Good morning.
The AI competition that matters most to your portfolio isn't between the US and China.
It's between members of the Magnificent Seven.
Google, Nvidia, and Tesla are fighting very different battles in AI, and understanding their positions could be the difference between catching the next leg up or getting left behind.
After all, the AI trade changes daily. If you miss a beat, you could miss the move.
So today, we're breaking down the current positions of three of the most important companies in the world: Google, Nvidia, and Tesla.
Let’s get to it.
Not financial advice. Always do your own research. Past performance doesn't guarantee future results.
In partnership with Equiscreen
It isn’t.
Every advanced AI system depends on a single physical bottleneck buried deep in the semiconductor supply chain.
For years, this constraint went largely unnoticed. Today, it’s becoming decisive.
- Governments are reviewing it.
- Technology companies are securing long-term access.
- And the companies most exposed to it are already in plain sight.
We’ve published a short report that explains what this bottleneck is, why it matters, how it shapes the future of AI - and which major publicly traded companies are tied to it.
Click here to get the report
Google (GOOG)
Google is looking overwhelmingly strong in the AI race at the moment, and many people already think Sundar Pichai’s company has won. Here are the reasons why:
Google “has an Nvidia inside of it,” meaning that it makes its own TPU (Tensor processing unit) chips as opposed to the GPUs (graphics processing units) that other companies make/use. It then uses those in-house TPUs to train Gemini, its AI model. In fact, no other company has direct access to those TPUs; if you want to use them, you have to rent them through the Google Cloud Platform.
TPUs are specially designed to handle the specific math that powers neural networks, whereas GPUs are like a swiss army knife (good at many things like graphics and crypto mining, but not as great at neural network math). GPUs are the industry standard, but TPUs are Google’s standard.
So Google doesn’t have to pay the huge premiums on Nvidia (NVDA) GPU chips that other companies do because it doesn’t need them. It can use Google-made TPUs that are manufactured directly.
GOOG also owns their entire AI “stack” and is monetizing it effectively: they have the hardware (TPUs), the software (TensorFlow and JAX), and the models (Gemini). Most other AI companies only do one or two of those things well; Google crushes it on all three.
And finally, Google has unbelievable pre-existing AI distribution channels. They have the tech and they can SELL that tech:
Nvidia (NVDA)
Now, Nvidia has the whole stack, too, but their business model is entirely different.
If Google is like an F1 racing team that only builds engines, tires, and frames for its own race cars, then Nvidia is the best engine maker in the world for every other team.
Nvidia sells its GPUs to everyone, including OpenAI, Tesla, Anthropic, Amazon, and Microsoft. Those companies can’t really find Nvidia-level quality anywhere else, which means that Nvidia gets to charge them 70-80% profit margins on their chips. The AI revolution is not cheap, and CEO Jensen Huang is a shrewd businessman!
The moat that surrounds Nvidia is its chip quality and also its software language CUDA. It’s been around for two decades, but in the past few years it’s become like the English of the AI world. It’s just way simpler and more effective for AI companies (new ones and established ones) to work with NVDA chips and code; it just works, and it works better than most other options.
To put it simply: your prospects as a company look pretty great when the other biggest companies in the world are basically forced to come to you for their most important resource.
(Also, Nvidia just got cleared by China to sell H200 chips again… we’ll see if that lasts though. Big if it does!)
Tesla (TSLA)
Tesla is an interesting one, and easily the most divisive of the Magnificent Seven (imagine that).
And if SpaceX and xAI merge with TSLA, things could get even spicier.
Currently, Tesla sells EVs and battery packs/walls. But it also makes FSD (full-self driving) chips and the neural networks used to train Tesla cars to drive themselves. Which sets it up perfectly to train and then sell Optimus robots (starting in 2027), which literally uses FSD and Tesla’s neural networks in its stack. It’s obviously a long-term play; Optimus robots might not be very good for a while yet. But Musk isn’t joking when he says up to 80% of Tesla’s revenue will eventually come from Optimus.
But if SpaceX and xAI merge with Tesla, we have to ask all sorts of questions about what TSLA will be worth as a company. If we add them up:
Tesla market cap: $1.4 trillion
SpaceX target IPO market cap: ~$1.5 trillion
xAI estimated market cap: ~$250 billion
Total: ~$3.15 trillion
But would the synergy between the companies create a premium, driving the stock’s price higher than $3.15 trillion? Or would there be a discount because there might not actually be as much immediate synergy between the companies as investors might hope?
Unclear. But if the three merge, it will certainly shake up the already shaken stock market.
Bottom Line
These three companies represent fundamentally different approaches to the AI revolution:
Google: Vertical integration from chips to distribution
Nvidia: Infrastructure provider with pricing power
Tesla: Autonomous systems transitioning from cars to robots (and potentially merging with space/AI)
All three have compelling narratives, and they all face significant risks.
The AI trade has been running hot for years. Valuations are stretched. The floor could fall out in 2026 if growth disappoints or if the market decides AI infrastructure spending has peaked.
BUT if AI continues scaling (and if these companies execute) the long-term upside cases could be massive.
Understanding their different positions is key if you actually want to trade them. Each one of them is a different bet on different parts of the AI value chain.
Choose accordingly!
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🫡 See You Next Week
That’s all for today’s special edition. We hope you got value from it—reply and let us know if you did.
Until next week,
— Brandon & Blake
The information provided in Stocks & Income is for informational and educational purposes only and should not be construed as financial advice, investment advice, or a recommendation to buy or sell any securities. Stocks & Income is not a registered investment advisor, broker-dealer, or licensed financial planner. Always do your own research and consult with a licensed financial advisor before making any investment decisions. We may hold positions in or receive compensation from the companies or products mentioned. Disclosures will be made where applicable.
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