CUDA was Nvidia’s first step into artificial intelligence

Nvidia entered its AI era after learning that its chips could be used in industries beyond gaming

Its semiconductor chips were used in the automotive industry, for data centers, and by crypto miners. And starting in 2006, Nvidia took steps that would ultimately transform it into the AI company it’s known as today. This podcast is the second part of a three-part series diving deep into Nvidia’s company evolution.

Nvidia's attempted Arm acquisition revealed its hopes of becoming the world's leading AI company

Though Nvidia's acquisition of Arm, another company that designs semiconductors, was ultimately quashed over antitrust concerns, the attempt offered insights into Nvidia's business strategy. Over time, Nvidia has increasingly focused on using its graphics cards to power machine learning, and its platform CUDA is dominant in the sector.

By 2024, Nvidia had become one of the world’s most valuable companies

Nvidia started as a graphics chip designer for PCs and consoles. This explainer traces its rise from early GPU innovation to powering AI breakthroughs and fueling the data centers behind today’s biggest tech platforms.

Nvidia was founded in a Denny's restaurant

Nvidia is one of a handful of companies valued at more than $1T. In its early days, the semiconductor company sold GPUs, or graphics processing units, that were used for video games. But in recent years, Nvidia’s chips have been used for crypto and AI. Nvidia has faced several setbacks on its journey, including when the US sanctioned chip exports to China.

Nvidia pioneered the GPU industry via its origins as a video game company

From the mid-1990s to early 2000s, Nvidia carved out a niche as a maker of semiconductor chips specially designed for the video game industry. Nvidia broke through the competition to seal deals with TSMC and Microsoft, and popularized the term “graphics processing unit,” aka GPU.

The hardware powering AI was originally designed for video game graphics processing

Graphics processing units are specialized computer chips that can process multiple data streams in parallel, including pixel colors for a display. Such processing is required to find connections across text data and generate outputs quickly.

Nvidia's rapid development of GPUs is forcing computing to depart from something called Moore's law

Moore’s law, named after Intel’s cofounder, predicts that the number of transistors on a chip will double every two years. But Nvidia could be outpacing that prediction.

Nvidia Omniverse can be used to accelerate 3D workflows and explore creative ideas

This video explores different apps available within Nvidia Omniverse that artists can use to create cinematic, virtual worlds. Some of the tools are AI-powered, like a feature that converts spoken audio into a video of a character speaking.

Nvidia CEO Jensen Huang’s keynotes have become a main event at CES

Watch Jensen Huang’s 2025 CES keynote, where he unveiled major advances in AI and GPU technology. His presentations now draw global attention, blending product reveals with sweeping visions of the future of computing.

Nvidia CEO Jensen Huang once saved Nvidia from bankruptcy with a multi-million dollar Hail Mary

Nvidia is now known as one of the top companies contributing to the AI boom, but back in the 1990s, it almost failed. One last-ditch effort conversation that CEO Jensen Huang had with an investor saved the company.

NVIDIA named several computer chip architectures after Grace Hopper

Unveiled in 2023, the GH200 Grace Hopper Superchip, designed for generative AI applications in data center-scale systems, combines a Grace CPU with a Hopper GPU to create a coherent memory model. This allows the Hopper to access Grace data directly, reducing the need to repeatedly copy data back and forth and vastly improving performance.

Over half of Nvidia’s revenue comes from outside the US

This chart breaks down where Nvidia’s revenue comes from—both in terms of which business segments it’s generated by and in which countries. Most of Nvidia’s revenue stems from its computing segment, which includes billions spent by companies building AI.

AI data center growth has created shortages and price hikes in computer parts

The parallel processing needed to power large language models for AI chatbots and other tools drove demand for high-speed graphics processing units to spike in 2025, enabling capital-rich technology companies to price out consumers. Similar demands for the computer memory used in storage drives are expected to keep shortages from easing through 2028.

Nvidia’s RTX graphics chips support ray tracing, which, the company says, can boost performance in games by 25%

Ray tracing allows developers to add more realistic-looking lighting and shadows to video games, and Nvidia continues to improve the tech in newer chips. Rendering light realistically in video games requires immense computing power, and ray tracing “cheats” the process with a little guesswork.

Rival companies AMD and Nvidia's CEOs are related

Advanced Micro Devices (AMD) and Nvidia are two of the world's largest manufacturers of processing chips and are fierce competitors. AMD's CEO Lisa Su and Nvidia CEO Jensen Huang are actually first cousins once removed, but reportedly don't share a close relationship and didn't even meet until later in life at an industry event.

The term 'artificial intelligence' was coined in 1956

Dartmouth professor John McCarthy introduced the term during a summer workshop aimed at exploring how to make machines perform human-like tasks. Two years later, Perceptron Mark I became one of the first neural network machines.

Computational and biological systems share fundamental principles, like randomness

Proposed by Alan Turing and John von Neumann, the concept originates from how DNA and computers run by executing encoded instructions in parallel. The advent of AI and the temperature parameter has seen neural networks mimic the randomness of protein encoding.

The world's first commercial biological computer combines neurons with silicon

Australian start-up Cortical Labs unveiled CL1, a hybrid chip designed to help scientists study brain function in real-time. The 800,000 lab-grown neurons on the chip are kept viable for six months via a built-in life support system.

Machine learning lets computers learn from data instead of relying on programming

ML is a core part of artificial intelligence and is foundational to applications like chatbots, fraud detection, and self-driving cars. Businesses are also adopting it to improve efficiency and identify patterns in data, though the latter may be inaccurate.

Today's massive data centers evolved from single-room mainframes

Punch card computers from the late 1940s were used to store and process a company's data locally before the advent of desktop computers. As the amount of data and company sizes increased alongside the miniaturization of technology, mainframes were replaced by local server rooms and external facilities with interconnected servers running cloud-based and AI software.

Colorado legislates neural and biological data generated by the nervous system

The law expands personal privacy protections to include data from brain activity, marking the first legal step of its kind in the US. It targets companies involved in consumer neurotechnologies, which were previously not required to restrict user data access.

The first computers performed calculations using lightbulb-like tubes

Before transistors, the first electronic computers relied on vacuum tubes—components that switched signals on and off. Despite machines like ENIAC—the first programmable, general-purpose, electronic computer—utilizing nearly 18,000 tubes that generated massive amounts of heat and frequent failures, they laid the foundation for modern computing hardware.

DeepSeek is a Chinese AI startup that rattled US competitors when it made an AI model much faster and cheaper than they did

DeepSeek unveiled an AI model in 2025 that it said was made in two months for roughly $6M. For context, OpenAI has suggested it took over $100M to make its AI model GPT-4. The news rattled the stocks of American tech companies, including leading chipmaker Nvidia.

AI gained mainstream attention with tools like IBM Watson and Apple’s Siri

With the release of ChatGPT in 2022, which drew over 100 million weekly users in just two months, natural language processing and understanding could be achieved at scale via machine learning. Unlike earlier artificial intelligence that could pull stored knowledge, generative AI produces text, images, or sounds.

The first neural devices were cochlear implants, designed to treat hearing loss

Neural interfaces connect with our nervous system to restore or enhance abilities, such as hearing or movement. These neuroprostheses have enabled the restoration of mobility, communication, and activities of daily living that might otherwise require a caregiver.

What are neural networks and why do they matter?

Learn how a neural network works, why it matters, and how it can be trained to recognize patterns, classify data, and forecast future events.

Computex Taipei is Asia’s premier computing and hardware trade show

Held annually in Taiwan, Computex Taipei brings together global tech leaders to debut innovations in processors, GPUs, AI, and next-gen computing—making it a key event for the IT and hardware industry.

Tour Brother Zhang's repair shop to see how graphics processing units are fixed

The workshop repairs 40 to 50 GPUs from across China daily, extending the life of the costly computer parts that are the lifeblood of the hardware powering AI tools. By salvaging working components of different GPUs, custom parts can be built atop printed circuit boards, including custom GPUs that manufacturers do not currently produce.

Clouds' subtle climate effects require significant computational power to simulate

Responsible for reflecting sunlight and preventing thermal energy from entering the Earth system while also trapping energy and keeping it in the system, clouds are understood to substantially influence climate predictions. Because even supercomputers struggle to accurately model their dynamic behavior, researchers have used AI to indirectly incorporate clouds into climate models.

Using deep learning to analyze tumors

The explosive growth of life sciences data is driving artificial intelligence methods to gain traction in biology and medicine — including cancer research.

The Cybathlon is an international competition for assistive technology

The competition pits teams against each other in eight races targeting different innovations, such as arm prostheses, leg prostheses, and vision assistance. Participants in the Cybathlon use it to push the boundaries of technology, including brain implants and assistive software that incorporates AI.

Pixar's earliest days began with a handful of academics developing the technologies they thought might make fully animated movies possible.

DNA computing allows for storage and processing of massive amounts of data

Although costly and less efficient for simpler tasks, as of 2025, DNA could hold 455 exabytes of data with near limitless parallel computation potential in small data centers. Every movie ever made would fit inside the volume of a single sugar cube.

Microsoft's Azure cloud computing platform serves customers in 140 countries

Rather than owning and maintaining hardware on-premises, cloud computing enables users to access large reserves of storage and processing power over the internet, much like customers connect to a utility provider rather than generating their own electricity. This centralization also standardizes security tools and updates.

The Worldwide LHC Computing Grid—a distributed system of 2 billion gigabytes of storage across over 40 countries—manages data produced by the Large Hadron Collider.

AI's growing energy demands are driving tech companies to consider nuclear power

Big Tech has rebranded nuclear power as a green solution to address the strain on the grid from millions of people using power-hungry AI tools. As of mid-2025, generating one image uses as much electricity as charging the average smartphone, or leaving a household light bulb on for 87 consecutive days.

Explore Anthropic Academy, which provides courses on using Claude

The online courses include Claude Code in Action, which teaches software developers how to integrate Claude Code into existing workflows; Claude 101, to learn how Claude can be used to complete everyday tasks; and an AI Fluency series to help educators, instructional designers, and students learn to apply AI in academic settings.

How Model Context Protocol allows AI systems to communicate with databases

Developed by Anthropic, the open-source software serves as an integration layer that standardizes how large language models connect to real-time information sources or tools. Just as a USB-C port serves as a universal standard for many peripherals, MCP streamlines these integrations and provides context about external sources to LLMs in a way that AI can understand.

NASA purchased about 60% of all integrated circuits from 1961 to 1965

The US government adopted the new technology to support the development of the Apollo Guidance Computer, which would help astronauts fly to the moon. This drove manufacturing up and costs down, setting the stage for the modern computing era.

Linux adoption statistics, including its use in all the world's top 500 supercomputers since 2017

This has been driven by kernel-level customizations available with Linux-based operating systems that improve computational performance and reduce latency. As of 2025, Linux's desktop market share is 3.7%, but 87.8% of machine learning workloads run on Linux infrastructure. The Linux OS market is expected to grow 105.8% through 2029.

FLOW-MATIC was the first programming language resembling the English language

As part of the team working on UNIVAC—the first commercially produced electronic digital computer in the US—Grace Hopper helped develop the system that enabled nonprogrammers and businesspeople without a strong mathematics background to use the machine effectively, thereby enhancing the computer's commercial viability.

Fair use may shield AI companies from potential copyright violations

AI models are trained on enormous datasets built from content scraped from websites across the internet. Copyright law includes a four-factor test to determine whether copies of content fall under fair use, but the law's enforcement has been inconsistent.

All computers are defined by their ability to input, store, process, and output data

From wooden machines to wearable tech, computers have changed a lot in appearance, but they all still perform the same essential tasks. Early computers were made of wood and metal—some were so big that they filled entire rooms just to solve simple math problems.

Netflix's recommendation algorithm was born from a $1M competition

In 2006, Netflix launched an open competition for data science teams to develop approaches to outperform its recommendation algorithm. Three years later, the prize was awarded after a group of competitors merged, developing a solution that beat Netflix's internal algorithm by more than 10%. Today, recommendations are based on what users watch, particularly via bingeing.

When you complete a CAPTCHA on a website to prove you are human, you may be unknowingly training algorithms for self-driving cars, whose systems require training data to help identify crosswalks, bicycles, and other outdoor objects.

Explore an animated list of nine scientific breakthroughs funded by NASA, the NSF, and the NIH

Among the technologies made possible by the National Science Foundation and the National Institutes of Health were the CAPTCHA digital puzzles to block bots from accessing sites, the set of diabetes and obesity drugs that fall under the umbrella of GLP-1 receptor agonists, and various cordless appliances, including the handheld vacuum cleaner. (Some readers may experience a paywall.)

A breakdown of algorithms, how they are constructed, and their applications

Algorithms are instructions for accomplishing a goal and typically take the form of a step-by-step procedure. Given the conditions, these procedures can take various paths, increasing an algorithm's complexity. While traditional computer algorithms are programmed to account for all possible scenarios within a given process, machine learning systems build their own rules from data-driven patterns.

Explore the components of autonomous vehicles controls

A suite of cutting-edge hardware and computation-intensive software creates the potential for self-driving cars to be safer, more fuel-efficient, and more accessible to a broader range of drivers. However, automation also introduces potential cybersecurity threats.

Quantum computers harness weird physics to explore unsolvable problems

Classical computers manipulate bits as either 0 or 1, but quantum computers use qubits to hold combinations of both, enabling new algorithms. This new approach could one day help with breakthroughs in medicine, chemistry, and AI.

Take a deep dive into the neuron

Neurons are the basic unit of the brain and nervous system—electrically excitable cells that sends signals throughout the body. They can communicate with each other, fire in sequence, and conspire to do everything from drive body movement to help form memories. Check out this intro-level overview to learn more about their structure and how they work.