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NVIDIA & AI: NVIDIA’s Role in the AI Revolution

Date Modified: 11/04/2024

It is no secret that NVIDIA (NVDA) played a significant role in the development of Artificial Intelligence (AI).

The company has arguably been at the forefront of the AI revolution ever since its involvement in the advancement of Deep Learning (DL) through its GPUs in the 1990s which were used to run DL algorithms.

But what exactly is NVIDIA’s contribution to AI technology and what does it mean for its shares?

Here’s what you need to know:

An illustration of an AI chip

What Does AI Mean?

First, to understand how NVIDIA contributed to the AI revolution, it is important to know the meaning of AI.

AI is a technology that simulates human cognition in software and machines. It is widespread across multiple products we might use on a daily basis such as navigation systems (GPS), Chatbots like OpenAI’s ChatGPT, or digital assistants like Apple’s Siri or Amazon’s Alexa.

To find out more about what AI is, you can read our article titled “Artificial Intelligence (AI) Stocks: Biggest AI Companies.

Types of AI Functions

In order to understand NVIDIA’s AI advancements better, it may also be helpful to learn the different types of AI, with the main types being as follows:

Reactive Machine AI

This type of AI has no memory and is based on an input-output model, whereby the input delivers the same output. In addition, they are considered reactive because they react to certain data. One of the most popular examples of Reactive Machine AIs is the “Recommended” features in streaming services or retail websites.

Limited Memory AI

This type of AI is based on machine learning and operates on historical or past data and is often prevalent in autonomous vehicles (which rely on past data to predict movements), virtual voice assistants, and chatbots.

Generative AI & LLMs

This type of AI is a type of Limited Memory AI that generates different types of content by taking inputs such as audio, text, or video and turning them into new content.

While there are various kinds of generative AI, Large Language Models (LLMs) are considered one of the most popular given their prevalent uses. LLMs can perform functions such as making conversations, explaining, and answering questions.

Popular examples of generative AI include OpenAI’s ChatGPT, Google’s Gemini (previously called Bard), and Microsoft’s Copilot.

NVIDIA’s AI Contributions

For a long period of time, while NVIDIA offered a plethora of products and services, it was widely celebrated as a “gaming company”. Nonetheless, in more recent years, it became more renowned for its involvement in AI, with the main AI contributions being as follows:


NVIDIA created the CUDA software toolkit in 2006, which enabled the use of parallel computing, hence providing the necessary infrastructure for AI functions such as deep learning, natural language processing, and image recognition.

A100 GPUs

In 2020, NVIDIA released its A100 GPU series which are GPUs that are deemed a breakthrough in the AI R&D sphere and also facilitated AI processes such as natural language processing and machine learning and are highly sought after.


In 2022, ChatGPT was launched and made a notable buzz in the tech world. This chatbot was created by OpenAI and Microsoft (MSFT) but was based on the AI infrastructure that runs on NVIDIA’s GPUs.

Why Are GPUs Useful For AI?

Graphic Processing Units (GPUs) are widely regarded as some of the most useful technology innovations for AI. This is due to their capability to conduct complex technical calculations effectively and swiftly.

GPUs are often compared to Central Processing Units (CPUs). Although CPUs are deemed the most important processors found in any computer, GPUs are often accredited for their ability to conduct the aforementioned AI functions faster.

NVIDIA’s Enterprise AI Solutions

As of 2024, NVIDIA’s main AI solutions include generative AI, data analytics AI, AI training, AI inference, speech AI, and cybersecurity AI.

  • Generative AI allows the quick generation of content like 3D models, animation, and sound.
  • Data Analytics uses data science to facilitate AI functions and end-to-end data workflow.
  • AI Training which allows businesses to use generative AI and LLMs in their cloud and infrastructure.
  • Inference can be used across various platforms and applications.
  • Speech AI can be used by enterprises to build conversational AI pipelines that would help them interact with customers.
  • Cybersecurity uses AI to shield data centres from cybersecurity attacks.

NVIDIA’s AI Investments

Beyond its AI products, NVIDIA made its involvement in AI even more robust due to its investments in the companies that advance it:

Arm Holding (ARM)

NVIDIA announced its investment in British semiconductor company ARM Holdings (ARM) back in 2020, whereby it intended to buy it for $40. Nonetheless, the deal did not materialize. Instead, as of February 2024, NVIDIA owns about 1.96 million ARM shares. This is important considering the fact that the majority of smartphones’ CPUs are from ARM and that ARM itself advances AI.

Recursion Pharmaceuticals (RXRX)

In February 2024, NVIDIA announced that it purchased more than 7.7 million shares of biotechnology company Recursion Pharmaceuticals showing how AI can be incorporated into drug development.

Soundhound AI

NVIDIA also announced its investment in Voice and speech AI leader SoundHound AI in February 2024 in which the company owns about $6.6 million shares.

Nano-X Imaging

X-Ray company Nano-X Imaging is also partially owned by NVIDIA, who as of February 2024, owns over 59,000 shares of the Xray company. Nano-X is known for its use of AI in patient diagnosis.

Conclusion: The Future of NVIDIA’s AI

While the future of NVIDIA is unclear, many market analysts believe that the company is poised to grow further and that the AI buzz may persist for longer. As of March 2024, the AI boom drove the company higher as it became the third-largest American company by market value, hence dethroning Alphabet (GOOG).

NVIDIA's price chart from the beginning of 2023 until March 2024

Nonetheless, only time will tell what the future holds for this AI giant.


What is NVIDIA doing for AI?

NVIDIA is investing in AI companies like OpenAI, ARM Holdings, and SoundHound AI. In addition, NVIDIA offers a wide range of AI products such as the Cuda series and A100 GPUs.

Who are NVIDIA’s AI competitors?

Some of NVIDIA’s AI competitors include, but are not limited to, Huawei, Juniper Networks, AMD, and Recogni.

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