Noone is focused on $HPE earnings this week.
In 1 month, $HPE spiked 125% from $20 β $45.
Earnings is exactly like $DELL:
β’ Revenue expected to surge 28% YoY to $9.77B one of the biggest growth quarters in HPE's history
β’ Networking revenue already exploded 152% YoY in Q1 Juniper acquisition turned HPE into an AI networking powerhouse
β’ Data center networking revenue specifically up 382.6% the AI buildout has found its backbone
AI backlog crossed $5B and 64% of orders are enterprise/sovereign, NOT hyperscalers. That's durable, diversified demand
β’ HPE raised full-year EPS guidance to $2.30β$2.50 and lifted networking revenue growth target to 68β73%
β’ Networking operating margins hit 23.7% in Q1 if that holds tonight, this stock re-rates immediately
β’ Q3 is expected to be the biggest AI revenue quarter tonight's print is just the setup, not the peak
β’ HPE has beaten EPS estimates 88% of the time and revenue 75% of the time the base rate is on the bull's side
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$NOW can easily triple from $125 by Jan 2027.
Remember, token use is expected to 2800% in 5 years says $GS.
So these 24 stocks can still 10x-20x:
(COMPUTE / GPU)
1. $NVDA β Every token touches a GPU. 24x tokens = 24x chip demand, full stop.
2. $AMD β MI300X gaining enterprise traction. Second GPU source as hyperscalers diversify suppliers.
3. $INTC β Gaudi AI accelerators + x86 CPUs running inference at the edge and enterprise.
(NETWORKING)
4. $ANET β AI clusters need ultra-low latency switching. 24x tokens = 24x network traffic routed.
5.$AVGO β Custom AI ASICs for hyperscalers. Token volume drives ASIC and switching orders higher.
6. $CSCO β Data center fabric and ethernet switching. Every agent call crosses Cisco infrastructure.
7. $CIEN β Optical networking backbone connecting AI data centers. Bandwidth demand scales with tokens.
(MEMORY / STORAGE)
8. $MU β HBM3E stacked on NVDA GPUs. More inference = direct memory bandwidth demand explosion.
9. $WDC β Flash storage holds model weights and KV caches. Agent scale drives NAND demand structurally.
10. $STX β Hard drives store cold AI training data. Data center storage TAM expands with every model.
(POWER / COOLING)
11. $VRT β More tokens = more heat. Liquid cooling demand explodes alongside data center power density.
12. $ETN β Electrical infrastructure for AI data centers. Power management is the #1 buildout bottleneck.
13. $GEV β Gas turbines and grid solutions powering new data center campuses requiring gigawatt-scale energy.
14. $VST β Power generator selling directly to hyperscalers. AI energy contracts already locked in long-term.
(CLOUD PLATFORM)
15. $MSFT β Azure hosts majority of enterprise agents. Token spend flows straight through its cloud margin.
16. $AMZN β AWS Bedrock is the enterprise agent backbone. More agents, more API calls, more revenue.
17. $GOOGL β TPU infrastructure + Gemini API. Every token processed on Google Cloud prints margin.
(ENTERPRISE AGENT LAYER)
18. $NOW β Enterprise agents run on its platform. Every workflow automated burns more tokens daily.
19. $CRM β Agentforce deploys AI agents across sales, service, and marketing. Per-action token billing scales.
20. $PLTR β AIP platform runs AI agents on enterprise and government data. Token volume is its revenue driver.
(AI INFRASTRUCTURE)
21. $NBIS β Pure-play AI infrastructure at ground level. Token supercycle lifts the entire compute ecosystem.
22. $SMCI β Builds GPU server racks for data centers. Every NVDA chip needs a SMCI chassis to run.
23. $DELL β AI server sales to enterprises exploding. Token growth drives hardware refresh cycles faster.
24. $ARM β Chip architecture inside every mobile and edge AI device. Royalties scale with token proliferation.
$NOW is the most undervalued right now. This is why Jensen Huang says the market has made a mistake on it.
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Yesterday, $DELL spiked 45% after its Q1 earnings.
Options exploded 20000%-30000% in 1 day (rare).
Next week, there's 4 earnings with exact same set-up:
1. $CRWD π Earnings: June 3 (After Close)
As enterprises deploy thousands of AI agents, cloud workloads, and connected endpoints, the security perimeter expands infinitely, making Falcon's AI-driven threat detection not optional but mandatory.
No one builds a $500B AI datacenter and skimps on security. $CRWD is the toll booth on the AI buildout highway and that moat compounds with every new customer and dataset feeding its threat intelligence engine.
Target: $800 median | $700 Wedbush & Benchmark | $750 Oppenheimer
2. $AVGO π Earnings: June 2 (After Close)
Custom AI chip (XPU) demand from hyperscalers accelerating every quarter. $AVGO is the silent infrastructure backbone of the AI supercycle.
While $NVDA dominates training, Broadcom owns the custom silicon layer designing the XPUs that $GOOG, $META, and Tiktok use to run inference at hyperscale, plus the networking chips that stitch datacenters together.
As hyperscalers race to reduce $NVDA dependency and build proprietary AI chips, Broadcom is the only company with the design expertise and manufacturing relationships to deliver.
Target: $500 avg | $480 Susquehanna | $560 high
3. $PANW π Earnings: June 2 (After Close)
Platformization strategy converting AI security budgets into sticky, recurring revenue.
AI doesn't just create new threats it supercharges existing ones, making next-gen cybersecurity a non-negotiable line item for every enterprise on the planet.
PANW's platformization strategy is purpose-built for this world: one unified platform replacing dozens of point solutions, with AI models running across network, cloud, and endpoint security simultaneously.
Target: $320 avg | $340 high | $300 median (75 analysts)
4. $GTLB π Earnings: June 2 (After Close)
AI-native DevSecOps platform controls full dev lifecycle as code volumes explode.
AI is going to produce more code in the next five years than humans wrote in the last fifty and all of it needs to be managed, secured, and deployed somewhere.
While competitors like GitHub Copilot focus on code generation, GitLab controls the entire pipeline and that becomes more valuable, not less, as AI-generated code volumes explode.
Target: $40 median | $60 high (Macquarie) | $27 low (Cantor)
$ORCL earnings is on June 10 and $MU is on June 24. These will explode like $DELL did most likely.
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2 years ago, I called out $ASTS at $2. Its up 6500% so far at $130.
My target at least $200+ when $SPCX IPOs.
Right now, $ORCL is the most obvious play. Its earnings is on June 10 then $MU on June 24.
This year, I explained these would 10x-20x:
$INTC β $AAPL chip deal + foundry turnaround tripled the stock in months (Trump)
$DELL β Pentagon contract + AI server orders created a multi-catalyst monster (Trump)
$MU β HBM memory sold out through 2026, AI supercycle just getting started (Trump)
$NOW β Enterprise AI agents replacing entire IT workflows, 22% revenue growth accelerating (Trump)
$PLTR β Government + commercial AI contracts exploding, revenue up 56% in 2025 (Trump call)
$TE β nuclear power is the only answer to AI's insatiable electricity demand (Leopold call)
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