GoKawiilHowHow does AI make you feel? Are you excited to “vibe-code” your smart home? Or anxious about all the added pollution and billions of gallons of water used by data centers? Dig a little deeper and you’ll start to question the actual value of the GPUs that underpin all the leaps and promises of generative AI.
Sidebar by Sean Hollister GPU stands for graphics processing unit, and it originally had nothing to do with AI at all. GPUs were designed to be a companion to a computer's CPU — or central processing unit — to offload the hard work of rendering computer graphics. While all sorts of graphics accelerators predated “GPU” as a marketing term, modern GPUs excelled because they could process multiple graphical tasks in parallel across their multiple graphics pipelines. Roughly 20 years ago, Nvidia began to help programmers run non-graphical computing on those parallel computers too. GPUs eventually got hundreds, then thousands, and now tens of thousands of cores for massively parallel general purpose “GPGPU” computing, which sped up training of neural networks, image recognition, and now modern AI training and inference.
Right now, GPUs, hundreds of thousands of them, are being crammed into data centers around the world to power the AI boom. These chips are also found in everything from smartphones to cars to gaming PCs. Nvidia — once a niche chipmaker that has become the world’s most valuable company — still brags about releasing what it calls “the world’s first GPU” and a “gaming breakthrough” in 1999, although some trace the origins of the GPU back to at least the ’70s with graphics hardware used in arcade games.
“There are massive hardware developments that start because of games,” says Catherine Flick, a professor of ethics and games technology at University of Staffordshire. And whether it’s a testbed for new graphics processing units or the development of virtual reality and AI, “all these sorts of things that have quite significant ethical issues, a lot of these start with games,” Flick says. So since its inception, the GPU has been at the root of some of the biggest ethical questions new technologies pose. What impact do games, and now AI chatbots, have on how we interact with the world around us?
Whether mining for raw materials or exposing workers to toxic chemicals in semiconductor factories, GPU manufacturing can leave behind a big mess. Collectively, GPUs warehoused in data centers burn through an enormous amount of water and energy, which can lead to more air pollution and greenhouse gas emissions causing climate change. And at the end of its life, a GPU can do even more damage in the form of e-waste.
What’s worth taking those risks? Do potential AI-driven advances in weather forecasting or wildlife conservation justify the environmental footprint of a data center? And what about the GPUs in a gaming PC or iPhone — do they deserve just as much scrutiny?
Nvidia quarterly revenue by market, fiscal years 2018–2026, in billions Source: investor.nvidia.com Line chart of Nvidia quarterly revenue by market, fiscal years 2018–2026, in billions of dollars. $ 20 B $ 40 B $ 60 B ’18 ’19 ’20 ’21 ’22 ’23 ’24 ’25 ’26 Data centers
Gaming, professional visualization, automotive and robotics, original equipment manufacturing, and intellectual property Nvidia quarterly revenue by market, fiscal years 2018–2026, in billions Year Data centers Other markets 2018 0.606 2.305 2019 0.679 1.526 2020 0.968 2.137 2021 1.903 3.1 2022 3.263 4.38 2023 3.616 2.435 2024 18.404 3.699 2025 35.58 3.751 2026 62.314 5.813
Hitting close to home
WhileWhile GPUs have been around for a long time, AI has thrust them into the spotlight in a way that, quite literally, hits close to home for many Americans. The US has far more data centers than any other country and has plans to build many more. As tech companies race to expand a new generation of hyperscale data centers for AI, communities are grappling with the prospect of having these hulking warehouses full of servers as their neighbors.
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