The One Chart Nvidia Investors (NVDA) Worship

Back in 1993, you could get an all-you-can-eat Denny's Grand Slam breakfast for $3.99…

Pancakes. Scrambled eggs. Bacon.

Yum. Bacon.

And one 15-year-old busboy in a San Jose, California restaurant shuttled plate after empty plate after plate back to the dishwasher…

And dreamed of doing more with his life.

Little did he know that he would return to the very same restaurant years later to found one of today's hottest stocks.

That busboy was Jensen Huang, the co-founder and CEO of NVIDIA.

Years later…

After graduating college, he found himself back in the same Dennys.

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Sitting in a booth he and his friends sketched a vision that would eventually revolutionize the tech industry.

That meeting led them to design and produce a new computer chip that would transform video gaming…

But what they couldn't have predicted was that the same chip design would end up driving the future of artificial intelligence…

And have Nvidia chasing ONE exponential chart that looks like this…

A chart that says: the more compute you throw at AI, the better it gets.

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The chart above illustrates the "compute scaling law," showing that as you throw more compute at an AI model…

The smarter it gets.

More compute… better models, better products, bigger profits for Nvidia.

There’s a predictable pattern that connects compute to performance, no matter the model size.

So, what is compute?

Compute is an “all you can eat” combination three things: processing power, memory, and networking.

Processing power comes from chips like NVIDIA’s GPUs.

Memory stores the oceans of data that AI needs to learn.

Networking ties everything together, moving data quickly between processors.

NVIDIA, under Jensen's leadership, has focused on all three…

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Ensuring their GPUs can handle the massive data and networking demands of modern AI.

Jensen's belief in this chart is the key to their AI dominance.

The other Magnificent 7 stocks —Tesla, Meta, Alphabet, Microsoft, and Amazon— do too…

And they are all buying NVIDIA's hardware to push their own AI visions.

NVIDIA's big bets to support their vision are their Hopper and Blackwell chip architectures.

Hopper, designed for high-performance computing and AI, focuses on scaling up the processing power needed for training massive AI models.

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Blackwell, their next big leap, is poised to further enhance the efficiency and power of NVIDIA's GPUs, making them even more suitable for AI at scale.

These 5X more powerful chips are now just coming off the production line.

Jensen says — and this is a direct quote — “Demand is Insane.” 

In fact, Blackwell is SOLD OUT for the next 12 months.

That’s nothing.

Nvidia's growth trajectory is about to get even insaner.

A quick lesson…

GPUs handle two major tasks:

Training: The behind-the-scenes machine learning work.

Inference: The real-time processing, like answering questions on ChatGPT.

Currently, 40% of Nvidia's revenue comes from inference…

But Jensen Huang (CEO) suggests it could reach 90%.

Why?

Chain of reasoning.

Chain of reasoning is a concept where a prompt is passed multiple times, creating layers of responses.

Instead of a single prompt generating one inference, it can generate ten, a hundred, or even a thousand inferences.

That can be…

1. “Stopping and thinking” before giving a response to a prompt. Think of it like having a “deep thinker” for your prompt.

2. Passing a prompt to multiple agents. Think of it like having a “team of experts” for your prompts.

This means an EXPONENTIAL increase in demand for hardware capable of processing all these layers.

Jensen even mentioned inference could grow by a billion times — and Nvidia would be powering most of it.

That’s a direct quote.

A billion times!

Why would anyone bet against the hardware enabling the Singularity?

It would be like betting against the 8088 during the rise of home computing…

The Pentium during the rise of the Internet…

And betting against YouTube when there were cat videos like these.

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Always be prospering,

socrAItes

Publisher, Sage Research