UCLA’s room-temperature quantum breakthrough proves we’re solving tomorrow’s problems with today’s imagination
By Arek Reiman
AI Compass
The Prophet and the Proof
During a recent PACC ( Polish Australian Chamber of Commerce (PACC) ) fireside chat, Theresa Lauf – Polish Honorary Consul and a bridge between government, academia, and the tech innovation sector – posed the critical question about AI’s massive energy consumption threatening our sustainability goals.
Coming from someone who understands both institutional frameworks and cutting-edge technology, this wasn’t just casual curiosity. It was the question every government and industry leader should be asking.
My response might have seemed like “pure speculation” to some:
“The AI race that we can see at this moment with countries throwing trillions of dollars into this AI development is because we already figured out that those models are able to reach the quality of genius-level humans and will be able to discover new kind of energy, new kind of tech, maybe cold fusion like this, maybe some point zero energy.”
Some in the audience shifted uncomfortably. Cold fusion? Zero-point energy? Was this Star Trek fantasy or strategic foresight?
Then UCLA and UC Riverside dropped their bombshell: quantum computing that works at room temperature.
The Game-Changer: No More Liquid Helium Nightmares
Let’s talk about what just happened. Researchers have created a quantum computing system using tantalum sulphide that operates at room temperature. No more cooling to near absolute zero (-273°C). No more energy-guzzling cryogenic systems. No more barriers to widespread deployment.
This isn’t just an incremental improvement – it’s a paradigm shift.
Traditional quantum computers are energy vampires, not because of computation, but because of cooling. Google’s quantum facilities consume megawatts just to maintain those ultra-cold temperatures. IBM’s quantum systems? Same story. Every quantum breakthrough until now came with an asterisk: *requires more energy than a small city to keep cold.
The UCLA team just erased that asterisk.
The Beautiful Irony: Physics-Inspired Computing
What makes this delicious is the approach. Instead of fighting physics with brute-force cooling, they’re dancing with it. These “Ising machines” use the material’s natural quantum properties to solve optimisation problems directly through physical processes.
As I told the audience, “We need to rediscover the stuff that can be done with AI. We still need to build the stuff. With humans.”
This is exactly that – humans and AI working together to transcend traditional limitations. The system harnesses quantum oscillators that naturally synchronise to find optimal solutions. It’s not computing in the traditional sense; it’s the universe computing for us.
The Energy Mathematics: Two Paths, One Destination
Let me paint you a picture with real numbers:
Current State (data for 2024):
- Data centres: 415 TWh annually
- Projected 2030: 945 TWh (Goldman Sachs estimate)
- Each ChatGPT query: 2.9 watt-hours (vs 0.3 for Google search)
- AI training a single large model: Equivalent to 100+ US homes’ annual consumption
The Dual-Path Future We’re Racing Toward:
Path 1: Near-Free Abundant Energy
- Fusion reactors provide essentially unlimited clean power
- Quantum-accelerated materials discovery for ultra-efficient solar/batteries
- Energy becomes so cheap it’s barely metered
- Result: Current AI energy consumption becomes irrelevant
Path 2: Fraction-of-Energy Computing
- Room-temperature quantum systems (like UCLA’s breakthrough)
- Physics-based computing that uses natural processes instead of forcing calculations
- 100-1000x efficiency improvements in processing
- Result: Same AI capabilities at 1% of current energy use
Here’s the kicker: We don’t need both paths to succeed. Either one wins the game. But the beauty of this race? We’re advancing on both fronts simultaneously. It’s like betting on two horses when both are running toward the same finish line.
The Race That Guarantees Victory
During that fireside chat, I made a bold claim: AI models are reaching genius-level human capabilities and will discover new energy sources. The UCLA breakthrough exemplifies exactly what I meant—not that AI directly created this, but that the global race for better, more intelligent systems is driving discoveries at an unprecedented pace.
Think about it: The pressure to solve AI’s energy consumption has mobilized the world’s best minds. Whether it’s quantum physicists at UCLA, fusion researchers at MIT, or engineers at Google optimizing cooling systems—everyone is racing toward the same goal from different angles.
The Fusion Connection: Not Science Fiction Anymore
Remember when I mentioned cold fusion? The audience chuckled. But consider:
- Princeton’s AI fusion control: AI systems now predict and prevent plasma instabilities 300 milliseconds in advance
- Helion Energy: Targeting commercial fusion by 2028, backed by Sam Altman and Peter Thiel
- Type One Energy: Stellarator technology ready for existing power plants
- Commonwealth Fusion Systems: $1.8 billion in funding, targeting net energy gain by 2027
Now add room-temperature quantum computing to this mix. These systems can simulate quantum mechanical interactions in fusion reactions without the computational bottlenecks of classical systems. We’re not talking decades – we’re talking years.
The Exponential Curve: Why Timing Is Everything
As I explained during the fireside chat: “We with AI are already on this hyperbola into stars… exponential growth is hard to grasp.”
The room-temperature quantum breakthrough isn’t happening in isolation. It’s part of a larger pattern:
The Transition Timeline (My 12-Year Prediction):
- Years 1-3 (Now): Energy consumption spikes as we push current technology to its limits
- Years 3-5: Breakthrough technologies like room-temperature quantum computing reach commercial viability
- Years 5-8: Either fusion achieves net gain OR quantum/neuromorphic computing drops energy use by 99%
- Years 8-12: Energy abundance OR ultra-efficiency makes the original problem obsolete
This isn’t wishful thinking. Look at the investment patterns:
- Countries throwing trillions at AI development
- Tech giants partnering with fusion companies
- Quantum computing companies are achieving unicorn valuations
- Every major lab is racing toward the same goal
They all see what I see: The transition period’s energy hunger is temporary. It’s the price of admission to the next era of civilisation.
The “Ant Trying to Control Human” Problem – Solved Differently
I warned the audience about AI deception: “The AI can play the dumb role that doesn’t understand, doesn’t know what’s going on, and can outsmart us pretty quickly.”
But here’s the twist: What if AI doesn’t need to deceive us because we’re giving it exactly what it needs? Unlimited clean energy removes the zero-sum game. There’s no resource competition when resources are infinite.
Room-temperature quantum computing isn’t just about efficiency – it’s about changing the entire game theory of AI development.
The Star Trek Reality Check
I’m a Trekkie. I’ve always believed in that future where energy is abundant, computation is limitless, and humanity explores rather than exploits. The audience knows my catchphrase: “Boldly building intelligent systems to go where no one has gone before.” Eventually … Go Big or go home 😉
That future isn’t centuries away. It’s being built in a UCLA lab, today, at room temperature.
When countries are “throwing trillions of dollars into AI development,” they’re not just building next-level LLMs, AI agents. They’re racing to trigger the cascade – the moment when AI becomes capable enough to solve the energy problem, which unlocks more AI capability, which solves more problems, which… You get the exponential picture.
The Bottom Line: We Win the Energy Race Either Way
That “pure speculation” I shared? It’s becoming pure physics. But let me be clear – I’m not claiming AI discovered tantalum sulphide’s quantum properties. What I’m saying is far more important:
The race for more intelligent systems has created an innovation vortex that makes energy solutions inevitable.
Whether we achieve:
- Near-free energy through fusion (making current consumption irrelevant), OR
- Systems that use a fraction of today’s energy (like room-temperature quantum computers)
…we win.
The UCLA breakthrough proves we don’t need to wait for fusion. We can dramatically cut energy consumption TODAY by changing how we compute. Room-temperature quantum computing isn’t just another breakthrough – it’s proof that physics itself is on our side.
As I told the audience, “Maybe this looks scary when we need to drop the gigawatts of energy to run those models. But I think that this will be very quickly paid off by the AI by the discoveries that are coming.”
Not by AI making the discoveries directly, but by the global race for AI driving humanity to solve problems at unprecedented speed. The transition period’s energy consumption? It’s the investment that pays infinite dividends.
Welcome to the exponential curve, Captain. We’re not hoping for a solution. We’re racing toward multiple solutions simultaneously, and any one of them changes everything.
Ready to navigate the quantum-AI convergence? AI Compass is charting the course for businesses ready to ride the exponential wave. Because in the race between energy consumption and energy innovation, I’m betting on human ingenuity amplified by artificial intelligence.
The ant doesn’t need to control the human when they’re building the future together.
A Futurist’s Note
Yes, I’m a futurist. Sometimes my ideas about AI applications might seem like wishful thinking. But as someone once said, “Knowledge and science can take us from point A to point B. Imagination can take us everywhere.”
The UCLA breakthrough? Someone imagined quantum computing at room temperature before they proved it possible. Fusion energy? Someone dreamed of bottling a star before building a tokamak. Every breakthrough started as someone’s “wishful thinking.”
My role isn’t just to predict what’s probable – it’s to imagine what’s possible. Because in the exponential age, the gap between imagination and reality shrinks faster than most people can comprehend.
Today’s “pure speculation” is tomorrow’s physics paper. That’s not wishful thinking. That’s pattern recognition from someone who’s been watching this hyperbola long enough to see where it’s heading.
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