From Fire to Fusion: Energy, AI, and Quantum Progress

In a world trapped by scarcity narratives we need a new philosophical framework that reflects what humans and nature actually do: continuously transform energy into ideas, progress, and intelligence.

In a world trapped by scarcity narratives — overpopulation, finite resources, impending collapse — we need a new philosophical framework that reflects what humans and nature actually do: continuously transform energy into ideas, progress, and intelligence. Civilization as a serendipity engine that turns chaos into creativity. Like Prometheus, who stole fire from the gods to gift humanity with light and possibility, we seize the primal forces of the cosmos—fire, fission, fusion—to defy limits and illuminate the unknown.

We are stardust, forged in the fiery hearts of stars that, billions of years ago, fused hydrogen into the elements of life. We are energy, as every thought, every city aglow in the night, every dollar traded in a market echoes that cosmic alchemy. Our civilization is a vast serendipity machine, gathering millions into vibrant hubs to metabolize energy—in the biological sense—and transform it into ideas, capital, and progress. The more energy we harness, the more complex our collective intelligence becomes, weaving order from chaos, abundance from possibility. From the first campfires to the promise of nuclear fusion and the quantum leap in computing, we are alchemists, driven by the thermodynamic truth that energy is neither created nor destroyed, only transformed.

Today, we stand at a crossroads. Artificial intelligence (AI) is taming fusion’s plasma, small modular reactors (SMRs) bridge our energy present, and quantum computing redefines the energy cost of computation. 

The Thermodynamic Imperative: Energy as Universal Currency

Thermodynamics reveals a universal truth: ecosystems, from coral reefs to megacities, thrive by converting energy into order. The more energy a system metabolizes, the greater its capacity for serendipity. Historical data illustrates this: in Babylon (~2000 BCE), 75 million people used 5,500 kWh per capita annually, yielding a total demand of 412.5 TWh. By 2020, 7.8 billion people, each consuming 20,920 kWh, drove demand to 163,176 TWh. Each energy leap—writing in Babylon, philosophy in Greece, industry in the 1800s, algorithms today—has unlocked new layers of civilization.

Cities are our neural reefs, where density sparks collisions of ideas. A coffee shop chat can birth a startup; a trading floor insight can redirect billions. Financial markets, chaotic yet purposeful, are serendipity engines, transforming energy—via computation, attention, and capital—into signals that shape the future. This trinity of energy, processing power, and markets fuels our creative evolution, defying scarcity narratives from Malthus to modern dystopias. Scarcity is not destiny; it is a challenge to create, met with ingenuity: crop rotation, steam engines, fracking, solar panels. The lesson is clear: more energy, more solutions, more serendipity.

Nuclear Fusion: Emulating the Stars with AI

In stellar cores, nuclear fusion powers the cosmos. Hydrogen nuclei, colliding at millions of degrees, fuse into helium, releasing energy per Einstein’s E=mc². The Sun converts 600 million tons of hydrogen per second, sustaining life. Replicating this on Earth promises clean, abundant energy from seawater-derived hydrogen, with helium as waste—no carbon, no long-lived radioactive byproducts. Yet, containing 100-million-degree plasma is a monumental challenge.

A 2024 Nature paper, “Avoiding fusion plasma tearing instability with deep reinforcement learning,” marks a breakthrough. Princeton researchers used AI to predict and prevent tearing mode instabilities in tokamak reactors, where plasma tears disrupt reactions and risk damage. Trained on DIII-D National Fusion Facility data, the AI employs deep reinforcement learning to forecast disruptions 300 milliseconds ahead, adjusting magnetic fields in real time to stabilize plasma. Unlike slow physics-based models, this AI adapts dynamically, maintaining stability in challenging scenarios.

This leap toward commercial fusion reflects your vision: processing power amplifies energy’s potential. AI acts as a digital nervous system, enabling sustained reactions. However, the study notes limitations: reliance on historical data may not generalize to future reactors like ITER, and the AI’s “black-box” nature obscures interpretability. Commercial fusion remains decades away, necessitating interim solutions.

Small Modular Reactors: A Bridge to Fusion

While fusion is a horizon technology, small modular reactors (SMRs) offer a proven bridge. These compact fission reactors, producing 50–300 megawatts versus traditional reactors’ 1,000+, split uranium-235 to release energy. Factory-built for rapid deployment, SMRs power remote grids, industrial sites, or AI data centers. Tech giants like Google (500 MW from Kairos Power’s Hermes SMRs by 2030) and Amazon (X-energy projects) are investing heavily, driven by AI’s projected 165% energy demand growth by 2030.

SMRs excel in safety (passive cooling), economics (3–5-year build times), and flexibility. AI optimizes their design—Purdue’s 2024 study achieved 99% accuracy in predicting neutron flux—mirroring AI’s role in fusion. SMRs emit no CO2 during operation, aligning with climate goals. Yet, only three exist globally, none in the U.S., and regulatory, waste, and proliferation challenges persist. Unlike fusion’s minimal waste, SMRs rely on uranium, a finite resource, and face public skepticism about nuclear safety.

While the solar narrative is losing momentum, the nuclear energy narrative is gaining traction, with companies like Oklo (OKLO), Nano Nuclear Energy (NNE), NuScale Power (SMR), Centrus Energy (LEU), and Cameco (CCJ) leading the charge.

Quantum Computing: Redefining Energy Efficiency

Quantum computing, the next frontier in processing power, promises to revolutionize energy use. Unlike classical computers, which use bits (0 or 1), quantum computers use qubits, leveraging superposition and entanglement to solve complex problems exponentially faster. Recent studies highlight their energy efficiency, critical for your trinity of energy, computing, and markets.

A 2023 Pasqal study found neutral-atom quantum computers, like their 256-qubit model, consume ~7 kW, compared to the Frontier supercomputer’s 21.1 MW—a 1,000-fold difference. Even superconducting qubit systems, like Google’s 53-qubit Sycamore, use ~26 kW. Unlike classical systems, where energy scales linearly with processors, quantum computers’ energy use grows modestly with qubits. For example, Pasqal’s 10,000-qubit projection estimates ~9.8 kW, still orders of magnitude below supercomputers.

Quantum computing’s energy advantage shines in specific tasks, like optimization or quantum simulations, where algorithms like Shor’s or Grover’s reduce computational steps. A 2024 Cornell study showed a hybrid quantum-classical framework for AI data centers cutting energy use by up to 12.5% and emissions by 9.8%. IonQ’s CEO, Peter Chapman, noted quantum processors could offload linear algebra from AI models, slashing energy needs within years.

However, challenges remain. Quantum computers require cryogenic cooling (15 millikelvin for superconducting qubits), which dominates energy costs. Error correction, needing multiple physical qubits per logical qubit, increases overhead. A 2024 ScienceDirect study found quantum computing less efficient for low-complexity problems due to cooling and control systems, urging focus on high-complexity tasks like energy system optimization. 

Quantum computing aligns with your vision by enabling energy-efficient processing, critical for markets and AI-driven innovation. It could optimize SMR operations or fusion plasma simulations, amplifying the serendipity machine.

The History of Energy: From Fire to the Cosmos

Our pursuit of fusion, SMRs, and quantum computing is the latest chapter in a saga of harnessing energy:

• Fire and Biomass (>10,000 BCE): Burning wood (~2,000 kWh/year) sparked language.

• Agriculture (Babylon, ~2000 BCE): Crops and oxen (5,500 kWh/year, 412.5 TWh) birthed cities.

• Hydraulic/Wind (Greeks/Romans, ~500 BCE–500 CE): Mills (5,500 kWh/year, 687.5–1,375 TWh) freed time for philosophy.

• Steam and Coal (1800): Engines (5,555 kWh/year, 5,555 TWh) globalized markets.

• Oil, Gas, Electricity (1900–2020): Fission and fossils (7,235–20,920 kWh/year, 11,938–163,176 TWh) digitized civilization.

• Renewables, SMRs, Fusion  (2020 Onward): Clean energy and efficient computing promise limitless progress.

Each leap has amplified our ability to create, connect, and transcend limits. SMRs power the present, AI-driven fusion beckons as the ultimate energy currency, and quantum computing redefines the energy cost of thought.

Beyond Scarcity: A Cosmic Destiny

Scarcity narratives—Malthusian fears, environmental dooms—misread our nature. We are creators, turning crises into opportunities. Fusion, if achieved, will render scarcity obsolete, powering AI, markets, and exploration. SMRs defy limits now, fueling computing and capital. Quantum computers, with their minimal energy footprint, promise to solve problems that supercomputers cannot, from energy optimization to financial modeling, without draining the grid. Critics highlight risks—SMR waste, fusion’s timeline, quantum’s cooling overhead—but these are challenges, not endpoints. Our serendipity machine thrives on solving them.

We are stardust, not bound to Earth. We are energy, transforming chaos into meaning. With AI stabilizing fusion’s plasma, SMRs lighting our cities, and quantum computers rethinking computation, we are cosmic alchemists. Each reactor, algorithm, and market trade brings us closer to the stars that birthed us. Our civilization is not just a machine; it is a bridge to the cosmos, where our destiny awaits.

We Are Stardust, We Are Energy, our Civilization as a Serendipity Engine!

Thanks for reading, 

Guillermo Valencia A 

Co-founder MacroWise