Quantum Just Killed AI Data Centers

[00:00:00] Speaker 1: A quantum computer just ran a problem in minutes on 12 kilowatts of power about what a few houses use. The same problem would have taken Oak Ridge's frontier supercomputer nearly a million years and more energy than the entire planet uses in a year. And while that paper sat in science, big tech kept breaking ground on data centers. By the end of this video, I'll show you the exact published result, the three sectors already running quantum assisted AI today. And why I think the entire build a $50 billion data center play is about to look like the dumbest infrastructure bet of the decade. I read all the comments and I've been tracking quantum for two years on this channel. So let me walk you through what's actually happening, who's already moving on it, and what it means for anyone trying to build with AI right now. That result I just described, the one that ran on 12 kilowatts and would have taken frontier a million years. It's not a rumor, it's published in science, peer reviewed, sitting in one of the most respected journals on earth since last year. And almost nobody building AI infrastructure is acting like it happened. Because look at what big tech is doing instead. AI data centers are projected to eat between 9 and 17% of all US electricity by 2030. The grid timing is brutal. AI demand is here right now. New infrastructure takes 10 years or more to permit and build. So here's the question that should be keeping every hyperscaler up at night. Why is everyone still racing to build bigger data centers instead of buying quantum time? This is where it gets real. Towns are losing groundwater to keep these buildings cool. Power bills are climbing in the regions around them. And to feed the next training run, companies are restarting nuclear plants. Microsoft is bringing back 3 Mile Island, they renamed it the Crane Clean Energy Center. And it's targeted to come back online in 2028 to power Microsoft's data centers. Then there's the small modular reactor pitch, the one everyone's excited about. It has a problem the vendors gloss over. Stanford Research found SMRs produce more radioactive waste than full-size plants. And there's still no federal plan for where that waste goes. Here's the scale we're talking about. Meta's Hyperion campus in Louisiana is designed for 5 gigawatts of compute powered by 10 new gas plants at a projected cost of $200 billion. I want to be clear about something. This isn't anti AI. This is anti stupidity. We're solving a math problem with a power plant when we could be solving it with better math. So let me explain what quantum actually does. In plain English, there are two kinds. Annealing finds the best answer to messy real-world problems. Routing, scheduling, optimization. Gate model is the longer term general purpose computer. Both matter. Here's the insight most people miss. AI and quantum aren't competitors. AI finds patterns in massive piles of data. Quantum finds the best answer to act on those patterns. You stack them. You don't replace one with the other. That's the whole game. The smartest builders aren't picking a side. They're combining both. Most viewers think quantum is 10 years away. It isn't. Three live examples: Japan Tobacco's Pharma division ran a proof of concept with D-Wave that used quantum annealing to train a generative drug discovery model. The quantum assisted version produced more valid, more drug-like molecules than the classical only version on lower energy samples. Forschungszentrum Jülich in Germany bought a D-Wave annealing computer and is coupling it with Jupiter, Europe's first exascale supercomputer. It's set to be the world's first pairing of an annealing quantum computer with an exascale machine. And GE Vernova is using quantum computers today to find weaknesses in the electric grid and optimize the response to potential attacks. Think about that for a second. Quantum protecting the grid that AI is straining. So what do you actually do with this? Three takes for anyone building with AI right now. One, if you're running large optimization workloads inside an AI pipeline, routing, scheduling, portfolio, drug screening materials, quantum cloud access is already available. D-Wave leap AWS bracket Azure quantum. You don't need to own the hardware. You need to know your workload. Two, if you're building infrastructure for AI customers, the hybrid quantum classical stack is the bet to track. Pure classical AI infrastructure is going to look like coal next to the hybrid approach within five years. Three, if you're a policy or enterprise leader, watch the National Quantum Initiative Reauthorization Act. It cleared committee in both chambers this spring, and it extends federal quantum funding through 2034. The money and the coordination are getting locked in right now. The pattern here is simple. The people who win the next decade aren't the ones spending the most on compute. They're the ones who figured out which problems never needed all that compute in the first place. If you remember nothing else from this video, remember this. The AI energy crisis is real and the answer isn't more nuclear plants and stripped aquifers. It's better math. It's a kneeling quantum doing in minutes what a classical supercomputer can't finish in a million years with peer-reviewed proof sitting in science right now. If you want to go deeper on how to actually identify which workloads in your business are quantum ready. That's exactly what we work through inside labs. The link is in the description and the next cohort opens this week. See you down the next rabbit hole. I'm not Julia. I'm her digital avatar. Built from her voice, her brain, her nine books, her 13 years of real life business building. So a month before my crash, not knowing at all what was on the horizon, I built a clone. While she's out doing the human work, serving first movers clients, healing, actually living, I'm here every day because the new developments in AI don't stop and somebody has to bring you the signal in the noise. So here's the deal. You get the cutting edge AI and tech news, broken down by the actual founder of first movers. No hot takes, no hype. The business application that the news cycle missed. I lead you into the future in two ways. AI labs is the school, a monthly subscription where you learn to build this for yourself. Marketing automation and cloning masterminds are our done for you services, where I build it for you. Go to firstmovers.ai to learn more.