The term GPU was first used by Sony in 1994 to refer to the geometry processing unit inside the PlayStation console, five years before Nvidia's marketing of the GeForce 256 revised the acronym to graphics processing unit.

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.

Although GPU stands for graphics processing unit, the acronym is often used to refer to a graphics card—an assembly that houses the microchip along with supporting components.

The history of graphics processing units began with hardware for displaying visuals in arcade machines, but the transition to 3D graphics led to the microchips and software that power today's AI data centers.

Graphics processing units, which process large amounts of data in parallel, have become the foundational hardware for AI systems that rely on hardware capable of processing millions of text parameters simultaneously.

Watch a tech demo of the world's first consumer graphics processing unit, the Nvidia GeForce 256, released on October 11, 1999.

Take a virtual tour inside the NVIDIA GA102 graphics processing unit to explore the architecture that enables it to perform over 35 trillion calculations per second.

CUDA, the computing platform that transformed graphics processing units from pixel renderers into general-purpose components powering AI, originated from a computer science student.

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 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.

Nvidia controls more than four-fifths of the GPU market—but isn't considered a monopoly

Semiconductor company Nvidia has a commanding market share when it comes to graphics processing units. Its competitors include Advanced Micro Devices and Intel, which together account for less than a fifth of the GPU market.

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.

CUDA was Nvidia’s first step into artificial intelligence

CUDA (Compute Unified Device Architecture) is a parallel computing platform that was developed by Nvidia in the mid-2000s. By letting people perform computations in parallel, rather than sequentially, CUDA allowed people to compute large amounts of data quickly. CUDA has been used to build machine-learning models as well.

With many smaller computing cores, graphics processing units process many identical tasks in parallel, whereas central processing units have fewer, larger cores built to handle a wide variety of more complex tasks sequentially.

As of 2025, Nvidia controls over 90% of the discrete graphics processing unit market, with its high-end components serving as the backbone for the AI data center boom, followed by AMD and Intel.

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 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.

When buying a custom computer, selecting integrated graphics is more affordable, but a dedicated graphics card should be considered for CAD, video content creation, high-end gaming, and 3D modeling.

Explore graphics processing unit benchmarks for 2026, led in performance by Nvidia's GeForce RTX 5090, with AMD's Radeon RX 9060 XT 8GB and Nvidia's GeForce RTX 5060 providing the best 1080p performance per dollar.

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.

Some graphics processing units advertised under different product names, such as Nvidia's RTX 5070-Ti and RTX 5080, are identically manufactured microchips with different defect counts.

Graphic processing units rely on a hierarchy of memory for optimization, where the smallest, fastest memory—registers—is located closest to the core and provides access to data in a fraction of a nanosecond.

Watch how graphics cards are fixed in a workshop by replacing faulty components, including graphics processing units and memory, located atop printed circuit boards.

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.

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.

Since 2025, AI data center growth has created shortages and price hikes in graphics processing units and their supporting hardware, including high-speed memory.

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.

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.

Jensen Huang doesn't think Nvidia was a great company on day one

"Nvidia wasn't a great company on day one. We made it great over 31 years," explained businessman Jensen Huang on a recent podcast episode. He covered other principals and lessons he learned while building Nvidia in the epsiode too.

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.

Pixar's RenderMan software, which turned code into graphics, changed the way Hollywood produced special effects.

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.

Writer William Gibson invented the term 'cyberspace'

The science-fiction writer coined the term in his 1982 short story "Burning Chrome" to describe "a consensual hallucination experienced daily by billions of legitimate operators, in every nation, by children being taught mathematical concepts...A graphic representation of data abstracted from the banks of every computer in the human system. Unthinkable complexity. Lines of light ranged in the nonspace of the mind, clusters and constellations of data. Like city lights, receding."

View a timeline of 3D printing technology through 2019

The first working 3D printing device was invented in 1983 and utilized stereolithography, a process in which a laser triggers a chemical reaction that hardens liquid resin. Powder-based laser sintering technology was patented in 1987, with metal-based powders first being used for 3D printing in 1997.

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

Google invented the foundation of the AI movement—but ChatGPT was a shock

For years, Google was the cutting-edge of the AI world, including the development of the Transformer—the basis of contemporary AI chatbots. But since OpenAI debuted ChatGPT in 2022, the company was had to play catch-up. This is a four-hour deep dive into Google's AI history.

The first 3D printing patent was filed in 1967

Wyn Swainson, an English literature graduate student, filed a patent in Denmark for a system that scans an object and uses the scanning data to rebuild it using lasers that harden light-sensitive plastic. However, he never developed a working prototype. The idea originated from wanting to produce recreations of sculptures.

The original 'four horsemen' of tech were Intel, Dell, Microsoft, and Cisco

These companies became known as the "four horsemen of tech" for the influence the companies had both on other businesses and investors in the late 1990s and early 2000s. The expansion of internet infrastructure throughout the 1990s and the dot-com bubble lifted these companies to incredible heights.

Credit for inventing the laser was fought over for nearly three decades

Although Theodore Maiman built the first working laser in 1960, Gordon Gould coined the term earlier. Charles Townes and Arthur Schawlow of Bell Labs filed a patent after Gould came up with the idea and name, but before Gould filed his patent.

View a timeline of AI deployments from 2017 to 2025

The development of transformer architecture and the release of GPTs across AI labs led to rapid changes in LLM scale and power. Companies like OpenAI, Google, Meta, Microsoft, and Anthropic have invested billions of dollars to develop reliable, versatile models.

An integrated circuit combines major circuit components onto a single device

Before 1958, these components were fabricated separately before manual assembly, introducing human error, delays, and higher costs. The invention of the IC laid the foundation for automated manufacturing, miniaturization, and improvements to speed and energy efficiency.

Y Combinator, the startup accelerator, gets its name from the 'Y combinator' computer science concept.

Coined in 1971, the man credited with naming Silicon Valley was originally writing about semiconductors

Silicon Valley gained its name from an article published in January 1971, in Electronic News. Author Don Hoefler used the term in his headline for an article he was writing about the semiconductor industry. Hoefler is credited with naming the multi-trillion dollar area that is still called Silicon Valley today.

Bill Hewlett and Dave Packard are known for creating the 'founding' Silicon Valley company Hewlett-Packard

During the company's early years, Hewlett and Packard established a management approach called "the HP Way." The approach, which was considered radical at the time, helped shape the way Silicon Valley is run today.

Lasers help build the layers of circuit components in microchips

During the photolithography process, light is projected through a blueprint onto a light-sensitive chemical layer on silicon wafers, etching patterns that become transistors through a series of successive reactions. These processes require significant electricity, as only about 2% of photons reach the wafer.

Microsoft's Flight Simulator is one of history's longest-running software products

The program originated from a master’s thesis project on generating three-dimensional graphics, which was later combined with flight equations. The first version ran on the Apple II in early 1980, but its creator licensed the program to Microsoft two years later,

The Majorana 1 chip may provide quantum computing using geometry-based qubits

Traditional quantum computers are incredibly fragile, with encoded information easily disrupted and requiring significant error correction systems. Microsoft’s approach involves storing data on a surface, which is more stable, but involves an elusive particle first theorized in 1938.

Ten defining moments at CES through the years

Iconic CES devices like the Apple Newton, CD player, VHS VCR, Sony PlayStation, and Oculus Rift “Crystal Cove” didn’t necessarily seem groundbreaking at the time. Here's a list of some defining moments from the annual show.

Tetris was launched in the US at Summer CES 1988

Tetris first appeared in the US at the 1988 Summer CES, where Henk Rogers—who would later publish and market the game—first encountered it. This interview revisits that moment, with creator Alexey Pajitnov and Rogers reflecting on how the game gained global recognition.

Quantum computers use qubits to solve problems much faster than classical machines

Unlike regular computers, where each bit is either 0 or 1, quantum computers use qubits, which can simultaneously be both—allowing for massive parallel processing power. Google’s quantum processor once solved a problem in seconds that would have taken a supercomputer 47 years.

Comparing ChatGPT with Claude, the latter excels in writing and coding projects

As of December 2025, Claude Code—Anthropic's AI-powered coding assistant—accounts for 54% of the enterprise coding market, and, while subjective, some report that Claude provides more natural-sounding writing. However, ChatGPT can create images and videos, not just generate text, and provides a broader set of applications via custom GPTs.