AMD, The Hidden Gem?

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FUTURE

AMD, The Sleeping Giant?

Today, I will convince you that a company with a price-to-earnings ratio of 99 is undervalued.

Yes, you read that right.

We are returning with company deep dives to discuss Advanced Micro Devices, or $AMD ( ▼ 3.39% ) , which I believe has the highest upside potential for valuation growth in the entire space.

AMD's performance has been underwhelming for several years. However, something just took place that could change the course of this company forever. I believe this so profoundly that it has become the first stock I’ve directly invested in (I previously invested only in index funds).

Besides learning why I’ve made such a decision, you’ll also learn:

How AI hardware works in detail,

How top vendors compare (hardware, software, total cost of ownership (TCO), and more),

Understand the value propositions of disruptors like Cerebras (close IPO) or Groq.

And, finally, comprehend the door of opportunity I believe has opened for the both of us.

This article should interest anyone who wants to profoundly understand the hardware layer and improve their decision-making when dealing with AI.

Let’s dive in.

Before we get our hands dirty, pleas bear in mind this is not financial advice but technical analysis, which are two very different things. I’m an AI expert, not a financial advisor or professional investor.

The reason I’m disclosing my investment is to clarify that I’m biased toward AMD's success.

Keynes said it best: “Markets can remain irrational longer than you can stay liquid,” so even when fundamentals are correct, you can still be wrong, so please do you own due dilligence before making investment decisions.

An Inevitable Transition

Before we discuss the topic, in case you aren’t aware already, I want to introduce you to an idea that will guide you throughout the rest of the article:

AI compute is changing.

The Rise of Inference

For years, AI training represented the largest share of total AI compute. However, this is quickly becoming untrue for two reasons:

AI has been a research-led industry for decades. Models weren’t particularly adopted by the grand masses, so AI was more about a game of creating better AI models in the promise of future demand.

Now, AI is at a crucial time: with technology readiness and ‘return on CAPEX’ pressures, that “future demand” is—should be—now.

The year 2025 should mark the year that AIs become massively utilized by the masses (AI is already around us in our daily lives, mainly through social media algorithms, but that’s not a conscious act of AI usage; actually, it’s closer to manipulation).

Since the rise of foundation models, which can help users with many tasks, an exorbitant amount of compute has been dedicated to training them. While those training runs will continue to rise, as proven by GPT-4.5…

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