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Hype or Paradigm Shift?

„The Navy revealed the design of a computer today that it expects will be able to walk, talk, see, write, reproduce itself and be conscious of its existence“

– New York Times

GAI.

Generative Artificial Intelligence.

That is the buzzword of the moment. It is the new era of automation.

Unlike traditional artificial intelligence, which focuses on pattern recognition, GAI can independently generate new content (new text, images, audio, software code, etc.). To do this, it must be trained by a machine learning model.

We have moved from distinguishing whether a picture is “a cat or a dog” to generating an output from an input, e.g., “paint me a picture of a cat sitting next to a dog”. This ability to self-generate new content through prompts in natural language is what makes GAI so powerful. It mimics the learning and creative abilities of the human brain.

It is called generative because it creates something unprecedented based on historical data.

The best-known example of GAI is OpenAI’s ChatGPT, which has amassed millions of users in just a few months.

GAI models are only as good as the data on which they are trained.

To handle the data, powerful supercomputers are required.

This is where graphic processing units come into play.

In short: GPUs.

Chart 1: Time it Took for Selected Online Services to Reach 100 million users

Source: World of Statistics

Brain & Eyes

GPUs are the core technology needed for AI applications. They have enhanced mathematical computation capability, making it ideal for machine learning.

ChatGPT uses 10,000 GPUs.

In the GPU and GAI space, there is a picks and shovel supplier. It has the most technologically advanced products and, therefore, has a near-monopoly with a market share of over 80%.

It is Nvidia.

How come?

First-mover advantage. The invention of the GPU in 1999 is credited to them.

And specialization.

It is because of the brain & eyes comparison. Or CPU & GPU.

Imagine your computer is like a person. To understand things and think, it needs a brain and eyes. The brain is the Central Processing Unit (CPU), and it is like the smart part that figures out problems and thinks logically, just like our brain does. Whereas the GPU is like the eyes. It focuses on pictures and visuals, creating all the images you see on the computer screen, just like our eyes help us see the world around us.

This is where the two main competitors, AMD and Intel, come into play. They lag years behind in GPU technology.

Why?

Because they have one’s cake and eat it, too. Nvidia’s supremacy and pure focus on GPU has left them lagging due to their attempts to cover both CPU and GPU, preventing specialization and hindering technological advancement.

Remember: be an ant!

Chart 2: Add-in Board GPU Market Share in %

Source: John Peddie Research

Hype or Paradigm Shift?

With ChatGPT’s official release in November 2022, Nvidia became the seventh US company to reach a $1 trillion market cap.

The chipmaker’s valuation by the usual metrics is driving investors crazy.

A war of opinion is erupting!

Is GAI a hype or a paradigm shift?

How can one properly assess such future market potential?

The technology sector is plastered with the “Next Big Thing” that promises to take the world by storm. In many cases, it is more hype than reality – consider autonomous driving, the metaverse, Web 3.0, and cryptocurrencies.

The good thing about it? Nvidia as a picks and shovel supplier profits from all these hypes. GPUs are needed everywhere.

A sweet spot.

What is more, it is easy for the media to write about it and achieve their goal – plenty of clicks.

Example?

The prestigious Time Magazine is still not quite sure what to make of AI. The more doom and gloom, the more clicks. Their latest special report states that AI researchers predict a 4% chance of serious negative consequences from advanced machine intelligence – meaning an extremely bad outcome, e.g. human extinction.

Will this be the end of humanity?

Not so fast.

Chart 3: Time’s Magazine Cover in March & June 2023

Source: Time, X

Seize, do not fight

GAI might be fundamentally different.

It is applicable to virtually all industries and has the potential to unleash a new wave of productivity and innovation in the global economy.

It is so impactful.

It represents the next big technology platform shift after the internet, mobile, and the cloud and according to William Blair (Generative AI: The New Frontier of Automation) it has the potential to be as transformative to the global economy as the steam engine and electricity.

History does not repeat but it often rhymes (thank you, Mark Twain). Hence, we note that paradigm shifts in technology have historically not resulted in a reduction in employment, but instead have led to the creation of new roles and reduction of labor inputs in certain existing roles.

In our opinion, it will not be a threat.

It is more of an enabler.

Seize it.

Oh, before I forget…. Today’s quote is from 1958!

Chart 4: Nvidia ($NVDA) vs. S&P 500 ($SPX) over 5 years

Source: TradingView

arvy’s takeaway: GAI is rewriting the automation landscape, going beyond pattern recognition to independently creating new content. Nvidia’s dominant position in GAI, with its GPUs powering this transformation, mirrors the gold rush’s pick and shovel suppliers. Amidst concerns, historical patterns show technology shifts do not eliminate jobs but reshape them. But it will not happen overnight.

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