Everyone Is Watching NVIDIA. I'm Watching These Instead.
Yesterday I talked about a few names I was looking to accumulate on weakness.
Today, the catalysts are already starting to emerge.
This is exactly why investing isn't about chasing headlines.
It's about identifying where capital is going before the market fully prices it in.
Most investors wait for the good news and then buy.
The problem is that by the time the story becomes obvious, a large part of the upside is usually gone.
The biggest returns often come from owning the right assets before the narrative becomes consensus.
My core thesis remains unchanged:
AI infrastructure spending is still expanding.
Data center investment is still accelerating.
And the companies building the backbone of the AI economy are still being underestimated.
🔹 $NOK $诺基亚(NOK)$
Nokia has been quietly making one move after another.
Individually, the announcements may not seem groundbreaking.
Taken together, they tell a much bigger story.
Nokia is building an ecosystem around Agentic AI, autonomous networking, and multi-cloud infrastructure.
Over the past few days:
• Expanded its partnership with Google Cloud, integrating Gemini into Nokia Assurance Center and launching six specialized AI agents.
• Deepened its collaboration with AWS to accelerate deployment of Autonomous Network Fabric.
• Partnered with Databricks to build a unified data platform, solving one of telecom's biggest challenges: fragmented data silos.
Many investors still think AI agents are years away from meaningful commercialization.
I disagree.
Telecom networks may become one of the first large-scale deployment environments.
The industry is filled with repetitive decision-making, network optimization, fault detection, and operational workflows that are ideal for AI automation.
If AI agents are going to manage critical infrastructure, telecom networks could be one of the earliest proving grounds.
And Nokia is positioning itself to become the operating system behind that transformation.
At the same time, the company continues expanding its U.S. manufacturing and R&D footprint.
From photonic chip production in Pennsylvania to broader domestic investment initiatives, Nokia increasingly looks less like a legacy telecom vendor and more like an AI networking platform.
🔹 $GLW $康宁(GLW)$
Most investors focus on Corning's fiber and data center exposure.
I think the bigger opportunity may be Glass Substrates.
This is one of the most important long-term trends in advanced packaging.
Intel is investing heavily.
TSMC is investing heavily.
Multiple industry leaders are signaling that glass substrate technology could become a key enabler of future chip architectures.
And if that happens, Corning starts from a position of strength.
Glass science and precision materials are exactly where its competitive advantages lie.
At the same time, Corning recently expanded its long-term collaboration with NVIDIA to support U.S. optical connectivity manufacturing.
That gives the company direct exposure to AI infrastructure growth while maintaining optionality on the next generation of advanced packaging.
🔹 $INTC $英特尔(INTC)$
Another interesting development came from Nancy Pelosi's latest disclosure.
She purchased between $1 million and $5 million worth of Intel call options expiring in March 2027 with a $50 strike.
Following politicians is not an investment strategy.
But it does highlight something important:
The market may be starting to reassess Intel's long-term potential.
The debate around Intel has become extremely polarized.
Bulls see a turnaround.
Bears see a value trap.
My view is simple.
If Lip-Bu Tan can successfully restore execution across foundry services, advanced packaging, and next-generation manufacturing technologies, Intel's current valuation may look very different several years from now.
🔹 $MRVL $迈威尔科技(MRVL)$
Among all the names discussed here, Marvell remains one of my highest-conviction AI infrastructure plays.
JPMorgan recently suggested that ASIC shipments could eventually exceed GPU shipments by 2027.
If that thesis proves correct, AI infrastructure will evolve from a GPU-centric ecosystem into a hybrid environment where GPUs and custom silicon coexist.
Marvell sits directly at the center of that transition.
Custom ASICs.
High-speed networking.
Data center interconnects.
Cloud infrastructure.
Few companies have exposure to as many critical layers of the AI stack.
That's why I continue to view MRVL as one of the most overlooked beneficiaries of long-term AI spending.
The market's biggest opportunities rarely appear after the good news arrives.
They appear when the underlying thesis is intact, but sentiment temporarily breaks down.
So far, I have not seen evidence that AI infrastructure spending is collapsing.
I have not seen hyperscalers cutting investment.
I have not seen data center construction slowing materially.
And I have not seen demand for AI compute disappear.
That's why my view remains unchanged.
The names I'm watching most closely are:
DRAM, MRVL, INTC, NOK, GLW, and COHR.
Short-term volatility is inevitable.
Long-term returns are determined by where the industry is headed, not by where the stock traded today.
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