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Hook: Everyone knows Nvidia. But the next AI winners are quietly building the digital backbone of the future.

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Welcome to PyUncut, your weekly deep dive into the markets, money, and megatrends shaping our financial future.

Today, we’re talking about the next wave of AI — and why it may not be about the flashy apps or chatbots anymore.

Everyone knows Nvidia.
It’s the face of the AI revolution — the chipmaker that turned computing into gold.
But as the dust begins to settle, a new generation of companies is preparing to take the lead — not by creating AI models, but by powering the infrastructure that makes AI possible.

In this episode, we’ll explore five stocks that could ride the next AI wave — beyond Nvidia.

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💡 Segment 1: Why AI Infrastructure > AI Applications in 2025

Let’s start with a reality check.

AI applications — think ChatGPT, Midjourney, Copilot — are exciting. But they’re also costly and hard to scale profitably.
Most companies using AI aren’t making big profits yet.
The real money right now?
It’s flowing into infrastructure — the hardware, data pipelines, and automation layers that power AI behind the scenes.

In 2025, this is where the smart money is moving.

As Morgan Stanley recently noted, the AI build-out is transitioning from “model creation” to “model deployment.”
That means massive demand for data center capacity, memory chips, interconnects, and enterprise AI integration tools.

Think of it like the early days of the internet — during the dot-com boom, people were excited about websites.
But the real winners were companies building the routers, cables, and cloud infrastructure.

The same story is repeating — only this time, the “pipes and power” are digital.

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⚙️ Segment 2: Stock #1 — Broadcom (AVGO)

Broadcom is the quiet giant of the semiconductor world.

While Nvidia gets all the attention for its GPUs, Broadcom is building the connective tissue that keeps data centers running — networking chips, custom ASICs, and AI accelerators for hyperscalers like Google and Meta.

They recently announced a $10 billion partnership with OpenAI to co-develop AI chips and infrastructure solutions.
This positions Broadcom at the intersection of AI compute, networking, and cloud hardware.

Financially, Broadcom is a beast.
Its operating margins hover around 60%, and its PEG ratio near 1.4 suggests growth at a reasonable valuation, especially considering double-digit EPS expansion.
The company is also a cash-flow machine, generating over $17 billion in free cash flow annually.

In short — Broadcom isn’t just selling parts; it’s shaping the architecture of the next AI backbone.

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💾 Segment 3: Stock #2 — Micron Technology (MU)

If AI is the brain, Micron provides the memory.

AI workloads — especially training large models — require immense amounts of high-bandwidth memory (HBM).
And that’s where Micron’s story gets exciting.

The company’s HBM3E chips are already seeing record demand from Nvidia and other data center players.
Unlike older DRAM markets that were cyclical, AI memory has a clearer, sustained demand curve driven by compute intensity.

In 2024, Micron returned to profitability after several quarters of downturn. Analysts expect its EPS to grow over 100% in fiscal 2025 — that’s a massive earnings rebound.

Its PEG ratio near 0.9 makes it one of the cheapest AI infrastructure plays relative to growth.
Risks remain — particularly oversupply in the broader memory market — but Micron is positioned in the premium, AI-linked segment where demand is far more resilient.

If Nvidia is the “brain,” Micron is the “memory” that keeps it thinking faster.

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🖥️ Segment 4: Stock #3 — Super Micro Computer (SMCI)

Now, let’s talk about the company that has become every AI startup’s favorite secret weapon: Super Micro Computer.

SMCI designs high-performance servers optimized for AI workloads — from GPU racks to liquid-cooling systems.
And here’s the kicker: while traditional OEMs take months to adapt, Super Micro’s modular architecture allows it to deliver new systems in weeks.

That agility has made it a top supplier for Nvidia’s HGX systems, AMD’s MI300s, and soon Intel’s Gaudi accelerators.
Its revenue tripled year-over-year, and analysts expect another 30–40% growth ahead.

Yes, the stock has been volatile — it ran up over 1,000% and then corrected sharply.
But long-term, it remains one of the purest ways to play the AI server buildout.

The PEG ratio, around 1.2, isn’t cheap — but with expanding margins and strong cash visibility, Super Micro’s growth looks sustainable.

In the AI gold rush, Super Micro is selling the shovels and server racks.

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☁️ Segment 5: Stock #4 — Oracle (ORCL)

Oracle may not sound like an AI darling — but it’s quietly reinventing itself as a cloud infrastructure powerhouse.

Its Oracle Cloud Infrastructure (OCI) has been gaining traction with enterprises looking for high-performance, lower-cost alternatives to AWS and Azure — especially for AI workloads that require custom compute optimization.

Here’s what’s fascinating:
Oracle has partnered with Nvidia, Cohere, and Elon Musk’s xAI to provide AI cloud hosting with integrated data management and training capabilities.
Essentially, Oracle is positioning itself as the “data + compute” hub for the enterprise AI era.

From a valuation perspective, Oracle trades at around 20× forward earnings with a PEG ratio near 1.5 — not cheap, but fair given its consistent free-cash-flow generation.
And the company’s recurring cloud revenue base — now over $20 billion annually — provides long-term visibility.

Larry Ellison called it best: “AI runs on data — and Oracle owns the data infrastructure.”
He might just be right.

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🧠 Segment 6: Stock #5 — Palantir Technologies (PLTR)

And finally, a company sitting at the intersection of AI, data, and national security — Palantir.

For years, Palantir was known as a defense analytics company.
But since launching AIP — the Artificial Intelligence Platform — it has become the go-to software for enterprises wanting to integrate AI into real-world workflows.

Palantir doesn’t build chips — it builds AI orchestration software that sits on top of data and models, helping organizations deploy AI responsibly and securely.

The company’s balance sheet is clean — zero debt, $3 billion in cash — and its free-cash-flow margins exceed 25%.
While its PEG ratio near 2.5 looks expensive, the company’s strategic positioning in defense, healthcare, and government makes it a unique long-term AI infrastructure bet.

Think of Palantir as the “operating system” of enterprise AI — not flashy, but deeply embedded.

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📊 Segment 7: Valuation Talk — PEG Ratios & Cash Flow Visibility

Let’s zoom out for a minute.

When you compare these companies — Broadcom, Micron, Super Micro, Oracle, and Palantir — a common theme emerges:
cash flow visibility and sustainable growth.

AI infrastructure is capital-intensive, yes — but these firms already have cash-rich operations and proven profitability.
That’s a stark contrast to many AI “application” startups still burning cash to chase users.

PEG ratio — the price-to-earnings relative to growth — is one of the best ways to gauge if AI exposure is already overpriced.

• Micron (0.9) → undervalued given growth rebound.
• Broadcom (1.4) → fairly priced with stability.
• Super Micro (1.2) → volatile but justified by speed and demand.
• Oracle (1.5) → moderate growth, predictable cash.
• Palantir (2.5) → premium valuation for strategic moat.

Together, they form a balanced portfolio across hardware, software, and data.

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⚠️ Segment 8: Risks — Overcapacity, Export Restrictions & AI Spending Cycles

Of course, no wave comes without undertow.

The biggest risk for AI infrastructure stocks is over-capacity — if hyperscalers like Amazon and Microsoft pause their buildouts, demand for chips and servers could cool temporarily.

Then there are export restrictions, particularly around high-end semiconductors to China.
This affects Broadcom, Micron, and indirectly Super Micro, which source components globally.

Finally, the AI spending cycle itself is lumpy.
Corporations are still experimenting — not every enterprise will commit billions to AI in 2025.
Expect periods of hype followed by digestion phases, much like cloud adoption in the early 2010s.

That’s why patience and diversification matter.

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🚀 Segment 9: Final Take — The Second Wave of AI Investing

So, where are we headed?

The first wave of AI investing was about discovery — finding the tools that could build intelligence.
The second wave, starting now, is about deployment — building the infrastructure, memory, and automation layers that scale intelligence.

Nvidia will remain the leader, no doubt.
But the next chapter of AI wealth creation could belong to the builders behind the scenes — the chip fabricators, data engineers, and cloud architects enabling this revolution.

Broadcom.
Micron.
Super Micro Computer.
Oracle.
Palantir.

These are the companies quietly writing the code, soldering the chips, and structuring the data that tomorrow’s AI empires will run on.

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Thanks for tuning in to PyUncut.
If you enjoyed this breakdown, make sure to subscribe — we turn complex market trends into actionable investing insight every week.

Stay curious, stay invested, and remember — in every gold rush, the ones selling the shovels often strike the deepest gold.

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