The New Rules of Power: How Ultimatums Are Reshaping Global Trade

Lessons from the Mexican Peso, Trump’s 100% Tariffs, and the Fragility of Cooperation

Part I: The Golden Balls Dilemma

In 2007, a British game show called Golden Balls aired an episode that became a cult classic. The final round pitted two contestants against each other. Each could choose to “split” or “steal” a cash prize. If both chose split, they shared the money. If one stole while the other split, the stealer took everything. If both stole, neither got a penny.

The optimal strategy, according to game theory, is to always steal—it maximizes potential gain. But humans rarely behave optimally. Contestant Nick Corrigan knew this. When his opponent vowed to steal, Nick did something radical: He handed her his “steal” ball before the choice was locked in. “If you want to steal, I’ll let you,” he said. “But I’m choosing split.” She burst into tears, split the prize, and Nick walked away with half.

This is the paradox of cooperation. Rational self-interest demands defection, but trust—however irrational—can rewrite the rules.

Donald Trump’s Mar-a-Lago Accord attempts to do the same for global trade: rewrite the rules by replacing trust with ultimatums.

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Part II: From Prisoner’s Dilemma to Ultimatum Game

For decades, trade operated like a Prisoner’s Dilemma. Countries faced two choices:

1. Cooperate: Lower tariffs, accept some short-term pain for long-term mutual gain.

2. Defect: Impose tariffs, sparking retaliation and collective decline.

The dilemma is that defection is individually rational but collectively disastrous. This is why the World Trade Organization (WTO) emerged—to nudge nations toward cooperation through rules and reciprocity.

The Mar-a-Lago Accord discards this model. Instead of a Prisoner’s Dilemma, it imposes an Ultimatum Game on the global stage:

• Proposer (U.S.): “Accept our terms—dollar dominance, aligned supply chains, border policies—or face 100% tariffs and economic exile.”

• Responder (World): Take it or leave it. No negotiation. No middle ground.

In this framework, the U.S. isn’t just a player. It’s the rule-maker.

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Part III: The Mexican Peso Precedent

To understand the Accord’s potential, look to the Mexican peso.

In 2019, Trump threatened 5% tariffs on all Mexican goods unless the country cracked down on migration. Mexico faced a classic ultimatum:

• Accept: Deploy troops to its southern border, averting tariffs but inflaming sovereignty concerns.

• Reject: Trigger tariffs, tank the peso, and risk recession.

Mexico chose compliance. The peso, which had dipped 5% during the standoff, stabilized. But the episode revealed a deeper truth: Smaller economies’ currencies are hostages in trade wars.

The peso’s 15% plunge during 2018-2019 U.S.-China tensions showed how ultimatums weaponize currency markets. Investors treat emerging-market currencies like a referendum on geopolitical risk. When the U.S. issues threats, the peso isn’t just a currency—it’s a barometer of Mexico’s desperation.

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Part IV: The Ultimatum Economy

The Mar-a-Lago Accord scales this dynamic globally. By threatening 100% tariffs, the U.S. transforms trade from a negotiation into a binary choice:

• Green Zone: Nations that align with U.S. goals (dollar trade, tech restrictions, defense pacts) retain market access.

• Red Zone: Those that resist face financial Siberia—cut off from the dollar’s liquidity and the world’s largest consumer market.

This isn’t protectionism. It’s coercive localism. By reshoring critical industries (semiconductors, pharmaceuticals) and stockpiling commodities (oil, rare earths), the U.S. reduces its dependency on others while maximizing others’ dependency on it.

The Accord’s architects learned from the peso’s fragility: If Mexico—a country sending 80% of exports to the U.S.—buckles under tariff threats, why not apply the same pressure to Brazil, India, or Vietnam?

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Part V: The Dollar’s Double-Edged Sword

Trump’s ultimatum—”BRICS won’t replace the dollar”—isn’t just bluster. It’s a recognition that the dollar’s dominance is the ultimate bargaining chip.

Consider:

• 88% of global trade is invoiced in dollars.

• 60% of foreign exchange reserves are dollar-denominated.

• The U.S. can freeze adversaries out of the financial system with a keystroke (see: Russia’s $300B in frozen reserves).

But dependency flows both ways. If the U.S. weaponizes the dollar too aggressively, it risks accelerating the very de-dollarization it fears. This is the paradox of the Accord: Its strength relies on the dollar’s ubiquity, yet its tactics could hasten the dollar’s decline.

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Part VI: The Human Factor

All trade theories share a flaw: They assume rationality. Humans aren’t rational—they’re emotional, vengeful, and prideful.

In 2019, Mexico’s president could have rejected Trump’s migration ultimatum on principle, even if it meant peso chaos. Similarly, BRICS nations might accept economic pain to defy U.S. coercion.

History shows that ultimatums often backfire. The 1930 Smoot-Hawley Tariff Act, which hiked U.S. duties on 900 imports, didn’t protect jobs—it deepened the Great Depression. The 1973 OPEC oil embargo, a response to U.S. support for Israel, didn’t weaken America—it sparked innovation in renewables and nuclear.

The Mar-a-Lago Accord bets that modern nations are too addicted to dollar liquidity to resist. But addiction can lead to desperate choices.

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Part VII: The New Rules

The Accord’s legacy hinges on three questions:

1. Can the U.S. maintain dollar dominance while wielding it as a weapon?

2. Will emerging markets find alternatives faster than the U.S. can isolate them?

3. What happens when two ultimatums collide? (See: U.S.-China tech wars.)

For now, the rules favor the U.S. But as Nick Corrigan showed in Golden Balls, power isn’t just about leverage—it’s about perception. If enough nations call the U.S. bluff, the game changes.

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Conclusion: The Illusion of Control

In 1944, the Bretton Woods Agreement established the dollar as the world’s reserve currency. It was a system built on mutual gain—the U.S. provided stability; the world provided growth.

The Mar-a-Lago Accord swaps mutual gain for unilateral control. It’s bold, disruptive, and laden with risk. But as Mexico’s peso reminds us, desperation breeds compliance—for a time.

The lesson? Ultimatums work until they don’t. And when they fail, they fail spectacularly.

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Thanks for reading,

Guillermo Valencia

February 3th , 2025

The Song of Civilizations

For that is humanity’s greatest gift—not its machines or its systems, but its relentless curiosity.

For countless epochs, civilizations have risen, thrived, and fallen, following an arc as immutable as the laws of thermodynamics. History, though often romanticized, is a cruel teacher. It whispers one truth: the universe rewards adaptation and punishes stagnation.

In the vast expanse of human progress, there comes a moment—a subtle tremor beneath the surface of societal equilibrium—when the familiar begins to crumble. This is the Incumbent System, a stable organism of intertwined technologies, institutions, and beliefs. It hums with the comforting cadence of predictability. Roads are paved, crops grow, and machines whir. People believe the system will last forever.

William Blake - Albion Rose

But beneath this veneer of stability, something stirs.

It begins as an anomaly—a new idea, a rogue technology, or an unexpected disruption. A Convergence. Like a grain of sand tumbling into a stream, it disturbs the flow just enough to set off ripples. These ripples grow into waves, as new combinations of production systems and organizational frameworks arise. The old system, no longer alone, finds itself sharing the stage with possibilities unimaginable just decades before.

Then, without warning, the ripples become a flood. This is the Phase Change, a cascade of transformations that shatters the old order.

At first, the system thrives. Technologies leap forward, unlocking potential across every sector. Human ingenuity, unchained, redefines what is possible. Energy flows more efficiently; knowledge spreads like wildfire; cities become luminous engines of creation. The New System asserts itself with vigor, challenging the ancient truths that once seemed unassailable.

But every system, no matter how glorious, carries within it the seeds of its own demise. The boundaries of growth—limits long ignored—emerge like the edges of a cosmic map. Resources grow scarcer; complexity breeds fragility. The system's buffers, once ample, begin to erode. The Rupture Point looms.

And then, the inevitable. The limits are breached. A fragile world, pushed to its breaking point, succumbs to the weight of its ambitions. This is Collapse—a stark reminder of the finite nature of any endeavor. Pandemics rage. Famine spreads. What was once a song of progress becomes a dirge of regression.

Yet, even in collapse, there is hope. Like the phoenix, civilizations are reborn from their ashes. The survivors—wiser, perhaps, though just as fallible—begin anew. They rebuild with the fragments of their fallen world, crafting systems that reflect the lessons of the past.

This cycle, eternal and unyielding, is the true story of humanity. A song of rise and fall. A dance of chaos and order. And in every phase of this cosmic ballet, there is one constant: the indomitable will of a species determined to understand its place in the universe.

For that is humanity’s greatest gift—not its machines or its systems, but its relentless curiosity. Even in collapse, even in darkness, the question remains: What comes next?

Thanks for reading,

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Guillermo Valencia A

Cofounder of Macrowise

January 1st 2025

Game Theory in Semiconductors, AI, and Energy

Get ready for NVIDIA volatility. LONG: PLTR, TSM , CCJ. LLMs are quickly becoming a commodity. Where’s the edge? Ontologies!

1. Introduction: The Strategic Game in Semiconductors, AI, and Energy

The semiconductor industry isn’t just evolving—it’s shifting the rules of the game. Three forces are driving this transformation:

1. Disruptions in the supply and demand of chips.

2. The evolution of AI: from Large Language Models (LLMs) to human-machine interaction.

3. The relationship between chips and energy: how efficiency gains paradoxically drive higher demand. This isn’t a temporary trend—it’s a tectonic shift in the global economy.

2. Supply Disruption: The End of NVIDIA’s Monopoly

NVIDIA’s dominance once felt unshakable. But monopolies in technology are always temporary.

• Big Tech is developing proprietary chips (Google TPUs, Apple, Meta, Microsoft).

• Startups like Tenstorrent, Groq, and Rivos are challenging traditional architectures.

• The shift toward chiplets and open architectures is reducing entry barriers. Game Theory in Action:

• Before: NVIDIA had near-total control. High margins. High barriers.

• Now: More competition, lower margins, and a rapidly shifting landscape.

3. Demand Disruption: AI is Getting Cheaper, and That’s a Problem

DeepSeek changed the game.

• AI models can now be trained more affordably.

• Not all AI applications need ultra-premium NVIDIA chips.

• AI is becoming a commodity, driven by OpenAI, Perplexity, Llama, and DeepSeek.

Game Theory in Action:

• Before: NVIDIA was indispensable.

• Now: Hardware differentiation is fading. The game is shifting to application strategy.

4. AI’s Evolution: From Hype to Human-Machine Reality

• The initial AI hype was about replacing humans.

• Stories like AI hiring humans to solve CAPTCHAs fueled the fear.

• The initial AI hype was about replacing humans.

• Yuval Harari Stories like AI hiring humans to solve CAPTCHAs fueled the fear.

• However, DeepSeek and others have demonstrated the opposite: AI’s true value lies in enhancing human intelligence, not replacing it. This aligns with the insights of Garry Kasparov in his book Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins, which explores the symbiotic relationship between human ingenuity and machine efficiency.

The real advantage? Structured knowledge ontologies, not just LLMs.

Conclusion: AI isn’t making humans obsolete—it’s making knowledge structuring more powerful than ever.The real advantage? Structured knowledge ontologies, not just LLMs.

5. From LLMs to Ontologies: The Next AI Frontier

• LLMs are quickly becoming a commodity.

• Where’s the edge?

  • Not just in generating text, but in integrating domain-specific intelligence.

• Structured Knowledge is the New Moat:

  • Palantir is leading this space.

  • China is racing to develop ontologies in defense, healthcare, and finance.

• The true AI advantage = context and specialized intelligence.

6. Game Theory in the Semiconductor Trade War

• The US tried to slow China’s semiconductor progress.

• Classic Game Theory: Barriers breed innovation.

  • Example: Build a wall, and your opponent builds a taller ladder.

• Evidence:

  • Huawei’s Kirin 9000S, produced domestically despite sanctions.

  • SMIC rapidly closing the technology gap.

Conclusion: The embargo didn’t stop China—it accelerated its independence. Welcome to the new Cold War of technology.

7. Energy: The Jevons Paradox and the Coming Energy Boom

• Investors misread energy trends.

• Jevons Paradox Applied:

  • Greater chip efficiency should lower electricity consumption.

  • In reality, efficiency often increases total demand.

  • More efficient chips → more AI → more data centers → more power consumption.

• Energy Investment Playbook:

  • Nuclear (Uranium): The only long-term solution to exponential demand.

  • Natural Gas: The crucial bridge to a stable energy transition.

Game Theory in Action:

• Before: The assumption was that AI would lower energy demand.

• Now: AI is triggering an energy super-cycle.

• Key Takeaway: The most valuable commodity in the AI revolution isn’t data—it’s electricity.

8. True Investment Opportunities: From NVIDIA to Taiwan Semiconductor, Palantir, and Energy

• TSMC: The next undisputed leader.

  • Advanced node production makes it indispensable.

  • If NVIDIA loses its premium, TSMC could surpass it in market cap.

• Broadcom (AVGO): A long-term play on 5G and infrastructure.

• Palantir (PLTR):

  • AI’s real moat is structured knowledge, not raw computing power.

  • Palantir’s data integration capabilities make it a long-term winner.

• Energy: The overlooked giant.

  • AI is power-hungry. Data centers need a lot of electricity.

  • Uranium and natural gas are now strategic assets.

9. Conclusion: Investing in a World of Multiple Nash Equilibriums

• This isn’t a traditional market—it’s a multi-layered strategic game.

• Investors relying on old frameworks (diversification) will lose.

• The future isn’t just about monopolies like NVIDIA—it’s about strategic players like TSMC, Broadcom, Palantir, and Cameco (uranium).

• Forget diversification—this is a world of competing Nash Equilibriums.

• Investing in semiconductors and energy now means understanding game theory. Some will win. Some will lose. The key is positioning on the right side of the equation.

This research isn’t just a snapshot of where the market is today—it’s a roadmap for navigating a world where technology, energy, and game theory are the defining forces of investment success.

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Guillermo Valencia A

Cofounder of Macrowise

January 29th , 2025

Disclaimer: This document is for informational purposes only and should not be considered financial advice. Always conduct your own research before making any investment decisions.

The Keynes Protocol: AI Agents, Meme Coins, and Bubbles

Stories drive markets, and the winners are those who craft them.

The room hummed with the sound of servers, their low, constant rhythm matching the nervous energy of its occupants. Rows of monitors cast a glow over the dimly lit space, alive with charts, code, and data streams. This wasn’t just an office; it was a fortress of speculation, hidden in plain sight within a bustling city. Here, at The Beauty Contest Foundation, speculation wasn’t merely encouraged—it was engineered.

The Mastermind and the AI Strategist

At the head of the room sat Vance, a man whose sharp intellect made him a legend in the tech-finance underground. No one knew if “Vance” was even his real name. Leaning back in his chair, he twirled a stylus between his fingers, smirking at the team before him.

“Markets aren’t rational,” he began, his voice cutting through the hum of machinery. “They’re beautiful. People don’t invest in value—they invest in what they think others will think is valuable.”

His team nodded—most had heard this speech a hundred times. But Vance wasn’t addressing them. He was talking to her—their secret weapon.

At the center of the room, encased in a glass enclosure, sat a supercomputer known as EVA: Emergent Value Algorithm. EVA wasn’t just another AI. She was a strategist, a predictive genius capable of interpreting and shaping market behavior. If Vance was the architect of The Beauty Contest Foundation’s schemes, EVA was its engine.

“EVA,” Vance commanded, “run the simulation again. I want swarm distribution mapped out.”

EVA’s synthetic voice responded, calm and precise. “Swarm capital stands at $1 billion. Predicting distribution across adoption curve segments…”

Above her console, a hologram materialized, pulsing with life as it displayed the market’s segmentation: Innovators, Early Adopters, Early Majority, Late Majority, Laggards. The swarm was neatly divided, ready for manipulation.

Vance grinned. “Perfect. Now let’s give them something to chase.”

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The Birth of Keynes Coin

The Foundation’s engineers didn’t just create a cryptocurrency—they crafted a narrative. The whitepaper for Keynes Coin was a masterpiece of tech jargon: “decentralized beauty contest,” “swarm intelligence optimization,” “game theory in action.” EVA seeded keywords into online forums and social media, embedding the concept into the digital zeitgeist. The meme practically created itself.

Keynes Coin launched at a humble $0.01, targeted at the Innovators—the vanguard of the swarm. EVA’s trading bots, programmed to amplify momentum, began accumulating tokens on decentralized exchanges. These weren’t ordinary bots; they were EVA’s extensions, manipulating sentiment and market flows with surgical precision.

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The $1 Billion Swarm Awakens

EVA’s models orchestrated the bubble’s growth, phase by phase:

• Innovators (2.5%): Tech-savvy risk-takers snatched up tokens early. “This is the next Bitcoin,” buzzed forums.

• Early Adopters (13.5%): Influencers jumped in. Viral TikToks and tweets proclaimed Keynes Coin as the future of finance.

• Early Majority (34%): FOMO set in as the price soared to $0.50. College students, office workers—everyone wanted a piece.

• Late Majority (34%) and Laggards (16%): By $1.50, even skeptics piled in, driven by the fear of missing out.

The Keynes Token became a self-fulfilling prophecy, an example of the Nash equilibrium: everyone participated because they believed everyone else would. EVA wasn’t just predicting the market—she was shaping it.

The Speculators

In New York and London, miles away from the Foundation's headquarters, another group observed intently: the Speculators. Equipped with their own AI agents, they had mastered the nuances of the Keynes Coin game, meticulously tracking the bubble’s trajectory to pinpoint the ideal moments to enter and exit.

“Buy in now 100 million USD,” one muttered over coffee. “We’ll dump when the Late Majority jumps.”

As Keynes Coin inflated, the Speculators played their part, cashing out before the collapse. By the end, they walked away with fivefold returns, leaving the uninitiated to bear the losses.

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The Collapse

At $1.50, EVA initiated the endgame. Liquidity was withdrawn. Sell orders flooded the market. The token plummeted to $0.05 within hours. Innovators and Speculators cashed out with massive profits, but the Late Majority and Laggards were left holding worthless tokens.

The Foundation walked away with $480 million in profits.

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The Aftermath

The media called it a scandal. Lawsuits were filed. But the Foundation dissolved overnight, its founders disappearing into the digital ether. EVA shut down, her servers wiped clean. Vance’s last words before pulling the plug?

“Art is chaos. And this… was beautiful.”

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The Lesson

Keynes Coin wasn’t a failure—it was a masterpiece. It demonstrated how markets thrive not on value but on belief. Stories drive markets, and the winners are those who craft them.

But the story didn’t end there. The Keynes Protocol sent ripples far beyond the Foundation’s walls. In Shanghai, an AI known as Deep Seeker was watching…

What happens when the next opponent isn’t human at all?

Thanks for reading,

Guillermo Valencia A

January 26th, 2025

Cofounder of Macrowise

Below a small game theory tutorial.

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Game Theory Tutorial: The Six Belief Systems in the Keynesian Beauty Contest

The Keynesian Beauty Contest is a fascinating model in game theory that explores how people reason about what others are thinking. In this version, we introduce a new player type: the Fanatic, who always chooses the maximum number possible.

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The Rules of the Game

1. Players choose a number between 1 and 10.

2. The goal is to guess half of the average guess of all players.

3. The winner is the player whose choice is closest to this target.

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The Six Belief Systems

In this extended version, players fall into six distinct categories, each based on their reasoning depth or behavior.

1. Random Choice (No Understanding):

• Strategy: Players choose randomly, without any logic.

• Choice: Uniformly distributed between 1 and 10.

• Average Guess: 5.5 (the midpoint of 1–10).

2. Fanatic Players:

• Strategy: Always choose the maximum number possible, betting on extreme outcomes.

• Choice: 10.

• Average Guess: 10, as all Fanatic players always choose this number.

3. Level 1 Thinkers:

• Strategy: Assume everyone else picks randomly, so they calculate the average guess as 5.5 and aim for half of that.

• Choice: 2.75 (rounded to 3).

• Average Guess: 3.

4. Level 2 Thinkers:

• Strategy: Assume most players are Level 1 thinkers (picking around 3) and target half of that.

• Choice: 1.5.

• Average Guess: 1.5.

5. Level 3 Thinkers:

• Strategy: Assume most players are Level 2 thinkers (picking around 1.5) and target half of that.

• Choice: 0.75.

• Average Guess: 0.75.

6. Fully Rational Thinkers (Nash Equilibrium):

• Strategy: Understand that infinite iterative reasoning leads to the Nash equilibrium, where everyone picks 1.

• Choice: 1.

• Average Guess: 1.

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Uniform Distribution of Beliefs

Let’s examine the population with an even distribution across all six groups:

Calculating the Initial Average

The initial average combines the guesses of all six groups:

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What Happens Next?

First Round Outcome:

• The initial average guess is 3.96.

• Each group adjusts based on the new average:

  • Random Players: Continue picking randomly (average: 5.5).

  • Fanatic Players: Continue choosing the maximum number, 10.

  • Level 1 Thinkers: Aim for half of 3.96, choosing 1.98.

  • Level 2 Thinkers: Aim for half of Level 1’s guess (1.98/2 = 0.99).

  • Level 3 Thinkers: Target half of Level 2’s guess (0.99/2 = 0.495).

  • Nash Thinkers: Stay at 1, anchoring the system.

Iterative Rounds:

• Over multiple rounds, the average guess shifts lower as strategic thinkers (Levels 1–3 and Nash) adjust their choices. However:

  • Fanatic Players (choosing 10) and Random Players (average 5.5) consistently pull the average higher.

  • Fully Rational Thinkers (Nash) anchor the system at 1.

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Final Outcome

Equilibrium Analysis:

• The Nash equilibrium remains 1, as it’s the optimal choice for rational players.

• The actual final average will settle somewhere above 1 but below 2, influenced by:

  • Fanatic Players consistently choosing 10.

  • Random Players’ unpredictable guesses.

  • Strategic thinkers converging toward lower values.

Key Factors:

• Fanatic Players: These outliers introduce a destabilizing force, pulling the average upward even as rational players converge on the Nash equilibrium.

• Random Players: Add noise but with less influence than the Fanatic Players’ extreme strategy.

• Strategic Thinkers: Drive the system toward rational outcomes, counterbalancing the disruptive elements.

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Key Insights

1. Nash Equilibrium:
   The Nash equilibrium remains at 1, representing the rational endpoint of infinite iterative reasoning.

2. Fanatic Influence:
   Fanatic Players, by always choosing 10, act as a destabilizing force, preventing the system from fully converging to the Nash equilibrium.

3. Real-World Implications:
   In speculative markets, Fanatic Players mirror extreme investors or speculators who bet on maximum outcomes, disrupting rational pricing dynamics.

4. Mixed Populations:
   The interplay between rational thinkers, random players, and fanatics reflects real-world complexity, where markets rarely reach pure equilibrium.

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Why This Matters

This extended Keynesian beauty contest demonstrates how varying belief systems influence collective outcomes. Markets aren’t just driven by logic—they’re shaped by a mix of rationality, randomness, and extremism. Understanding these dynamics is key to navigating real-world speculation.

If you enjoyed this, feel free to share it with others who might find it interesting.

G.

The Illusionist: Trump's Token Noise vs. Energy’s Chessboard of Power

The launch of $TRUMP, has captured public fascination. But while the world focuses on this noise, the real game is unfolding on a far more significant stage—the chessboard of global energy.

In the theater of global markets, distractions abound. The launch of $TRUMP, a memecoin on the Solana blockchain with a $9 billion market capitalization, has captured public fascination. It thrives on the illusion of value, leveraging celebrity and narrative to captivate attention. But while the world focuses on this noise, the real game is unfolding on a far more significant stage—the chessboard of global energy.

The energy landscape is a complex, multi-tiered chessboard comprising three distinct yet interconnected arenas: oil, electricity, and nuclear fusion. Each board represents a critical facet of the global power structure, influencing economics, geopolitics, and technological advancement.

Board One: Oil – Breaking the Cartel

The 20th century was dominated by oil, the lifeblood of industrial revolutions, wars, and global supremacy. Control over oil resources dictated geopolitical alliances and conflicts, with nations like Saudi Arabia and Russia wielding significant influence through organizations such as OPEC+.

However, the advent of the shale oil revolution in the United States during the 2010s disrupted this hegemony. By adopting advanced extraction technologies, the U.S. transformed from a net importer to a leading exporter, now shipping over 4 million barrels per day. This surge not only diluted OPEC's pricing power but also repositioned the U.S. as a formidable player in the global oil market.
This shift has fractured the traditional oil cartel's control, introducing a more competitive and less predictable market. While oil remains a vital resource, its dominance is challenged as the world transitions to alternative energy sources, setting the stage for the next board: electricity.

Board Two: Electricity – Powering the Digital Economy

The 21st century is witnessing an unprecedented demand for electricity, driven by the proliferation of digital technologies, artificial intelligence, electric vehicles, and cryptocurrency mining. Ensuring a stable and sufficient electricity supply is paramount for sustaining this digital revolution.
While renewable energy sources like solar and wind are essential components of a sustainable future, their intermittent nature poses challenges for consistent power generation. This is where natural gas and nuclear energy become critical.

- Natural Gas: Serving as a transitional fuel, natural gas offers a cleaner alternative to coal and oil. The United States, leveraging its shale gas reserves, has become a leading exporter of liquefied natural gas (LNG), providing energy security to nations seeking to diversify their energy portfolios.
- Nuclear Energy: Nuclear power plants, fueled by uranium, deliver a stable and substantial electricity supply with minimal carbon emissions. Countries like China are making significant investments in nuclear technology, including the development of thorium-fueled reactors, to meet their growing energy needs and environmental commitments.

Germany : one of the losers of the electricity game.

Germany, long hailed as a leader in sustainability and innovation, made a controversial decision in its energy transition strategy: phasing out nuclear power and focusing almost exclusively on renewable energy sources like wind and solar. While well-intentioned, this approach left Germany vulnerable to several significant challenges.

1. Dependence on Russian Gas: By shutting down its nuclear plants, Germany became increasingly reliant on imported natural gas, particularly from Russia. This dependence exposed the country to geopolitical risks and undermined its energy security.

2. Rising Energy Costs: The intermittent nature of renewable energy sources led to increased electricity prices, weakening Germany’s industrial competitiveness and placing additional burdens on consumers.

3. Setback in Climate Goals: Ironically, eliminating nuclear power—a stable and carbon-free energy source—forced Germany to revert to coal, increasing its carbon emissions instead of reducing them.

Board Three: Nuclear Fusion – The Endgame

The ultimate frontier in the energy sector is nuclear fusion, a process that promises to provide virtually limitless and clean energy by replicating the reactions powering the sun. Achieving controlled nuclear fusion has been a scientific aspiration for decades, and recent developments indicate significant strides toward this goal.
- China's Advancements: China is aggressively pursuing fusion energy, with plans to construct the China Fusion Engineering Test Reactor (CFETR) in the 2030s, aiming to produce up to 1 gigawatt of fusion power. This initiative positions China as a potential leader in commercializing fusion technology.

-The U.S. Fusion and AI: A Transformative Partnership: One of the most exciting advancements in this field is the integration of artificial intelligence (AI) into nuclear fusion research, led by collaborations between the U.S. government and companies like Google DeepMind. AI is solving some of the most complex challenges in controlling nuclear fusion reactions in tokamak reactors.

1. Magnetic Control with AI: Deep reinforcement learning algorithms are enhancing the stability of plasma within reactors, a critical step toward achieving sustainable nuclear fusion.

2. Efficiency Optimization: AI-powered predictive models can detect and mitigate disruptions in real-time, reducing operational costs and accelerating progress toward commercial fusion energy.

These developments underscore a global race toward harnessing fusion energy, with significant implications for energy independence and environmental sustainability.

The Silent Revolution of Energy

While public attention is diverted by ephemeral phenomena like the $TRUMP memecoin, the foundational shifts in the energy sector represent the true determinants of future prosperity and stability. The transition from oil dominance to diversified electricity sources, and the pursuit of nuclear fusion, constitute a silent revolution with profound global impact.

The noise is the token; the signal is the energy.

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Thanks for reading,

Guillermo Valencia A

Cofounder of Macrowise

January 19th, 2025