The Four Short Term Winners of AI

When How You Start Determines How You Finish

Learning and innovation go hand in hand. The arrogance of success is to think that what you did yesterday will be sufficient for tomorrow. —William Pollard

[The] pace of innovation is all that matters in the long run. —Elon Musk

Innovation is moving at a scarily fast pace. —Bill Gates

Above: AIsop’s interpretation of The Tortoise and the Hare.

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The global AI arms race is at the end of the beginning.

Though a marathon not a sprint, Aesop’s “Tortoise and the Hare” does not apply; slow and steady will not emerge victorious.

Rather, the contenders that start fast and get out front early can run away with the whole thing. Of these, four speedy sprinters stand out.

1. Big Tech Firms (e.g. Google, Amazon, Meta, Microsoft, et cetera)

2. Chipmakers (e.g. NVIDIA, Micron, Intel, et cetera)¹

3. Intellectual Property Lawyers

4. The Big 4 (EY, PwC, Deloitte, KPMG)

Let’s take these in order:

Big Tech Firms (e.g. Google, Amazon, Meta, Microsoft, et cetera)

Unfortunately, the big will continue to get bigger. The key to winning this race is the double Ds: data and dollars. To say that companies like Apple have both of these in spades is putting it mildly.

More, the cash piles of these respective titans are fueling AI’s Cambrian explosion. Feast your eyes on the below headlines and graphs. Try not to weep:

• Google CEO Sundar Pichai announces $120M fund for global AI education

• OpenAI closes in on largest VC round of all time from Apple, Nvidia, Microsoft, and others

  • OpenAI is expected raise around $6.5 billion at a $150 billion pre-money valuation. For context: $150 billion is what the entire U.S. venture capital market had under management in 1999, which fueled the internet bubble.

    $6.5 billion is the amount raised just 10 years ago (2014) by all startups in New York, Texas, and Florida combined.

  • OpenAI is requiring a $250 million minimum investment.

Chipmakers (e.g. NVIDIA, Micron, Intel, et cetera)

AI workloads require a dramatic step-up in computing, networking, and software intensity. Nvidia, in my opinion, is best-positioned to win in all three domains. It is the mother of all pick-and-shovel plays and represents the winning horse in the race to end all races.

Revenue explosion notwithstanding, actions speak louder than words numbers.

One particular anecdote stands out: To source the 131,072 GPU Al "supercluster," Larry Ellison appealed directly to Jensen Huang, during a dinner joined by Elon Musk at Nobu. "I would describe the dinner as me and Elon begging Jensen for GPUs. Please take our money. We need you to take more of our money. Please!”

At the point where, as of this writing, the richest and third-richest men in the world are begging to give you billions of dollars, you have power and leverage that would make even the proudest emperor blush.

Intellectual Property Lawyers

Per Jane Austen, it is a truth universally acknowledged, that men are greedy and possessive (see all of history and the endowment effect). On a long enough timeframe, everything boils down to ownership. After all, property appears alongside life and liberty in the triad of natural rights.

Generative AI platforms are trained on billions of parameters that are constructed by software processing gigantic archives of images and text. The AI platforms uncover patterns and relationships, which they then use to create rules, and then make judgments and predictions, when responding to a prompt.

This process comes with tremendous legal risk, including intellectual property infringement. It also poses legal questions that are still being resolved:

• Does copyright, patent, trademark infringement apply to AI creations?

• Who owns the content that generative AI platforms create for you or your customers?

These claims are already being litigated in two landmark cases: Andersen v. Stability AI et al and Getty Images v. Stability AI.

When the wheels of justice stop their slow turn, we’ll see who ends up on top.

The Big 4 (EY, PwC, Deloitte, KPMG)

For many white-collar workers, AI remains just a fuzzy, vague concept—two letters that stand squarely in sight, but just out of reach.

Knowledge is not understanding; there's a difference between knowing that π exists and using it to calculate a circle's area or circumference.

Many know that AI exists, few know how to use it to lighten and streamline their professional workload. Per Checkr, 15% of American workers have never used AI to get work done.

The Big 4’s AI practices will help bridge the chasm between AI being an interesting, vague idea and an essential tool. By doing so, they stand to make a ransom.

Collectively, they have invested over $4 billion in their AI tools/practices. Because of this investment, Paul Knopp, Chairman and CEO of KPMG US expects “to generate about $12 billion of additional revenue over the next several years.” He grossly underestimated things.

In 2023, Deloitte ($23.2 billion), PwC ($22.6 billion), EY ($16.1 billion), and KPMG ($15.9 billion) alone made a staggering $77.8 billion from AI advisory services.

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Against such a formidable roster, you might ask: Why bother running? The race is over before it's even begun.

Au contraire, though the table’s been set, we have yet to get to the main course. 

As armchair AI expert, I believe we are currently descending from the peak of inflated expectations to the trough of disillusionment:

Put simply, we are riding on the fumes of Google’s 2017 Transformer breakthrough, focusing on "faster horses" in the words of Henry Ford.

Instead, we need a "carburetor" to take AI from good to great. 

After all, it’s not how you start but how you finish.

The gun has gone off and the race is on.

We’ll see who ends up on the podium of this decades-long race.

It is perhaps the most important that humanity has ever run.

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Per my about page, White Noise is a work of experimentation. I view it as a sort of thinking aloud, a stress testing of my nascent ideas. Through it, I hope to sharpen my opinions against the whetstone of other people’s feedback, commentary, and input.

If you want to discuss any of the ideas or musings mentioned above or have any books, papers, or links that you think would be interesting to share on a future edition of White Noise, please reach out to me by replying to this email or following me on Twitter X.

With sincere gratitude,

Tom

1. Micron and Intel are included to be polite. NVIDIA is the top dog and has perhaps a decades-long lead over any “competitor.”