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

Moore's Law came from observing exponential computing growth in the 1960s

In 1965, Gordon Moore, cofounder of Intel Corporation, observed a four-year trend of constant growth rate in computing power. Hypothesizing the trend would continue, his observation became the benchmark that the computing industry has worked to maintain for 60 years.

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.

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 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 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.

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

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 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.

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.

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.

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.

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.

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.

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.

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’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.

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.

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.

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 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 founder Jensen Huang would not do it again

Huang was asked in 2023 whether he would do it all over again if he was transported back 30 years before. Huang said no, arguing he would not have knowingly put himself through the suffering and difficulties it took to build Nvidia, calling this ignorance to future pain one of his superpowers.

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.

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

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.

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.

Grace Hopper warned against prioritizing hardware purchases in future computing

Foreseeing the rising volume of data and the increasing demand for its processing and access, she advocated that organizations first map the total flow of information they require and then choose infrastructure to support it, rather than wastefully spending on the fastest computing technology and forcing software to compensate for unnecessary hardware or incorrect data.

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.

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.

Electrical grids worldwide must double their power delivery capacity by 2050 to meet surging demand from AI and electric vehicles.

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.

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.

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.

A video compares two visions for the metaverse: one from Nvidia and one from Facebook

The CEOs of top technology companies Nvidia and Meta recently revealed their visions for the metaverse of the future. As of 2021, both Jensen Huang and Mark Zuckerberg were bullish on virtual world-building, although Huang seemed more focused on the metaverse's business implications than its social ones, which Zuckerberg prioritized.

Hear what Michael Burry thinks about the possibility of an AI bubble

Since his success shorting subprime mortgage-backed securities in 2008, Burry's positions have often become influential, sparking conversations on platforms like X. In 2025, Burry drew attention for betting against Nvidia and Palantir for being overvalued companies.

Modular data centers can be transported on a truck for rapid deployment

Bypassing the complications involved in building larger facilities over the course of several years, such as construction costs and permits, these pre-fabricated, self-contained pods, roughly the size of shipping containers, can carry thousands of graphics processing units for small- and medium-scale AI-related tasks.

AI investment may be the next major economic bubble

A video examines the massive surge in AI spending—forecast to hit $500B by 2026—and how this may be propping up a fragile US economy. Experts warn that if AI investment slows or under-delivers, the consequences could be felt in markets, jobs and growth.

Scientists increasingly can't predict what AI will do

Most AI systems are so-called "black box" models, where we only see inputs and outputs while the inner workings remain obscure. This piece, written prior to the launch of ChatGPT, cautions developers to know why and how a system produces its results, and not to sacrifice explainability for accuracy.

How 5G will transform media and gaming experiences

The latest generation of cellular mobile communication, known as 5G, promises speeds up to 100 times faster than 4G. Intel's Asha Keddy talk to MarketWatch about how this will transform media consumption and gaming experiences.

CNET previews CES 2026

This CNET preview outlines what’s coming at CES 2026—from major showcases by Samsung, Sony, LG, and Lenovo to expected trends in AI, chips, digital health, mobility, and robotics.

OpenAI CEO Sam Altman has called OpenAI 'the most capital-intensive startup in history'

As of 2024, Silicon Valley was set to spend $1T in the coming years building AI. As companies, including Google and Microsoft, fling billions at AI dreams, concerns are rising about whether that money will ever be recouped. To learn about the argument that there is an AI bubble—and that it could soon burst if AI doesn't prove its worth—read this article.

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.

Google’s CEO has warned that today’s AI boom shows ‘elements of irrationality’

An interview with Alphabet CEO Sundar Pichai warns that the trillion-dollar surge in AI valuations may contain clear signs of irrationality, echoing past tech bubbles. He says no firm—including Google—would be immune if the boom cools or bursts.

Transistors in traditional computers are physically limited to atomic scales

As computer parts shrink, transistors—tiny switches that control the path of electrical signals—become obsolete because electrons can quantum tunnel through switch barriers. This makes quantum computers, which take advantage of quantum effects, an enticing alternative.

See a web of circular investments among major AI industry players like Nvidia and OpenAI, as many top AI companies provide significant investments to one another.

Noise and instability made quantum computing seem out of reach for decades

Recent advances in error suppression, mitigation, and correction are allowing quantum computers to perform practical tasks that challenge classical machines. IBM’s 2016 launch of its first cloud-accessible quantum computer attracted over 22,000 users in its first month alone.

The virtual reality era has finally arrived

The smartphone era has driven a large share of the consumer electronics market for almost 20 years now. But what comes next? Dominant computing platforms come and go over time, and there’s reason to believe that mixed reality devices like headsets and glasses might be the form factor that eventually replaces smartphones. This article presents a snapshot of where we are right now in the VR era, and what the future holds.

Data center companies are worsening housing undersupply in some regional markets.

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.

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.