šŸ¤ Insiders: Tis' Nvidia's World

Nvidia deep-dive, plus if we are investing after 175% YTD stock increase.

"We are at the AI moment for AI." ā€” Jensen Huang

Tis' Nvidia's World

  • Intro

  • How AI works

  • History

  • Business Overview

  • ChatGPT Craze

  • Bulls

  • Bears

  • Conclusion/Recommendation

Intro

Investors are all-in on the AI craze, and their attention has turned to the graphics chip maker that powers the underlying technology, Nvidia. $NVDA has tripled its stockā€™s value so far in 2023 and has gained a staggering $650 billion in market capitalization since its two-year low last October.

Nvidia has surpassed giants such as Tesla, Berkshire Hathaway, and Meta in market cap. And now the company is closing in on Amazon, despite the fact that all of these aforementioned corporations boast considerably higher revenue.

Investors are starting to wonder if the hype is just empty steam, and if weā€™re heading towards an AI bubble.

Thereā€™s no doubt - Nvidia is the leader in the AI race. And everyone knows that. But the question remains - is it too late for investors to get in on the Nvidia hype?

How AI Works

Unless you work in tech, you probably didnā€™t know what a GPU (Graphics Processing Unit) was a year ago. But now itā€™s all the rage.

You know how your computer or game console has a CPU (Central Processing Unit) that helps it think and do tasks? A GPU is like a super version of that.

A GPU designed to be really good at doing lots of calculations at the same time, like solving many math problems all at once. And it turns out Nvidiaā€™s supercomputers work, and are widely touted as the best in the business.

Nvidia also creates special software called its CUDA that helps AI use their GPUs effectively. This software helps AI learn faster, make better predictions, and do cool things like creating realistic images or driving cars.

Right now, other major players in the GPU industry include Advanced Micro Devices, Intel, and even Apple. But Nvidiaā€™s the industry leader in the GPU space, and combining its supercomputers with CUDA cements its dominance.

History

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It turns out Nvidia was started in a Dennyā€™s diner in the 1990s. And it was over the Grand Slam breakfasts that Nvidiaā€™s co-founders began betting on obscure industries like artificial intelligence and video games.

Nvidiaā€™s eccentric co-founder Jen-Hsun Huang became the face of the company. And his strategic bet on GPUs transformed the company.

As major technology players pour billions of dollars into developing their AI programs, they need GPUs to fuel these systems. And Nvidia is the unrivaled supplier in this space. But the company didnā€™t get there overnight.

Nvidia by no means invented GPUs. But they might have perfected it. But how did GPUs go from powering video games to the generative AI craze? It all starts with an audacious bet by Huang.

In the early 2000s, GPUs really could only draw images on a computer screen. And Huang wasnā€™t satisfied there. He realized that not only could GPUs power video games, but they could also power generative AI and what weā€™ve come to call ā€˜deep learningā€™.

Huang embarked on an endeavor, transforming GPUs from mere graphic processors into versatile computing powerhouses.

Back then, Nvidia's annual expenditure on this initiative accounted for $500 millionā€”at a time when the companyā€™s total revenue stood at $3 billion. It was a risky move, but Mr. Huang went all-in on his gamble and belief in the untapped potential of GPUs.

Mr. Huang's vision drove Nvidia to seek new realms beyond graphics rendering. Recognizing the need for computing power that extended beyond drawing images on a screen, Nvidia developed modifications and software advancements that empowered these chips to handle a wide array of complex computational tasks.

Since then, Nvidia has been the undisputed manufacturer of GPUs. And the big dogs like Meta, Microsoft, and Google started buying more of their chips to beef up their AI capabilities in the 2010s. But the release of ChatGPT took everything to a whole different level.

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