How energy powers your AI work and fun: a step-by-step guide

AI feels like magic — largely because most of us don't understand how it really works.Why it matters: This story will radically break down the process so this technology — which is becoming as commonplace as the Internet — feels more real and less magical."My advice for you is to start from something that you have created with AI and walk backwards of how it works," Remi Raphael, the first-ever chief AI officer of the nonprofit Electric Power Research Institute, told me. "Bits and bites. Electrons to microchips."Let's begin at the end: Whether it's a memo for your boss or a meme of your cat, it's all produced the same way. Let's focus on a cat image, because that's more fun.This — radically simplified — breakdown comes from my interview with Raphael and several others in the AI and energy nexus since I started.Step 8 (end goal): My giant Seattle cat image. I use an AI tool — like ChatGPT or Gemini — to write a prompt for an image of my cat made giant stretching next to Seattle's Space Needle.The platform delivers it to me, even though all the heavy lifting happens in a data center far away — just like the regular ol' Internet.Step 7: The hardware doing the work. Inside a data center, the image I requested is crunched by powerful chips called GPUs (graphics processing units). These GPUs live in rows of computers that AI companies use — sometimes ones they buy, but often ones they rent from cloud giants like Amazon, Google and Microsoft.All this computing creates a lot of heat, so data centers need massive cooling systems, which use a lot of electricity. And the computers themselves draw huge amounts of power. (More on that in a moment.)We're taking a small shortcut here, because not all computing is created equal. Generating that cat image actually involves two kinds of computation inside data centers:Training the model, which happens long before you ever ask for an image and requires far more energy.Responding to your request — a phase known as "inference," which is what happens when you actually generate the cat image.Step 6: The hardware behind the hardware. The companies running these AI systems rely on GPUs built mainly by one company: Nvidia, which dominates the market.A GPU is a type of microchip — often just called a "chip" — designed to handle huge numbers of small calculations at once, which is exactly what AI needs.Step 5: Software foundation. Those GPUs sit inside cloud infrastructure that large tech companies own and operate.These companies provide the software that lets AI systems actually run on all that hardware.Step 4: Energy management. Because millions of people are using AI, data centers need huge amounts of electricity. (Indeed, as we've written about a lot: Global electricity demand from AI-optimized data centers is projected to more than quadruple by 2030.)Companies like startup EmeraldAI and longtime players like Schneider Electric work to make that energy use as efficient as possible — from smarter cooling systems to software that helps data centers avoid wasting power.Step 3: Physical foundation. This is the world of companies that build and operate the data centers themselves.That includes standalone operators including Crusoe, which grew out of the energy sector, as well as Vantage Data Centers and Digital Realty, that host equipment for many different customers.Step 2: Grid connections. This is where the data center from Step 3 connects to the electric grid.Key players here range from grid operators to utilities to firms acting as middlemen, like Cloverleaf Infrastructure, which help data center builders secure two scarce resources: land and power.Step 1: Energy generation. This is the original energy source — a wind farm, nuclear power or natural gas plant that either indirectly powers data centers via the grid or (increasingly common) is directly connected to the data center.No matter how clean or dirty the power source is, the electrons themselves are the same — but the source determines the emissions profile and other features (like if it needs backup power or if it's stable).The bottom line: AI's "magic" is actually a giant stack of energy, hardware and software working together so your computer can turn a few typed words into a giant cat sightseeing in Seattle. What's next: Behold: the image itself! Image: AI-generated by ChatGPT