in the Kansas City metro, accretively purchased interests in three hyperscale data centers in Northern Virginia, and announced the deal to acquire Columbia Capital, a leading investment firm in the digital infrastructure space.”

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• @faststocknewss neutral 12 eng

  VIKING GLOBAL Q2 13F: AMAZON UP 210%, NEW FERRARI AND SPACEX STAKES Largest holdings: - Visa $V: $2.19B - Taiwan Semiconductor $TSM: $1.51B, shares -29% - Air Products $APD: $1.39B - Sherwin-Williams $SHW: $1.33B - Fortive $FTV: $1.22B - Meta Platforms $META: $1.05B, shares +76% - Charles Schwab $SCHW: $981.6M, shares -27% - Thermo Fisher $TMO: $971.3M - JPMorgan $JPM: $949.1M - Lennox International $LII: $911.5M - Amazon $AMZN: $882.1M, shares +210% New positions: - Ferrari $RACE: $816.9M - MSCI $MSCI: $650.0M - Union Pacific $UNP: $556.9M - Digital Realty $DLR: $414.9M - Carnival: $408.5M, repositioned from the US line into the Panama-domiciled shares - CVS Health $CVS: $379.0M - FedEx Freight $FDXF: $357.4M - Morgan Stanley $MS: $339.2M - Qualcomm $QCOM: $279.8M - Aptiv $APTV: $279.5M - AvalonBay $AVB: $252.8M - Snowflake $SNOW: $244.4M - Equitable Holdings $EQH: $236.9M - Take-Two $TTWO: $235.1M - SpaceX: $205.0M, 1.2M Class A shares - BCE $BCE: $180.6M - US Foods $USFD: $177.3M - UBS $UBS: $120.8M Added: - Carvana $CVNA: +343% - Interactive Brokers $IBKR: +247% - Home Depot $HD: +83% - Waters $WAT: +32% - Sherwin-Williams: +25% Exited: - Apple $AAPL: $911.9M - CSX $CSX: $766.7M - Alphabet $GOOGL: $689.0M - PNC $PNC: $629.9M - T-Mobile $TMUS: $623.2M - HCA Healthcare $HCA: $508.8M - Celestica $CLS: $466.2M - Progressive $PGR: $320.5M - AIG $AIG: $317.6M - API Group $APG: $236.5M - Cboe $CBOE: $193.5M - Arthur J. Gallagher $AJG: $157.5M - Lululemon $LULU: $150.1M - Stellantis : $111.9M - CoreWeave : $108.3M Trimmed: - Tesla $TSLA: -78% - Capital One : -76% - Chubb : -71% - ATI : -65% - Medline : -58% - Disney : -46% - General Motors : -45% - Intercontinental Exchange: -43%

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