SNOWBUNNY ($SNOW)

🚨BREAKING🚨

$BNB reaches new all-time high of $1,000

Keep building $ION $SNOW $ICE

things are moving really fast

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Dear #Snowmen always Remember this referral code “mrcore” when we go live on #Online+

Is almost time 🔥🚀🧑🏻‍💻

$ICE $ION @ice_blockchain #SNOW

GM my CEO @ice_z3us , the tech guru that is behind the BEAST (ONLINE+) that will soon be released to the world. GM also to the @ice_blockchain team for their knowledge that has made the existence of the BEAST (ONLINE+) possible.
$ice & $Snow but the TICKER IS $ION. We're made

Unleashing the #ION beast #Online+. Eventually if Online+ goes live this month as promised by the team, I will use some Local KOLs Nose blow Trumpet. Hope you get it.

#ION $ICE $SNOW

Is @BingXOfficial and @Gate preparing to list $SNOW. They are one among the top holders of Snowman $SNOW memecoin from Ice Open Network.

@ice_blockchain
@robertpreoteasa
@ice_z3us
@ice_apoll0

$PHSE - Pride Holdings Group Expands with New Birdcage Cabaret Lease on Race St. in Cincinnati


$SWKS $CA $STX $CMCSA $SBUX $SNOW $PLAY $NKLA $INO $DKNG $PTON $WKHS $SPAQ $BA $BBIG $ABVC $CDIO $NEXI

. @Snowflake is #1 on the Fortune Future 50 list. ❄️

What a testament to our relentless innovation and the incredible partnership we have with our customers and partners. The future of SNOW + the AI Data Cloud is bright! 🚀🚀🚀

NOBODY WANTS TO LIVE ON SAAS AVE ANYMORE

The digital economy is shifting to Agentic AI Platforms -- here are 8 names best positioned to lead it:

1. $PLTR -- Execution Layer for AI in Gov & Enterprise
2. $SNOW -- Data Liquidity Layer Agents Act On
3. $NOW -- Workflow Backbone Agents Plug Into
4. $CRWD -- Real-Time Security Control Plane for Agents
5. $RBRK -- Cyber Vault Agents Depend On for Recovery
6. $NET -- Edge Enforcement Layer Where Agents Interface with the Internet
7. $MDB -- Memory Plane Agents Keep Reaching For
8. $ZS -- Zero-Trust Gatekeeper for Agent Access

EVERYTHING YOU NEED TO KNOW ABOUT THE AI TRADE

We’re not in an “AI feature” cycle anymore; we’re in an AI economy. Stage one was provisioning -- GPUs, fabs, scaffolding. Stage two is utilization -- turning that capex into tokens, tasks, and outcomes. The debate isn’t “who has the best model” but “who owns the metered points where intelligence becomes revenue.”

$NVDA print wasn’t a blowout, but the signals were clear: Blackwell is already half of Data Center, networking nearly doubled, and CUDA remains default. Growth may normalize, but the moat hasn’t. At this scale, even a license approval can swing billions without touching the core thesis.

$MSFT Azure growth re-accelerated even as OpenAI exclusivity loosened, because inference is the mix shift hyperscalers actually care about. Capex is set to ramp 50%+ into September, RPO keeps stair-stepping higher, and when internal build isn’t enough, Microsoft rents time-to-capacity from neoclouds.

That’s why $NBIS matters. The $17B Azure contract wasn’t GPU rental hype -- it was reserved, SLA-backed capacity financed off project debt and cash flows. At Vineland, economics jump from ~$500M ARR per 100MW to closer to $1.2B with Blackwell/H200 racks and liquid cooling. Microsoft’s endorsement validates Nebius as a peer to $CRWV in the AI factory lane.

$IREN is proving the model from another angle: a $1.2B run-rate, 10x EBITDA growth, and $500M in cash from $BTC economics fund the pivot without dilution. They’ve scaled to 810MW, are commissioning liquid-cooled campuses like Horizon 1 and Sweetwater, and already have GPUs rented under multi-year deals. With 3GW of secured renewable power and NVIDIA preferred-partner status, Iren is delivering clusters on time and monetizing them immediately.

$GOOGL just had its first quarter where AI became a monetization engine across the stack. Search is back to double-digit growth with AI Overviews driving >10% more queries, Gemini 2.5 now reaches 450M+ MAUs, and AI Mode already has 100M+ users. Cloud accelerated to $14B revenue (+32% YoY) with margins above 20% and backlog up 38% to $106B, while YouTube grew 13% with Shorts monetizing at higher rates per watch hour. This isn’t just an ads company anymore -- it’s utility pricing across tokens, models, and infra.

If intelligence is the new GDP, inference is the tax -- and $AVGO owns the meter. The $10B XPU award was full racks-in-a-box, bundling custom silicon, HBM, and Ethernet into time-to-capacity. XPUs now drive most of their AI semi mix, and each new cluster expands networking and software annuities.

And just like Broadcom is taxing inference at scale, $ALAB is becoming the toll booth inside the rack -- its Aries, Taurus, and Scorpio connectivity chips let GPUs, memory, and accelerators actually talk to each other. As clusters get denser, the meter broadens: Broadcom collects at the system level, Astera Labs at the lane level.

This quarter didn’t prove $TSLA already earns from physical AI -- it still makes its money selling cars and energy. But the thematic backdrop just shifted in Tesla’s favor. NVIDIA called this “the age of physical AI,” Broadcom showed inference scaling into racks, and Oracle reframed data custody as the control point for AI workloads. There’s no revenue line yet for robotaxis or Optimus, and that’s why the market still treats Tesla like a $1T startup. But the S-curve setup looks familiar: it’s the only large-cap with a global fleet generating billions of real-world data points, a vertically integrated autonomy stack, and a humanoid program sharing the same neural nets.

This is why I keep leaning into the “agentic platform” lens. Stage one rewarded anyone who could ship silicon and scaffolding. Stage two is about who owns the control points agents need to operate at machine speed. $CRWD is the security plane for real-time detection. $NET enforces policy at the edge. $PLTR wires models into workflows across defense and enterprise. $SNOW liquefies data so agents can act, and $MDB functions as the memory layer applications reach for.

So no, it’s not “too late.” This quarter didn’t close the AI trade or prove how mature this cycle is -- it proved how early we still are. The center of gravity is shifting from pilots to production, and the bottlenecks are visible: compute, power, bandwidth, and control planes. I'm all-in.

15 STOCKS THAT SCALE WITH $NVDA AI ENGINE

1. $TSLA leads physical AI deployment, aligning with Jensen’s vision of agentic systems that move, act & reason in the real world.

2. $AVGO bridges compute, memory & IO with custom silicon -- enabling the low-latency integration Nvidia’s full-system architecture demands.

3. $ASML enables Nvidia’s roadmap with EUV lithography -- making Blackwell, Rubin & future AI architectures physically possible.

4. $TSM builds every advanced Nvidia chip -- its packaging & CoWoS capabilities are foundational to Nvidia’s power and performance profile.

5. $AMD offers the leading alternative to Nvidia’s stack -- MI300X is gaining relevance as demand outstrips Nvidia’s available capacity.

6. $ARM scales low-power compute for inference at the edge -- a core pillar of Nvidia’s shift to distributed, real-time AI workloads.

7. $SNOW operationalizes enterprise AI -- powering the real-time data flows Nvidia called essential to next-gen agentic systems.

8. $PLTR enables sovereign-grade AI deployment -- securing & orchestrating the LLM infrastructure Nvidia is building globally.

9. $IREN expands sovereign-scale compute capacity with vertically integrated, renewables-powered data centers -- turning Nvidia GPUs into scalable, energy-efficient AI infra at hyperscale econ.

10. $ANET unlocks rack-scale GPU performance with high-throughput switching -- essential to Nvidia’s shift from chips to full-stack AI systems.

11. $AMAT rides the complexity curve -- supplying the advanced tools needed to package & manufacture Nvidia’s next-gen multi-die systems.

12. $VRT keeps AI infrastructure cool & online -- supporting the uptime of Nvidia-powered superclusters across the globe.

13. $ALAB solves GPU-to-memory bottlenecks with PCIe & CXL connectivity -- key for maximizing throughput in Nvidia’s high-memory inference workloads.

14. $NVTS provides critical power conversion tech -- keeping Nvidia’s dense compute clusters efficient as AI power demands surge.

15. $NBIS powers elastic, AI-native cloud infrastructure -- positioned to scale Nvidia’s sovereign-grade “AI factories” across global workloads.