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HashTechWave > Blog > Computing > Nvidia Become Most Valuable Company: Beating All Tech Giants
Computing

Nvidia Become Most Valuable Company: Beating All Tech Giants

Syed Safwan Abbas - CEO
Last updated: September 12, 2024 4:40 am
By
Syed Safwan Abbas
Syed Safwan Abbas - CEO
BySyed Safwan Abbas
Tech Editor
Syed Safwan Abbas is a senior full-stack developer and the founder of HashTechWave. With over a decade of hands-on coding experience and a deep interest in...
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6 Min Read
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On 19th June 2024, Nvidia Corporation(Nasdaq: NVDA), a tech company mainly known for their graphics cards have become the world’s most valuable company and its market value has reached an astronomical level of $3.34 Trillion USD which took Nvidia on top by surpassing other tech companies like Microsoft, Apple and Samsung.

Contents
  • The Origins of Nvidia: How it Started
  • The Birth First Nvidia GPU having Parallel Processing
  • Pivotal Moments: Nvidia’s Journey to the Top
    • The Power of CUDA: Beyond Graphics
    • How Nvidia GPU’s Became Backbone in AI Development
  • Strategic Moves of Stock Splits:
Nvidia Stock Price growth rate - hashtechwave
CNBC

Nvidia started in 1993 and has become a titan of tech industry. The path of Nvidia is not only limited to the sale of high-end graphics cards. Instead, it is related more towards innovation and well-strategic decisions that make this company a global giant.

The Origins of Nvidia: How it Started

Nvidia company was co-founded by Huang Jensen who is well-known for his former career as a waiter before he decided to get into tech. His vision resulted him in founding of Nvidia, which was actually discussed at a Denny’s diner.

The term ‘Nvidia’ originates is a combination of first letters of two words from Next-Vision. Because Huang earlier worked with AMD and wanted to create his own chips that would be more powerful. That’s the reason he combined “NV” envy from the Latin word which refers to jealousy and expresses the desire to be better than the others in technology.

Denny Diner Image with nvidia startup
Nvidia and Don Feria/AP Images for Denny’s

The Birth First Nvidia GPU having Parallel Processing

Huang Jensen talking on GPU launch event
Huang Jensen in Nvidia Launch Event

Nvidia launched their parallel processing chip named “Nvidia GeForce 256” in Year 1999, that was later marketed as Graphics Processing Unit or GPU. This innovation provided faster and more efficient graphics rendering which was earlier done by CPU and became a game changer in both PC and console gaming world. After GeForce 256 success, GPU became a household name in gaming and tech world so company consistently produced new generations of graphics cards.

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Pivotal Moments: Nvidia’s Journey to the Top

Real turning point for Nvidia was not just producing GPU’s rather it was their investment in Artificial Intelligence (AI). In 2006, Nvidia introduced CUDA (Compute Unified Device Architecture) technology into their GPU’s, that was a software platform that transformed the developer community to utilize full potential of Nvidia GPU’s even for non graphics tasks like data computations.

Nvidia Titan V first look
Nvidia

The Power of CUDA: Beyond Graphics

CUDA allowed developers to take their tasks that would be usually performed one by one on CPU core to be executed by splitting them for parallel processing. This power of Nvidia GPUs, expanded their applications far beyond traditional graphics rendering and unlocked new possibilities across a wide range of industries by making Nvidia’s technology indispensable to video editors, financial analysts, cryptocurrency miners and most notably, AI developers.

How Nvidia GPU’s Became Backbone in AI Development

Nvidia’s vision in recognizing the potential of AI was a game-changer. Most importantly, now any company wants to train and build powerful AI model for themselves which is all possible with power of Nvidia CUDA technology. Being the first company to utilize full power of GPU for developers has made CUDA much popular that now every software provided option for GPU computations for faster tasks execution.

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Nvidia

For the last two decades, Nvidia fabricated Artificial Intelligence into their GPUs for deep learning and neural networks hence became the backbone of AI development. They powered everything from creative medical simulations, enabling of faster drug discovery and Tesla’s sophisticated self-driving algorithms that continue to push the boundaries of autonomous vehicles.

Strategic Moves of Stock Splits:

Nvidia Stock Market Cap in 2024
Nvidia/CNBC

In an effort to grow rapidly in tech market, Nvidia made their shares more accessible with 10:1 (Ten to One) Split in their stocks. This means that new investors can easily afford Nvidia’s stocks and can invest in AI, as current rate of growth could consume alot of energy by 2027 which gives a quick answers to those people who are thinking about how much AI will sustain.

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Informational Note

Concept of 10:1 Split is about division of single stock price into 10 (ten) but the total value of investment will remain same.

Suppose if use of AI become less in future then still your investment in Nvidia will not be in loss because world is going digital, even movies are made using Game engine graphics, surgeons are using their crafts by help of digital twinning of patients before actual operation, also Meta verse is fully powered by Nvidia GPUs. This was the whole strategy that Nvidia got to top in tech industry.

Editors Recommendation:

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  • Beyond Gaming: How Nvidia’s CUDA Tech Boosts AI Computation
  • OpenAI ChatGPT Now Offers Free Image Generation
  • MSI MAG325CQRF-QD Review: Ultimate Monitor for Gamers & Creatives
TAGGED:GPU NewsNvidia

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Syed Safwan Abbas - CEO
BySyed Safwan Abbas
Tech Editor
Follow:
Syed Safwan Abbas is a senior full-stack developer and the founder of HashTechWave. With over a decade of hands-on coding experience and a deep interest in emerging technologies, he leads the platform's coverage of digital trends, smart tools, and developer news. Outside his work, he’s an active tech community contributor and a casual PUBG competitor.
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