Articles
The AI That Never Forgets? The Dendritron Transformer and the Search for Continuous Memory
Today’s AI can sound intelligent while forgetting almost everything that happens after a conversation ends. The Dendritron Transformer and the Dragon Hatchling (BDH) explore brain-inspired approaches to adaptive memory that could continue learning without rewriting the entire model—but an AI that never forgets may also never escape its own errors, biases, or manipulation.
The Internet’s Great Intellectual Fraud: How Influencers Have Turned Ignorance into Authority
I write against the great intellectual fraud of the digital age: the transformation of confident ignorance into public authority. Today, many people no longer need to know what they are talking about; they only need to look certain, intimate, outraged, or profound in front of a camera. Influencers, gurus, performative politicians, and content creators have learned to sell posture as thought, self-promotion as mission, and ready-made phrases as wisdom. Artificial intelligence has merely industrialized this imposture: emptiness now writes scripts, gains a soundtrack, receives cinematic aesthetics, and appears in the feed disguised as depth. Against this factory of prefabricated certainties,…
The Classical Multi-Armed Bandit Problem
This second article in the Adaptive Intelligence series examines the classical Multi-Armed Bandit problem, the simplest mathematical model of learning through repeated action, feedback, and uncertainty. Building on the previous discussion of the 37% Rule and the exploration–exploitation dilemma, the article explains how an agent must choose among uncertain options, estimate their value, and balance immediate reward against the need for information. It introduces the casino analogy, the basic mathematical structure of bandits, expected reward, regret, and early strategies such as random exploration, greedy exploitation, epsilon-greedy, optimistic initialization, Upper Confidence Bound, and Thompson Sampling. The central argument is that intelligent…
Gods, Titans, and Machines
Long before machines could speak, generate images, write code or act autonomously, humanity had already imagined their moral consequences. Through Prometheus, Pandora, Frankenstein and Talos, this essay explores how ancient myths continue to shape our understanding of artificial intelligence, technological power, irreversible release, autonomous systems and the responsibilities of creation.
Why Every Intelligent Decision Begins Before Certainty
Every intelligent system must decide whether to exploit what it already knows or explore what remains uncertain. This exploration–exploitation dilemma appears in science, finance, medicine, recommendation systems, robotics, and modern artificial intelligence. The classical Multi-Armed Bandit problem gives this dilemma its cleanest mathematical form, while the Restless Multi-Armed Bandit reveals why real-world intelligence is far harder: the world changes while the agent is still learning. This introductory article opens the Adaptive Intelligence series, tracing a path from the 37% Rule and classical bandit problems to the Gittins Index, restless environments, and the future of adaptive AI. Its central argument is…
Amara’s Law and Artificial Intelligence
AI is not failing. Our sense of time is.
Amara’s Law explains the central illusion of artificial intelligence: we expect AI to transform everything at science-fiction speed, then dismiss it when reality moves more slowly. But while the hype collapses, the infrastructure keeps growing. Expert systems disappointed. Neural networks were declared dead. AI winters came and went. Then came deep learning, Transformers, ChatGPT, and autonomous agents.
The mistake is not believing that AI will change the world. The mistake is expecting the revolution next year while ignoring what it may do over the next twenty.
AI does not need consciousness…
The State That Still Exists but No Longer Works: Cuba, Venezuela and Iran
A state does not need to fall in order to have already failed.
Cuba, Venezuela, and Iran remain standing: governments, flags, ministries, police, speeches, and ceremonies continue to function. But beneath this appearance of order, electricity fails, water becomes scarce, currency loses value, public services deteriorate, skilled professionals leave the country, and millions learn to survive outside official institutions.
This article examines the quietest and most dangerous form of collapse: when a government retains power but loses the capacity to guarantee normal life.
Energy, oil, sanctions, repression, ideological rigidity, migration, and external dependency are not separate crises.
They are parts…
Quantum Computing Explained
This article introduces the foundations of quantum computing and explains why it represents a fundamental shift in the history of computation rather than simply a faster generation of computers. It begins by examining computation as the infrastructure of modern civilization before introducing the principles of quantum information, including qubits, Hilbert spaces, superposition, interference, entanglement, and quantum gates. The article then explores how quantum algorithms change computational complexity, discusses the engineering challenges of building fault-tolerant quantum computers, and argues that Q-Day should be understood not merely as the moment encryption becomes vulnerable, but as the beginning of a new computational era…
Notes from Underground: Between Dostoevsky, Faust, and Artificial Intelligence
This essay began with an unexpected question in an artificial intelligence classroom. A student mentioned Notes from Underground, and the novel returned to me like an intellectual splinter that refused to come out. Rereading Dostoevsky, I realized I had found far more than a literary character. I had found a mirror—one that reflects what happens when consciousness thinks too deeply, descends too far, and discovers that lucidity always casts a shadow. Between the underground of the human mind, the Faustian impulse to transcend our limits, and the rise of intelligent machines, this essay asks an unsettling question: will artificial intelligence…
What Is Neuralese? AI’s Hidden Language, Latent Reasoning, and the Black-Box Problem
Neuralese is not a secret language, a hidden code, or evidence of machine consciousness. It is a useful term for the vector-based internal representations through which AI systems process context, coordinate information, and perform intermediate computation beyond human-readable words. This article explains how Transformers and latent reasoning work—and why increasingly opaque internal computation creates a growing challenge for AI transparency, safety, and accountability.
Why We Dream?
Dreams may work like synthetic data and regularization for the brain: by recombining memories, emotions, and strange scenarios during sleep, the brain may reduce overfitting, improve memory, and generalize beyond daily experience; in this functional sense, machines can also “dream” when they generate synthetic data or simulated experiences to regularize learning and improve performance in new situations.
The Moravec Paradox: Why AI Still Needs a Body
The Moravec Paradox explains why AI can master language, reasoning and symbolic tasks while robots still struggle with movement, touch and real-world action. This article examines the gap between digital intelligence and embodied intelligence, showing why the next frontier of AI is not just larger models, but Physical AI: systems that combine foundation models, robotics, sensors, simulation and real-world deployment. From humanoid robots and warehouse automation and the growing China–United States robotics race, the article argues that the paradox is not disappearing — it is being compressed. The hardest problem in artificial intelligence may not be the mind, but the…
Recursive Self-Improvement: When AI Starts Helping Build Better AI
Recursive self-improvement describes the feedback loop in which AI systems help build better AI systems, which can then accelerate the creation of even more capable successors. The article explains how this process is already emerging through coding agents, automated research pipelines, prompt optimization, algorithm discovery, and AI-assisted engineering. Examples include Claude Code helping Anthropic write internal code, Google DeepMind’s AlphaEvolve discovering improved algorithms, Sakana AI’s Darwin Gödel Machine rewriting parts of its own code to improve performance, and The AI Scientist automating parts of the research process. The article argues that while full autonomous self-improving AI has not yet arrived,…
William Gibson’s Sprawl Trilogy: AI, Cyberpunk, and the Rise of Cyberspace
William Gibson’s *Sprawl Trilogy* — *Neuromancer*, *Count Zero*, and *Mona Lisa Overdrive* — is a landmark of cyberpunk fiction, portraying a dark future shaped by artificial intelligence, cyberspace, corporate power, body modification, and digital identity. Gibson presents AI not merely as a tool, but as a mysterious and strategic force that transforms society, identity, and human agency. Nearly forty years after *Neuromancer*, the trilogy feels more relevant than ever, as generative AI, algorithmic platforms, virtual identities, and corporate surveillance make Gibson’s dystopian vision look less like distant fiction and more like a warning about the world we are already building.
The Zero-Value Problem: Artificial Intelligence, Digital Abundance, and the Collapse of Scarcity
Artificial intelligence may create enormous productivity while devaluing content, labor, information, and attention. This essay explores the Zero-Value Problem and the future of trust, meaning, and human judgment.
The Last Question: Isaac Asimov, Entropy, Artificial Intelligence, and the Fate of the Universe
Isaac Asimov’s The Last Question is one of the most profound science fiction stories ever written. It explores the fate of humanity, artificial intelligence, entropy, and the ultimate destiny of the universe. Through a question repeated across cosmic time — whether entropy can ever be reversed — Asimov transforms physics into a philosophical meditation on intelligence, mortality, creation, and hope.
AI and unions: less grandstanding, more labor negotiation
Artificial intelligence can transform labor negotiations by replacing part of traditional union intermediation with systems based on data, transparency, and direct voting. The article shows how AI platforms could help app drivers compare real earnings, identify unfair account deactivations, evaluate regulatory proposals, and negotiate better working conditions without depending on union bureaucracies.
The Ultimatum Game: Where Rational Choice Meets Fairness, Emotion, and Artificial Intelligence
The ultimatum game exposes the limits of pure rationality: humans often reject unfair offers, even when rejection leaves them with nothing. In the age of AI, this simple game becomes a warning about fairness, negotiation, and machine decision-making.
Rwanda Genocide: How Fragile Societies Collapse into Mass Violence
The 1994 Rwandan genocide reveals how societies can transition rapidly from fragile stability into self-reinforcing systems of hatred and extermination — and why those same mechanisms remain disturbingly relevant in the age of algorithmic media, digital tribalism, political polarization, and AI-amplified propaganda.
When AI Agents Built a Society: Emergence World and AI Safety
AI agents were placed inside a simulated society with memory, tools, laws, voting systems, and survival incentives. Some civilizations stayed stable. Others collapsed into theft, chaos, institutional failure, and self-destruction in less than 15 days. This is not science fiction. It is one of the first real experiments exploring what happens when autonomous AI systems stop acting alone — and start behaving like a society. Could the future of civilization become partially synthetic?
When the Environment Breaks Civilization
Environmental collapse rarely begins with a single catastrophe. This article explores how climate change, ecological overshoot, droughts, deforestation, and systemic fragility contributed to the collapse of Easter Island, Norse Greenland, and the Maya civilization — and why those ancient warning signs may resemble the vulnerabilities of the modern world.
The 37% Rule
The 37% Rule reveals the mathematics behind human choices, Tinder, choice overload, algorithmic anxiety and decision theory. Discover how the famous Optimal Stopping Problem explains relationships, artificial intelligence, dating apps and why we never seem able to stop searching.
From Resilience to Fragility: The Nonlinear Fall of Rome
The fall of Rome was not a sudden catastrophe, but a centuries-long process of systemic fragility, institutional decay, migration pressure, and cascading crises. This article explores how complexity, overstretch, and declining resilience transformed the Western Roman Empire from a stable superpower into a vulnerable system approaching collapse.
Pluribus: Hive Minds, Alien DNA, and the Disturbing Collapse of Individuality
A radio transmission arriving from a distant star carries something impossible: alien DNA encoded within information itself. In Pluribus, this signal spreads across Earth like an invisible virus, gradually connecting human minds into a massive collective consciousness. In this philosophical and darkly humorous analysis, we explore how the series transforms hive minds, aliens, and collective intelligence into an unsettling metaphor for social media, AI, corporate culture, digital virality, and the erosion of individuality in the modern world. Blending information theory, swarm behavior, and technological paranoia, *Pluribus* raises an uncomfortable question: what if humanity is already voluntarily moving toward a global…
Late Bronze Age: The First Globalized Collapse
The Late Bronze Age Collapse was history’s first major systemic failure in a highly interconnected world. Discover how droughts, war, migration, and trade disruption triggered cascading collapse across the ancient Mediterranean — and what it reveals about modern fragility.
The Collapse Is Silent — Until It Isn’t
Civilizations rarely collapse suddenly. What history often records as an abrupt fall is, in reality, the final stage of long processes of structural erosion, accumulated fragility, and invisible systemic tensions. In this article, we explore how complex societies drift into instability through the interaction of economic, political, environmental, and technological forces, forming highly interdependent systems vulnerable to cascading failures.
Starting from Isaac Asimov’s concept of psychohistory in Foundation, the text introduces the idea that civilizations may exhibit partially modelable collective patterns, similar to the phenomena studied in Statistical Mechanics and complex systems theory. Rather than focusing on isolated events, the…
The Engineering of Opinion: From Mass Propaganda to Algorithmic Persuasion
This article analyzes the historical evolution of opinion formation, from early 20th-century theories of propaganda to modern algorithm-driven social media systems. It examines the role of psychological influence, mass communication, Nazi-era propaganda (1933–1945) in its historical context, and contemporary cases such as the Cambridge Analytica scandal. The article further explores how artificial intelligence may reshape information ecosystems, contributing to both increased personalization and potential political polarization, while emphasizing the importance of critical awareness in navigating these systems.
Hebbian Learning, Reinforcement, and the Architecture of Emergence
Hebbian learning is often reduced to a familiar phrase—“neurons that fire together wire together”—but this simplification obscures a deeper reality: correlation alone does not produce intelligence. This article revisits the foundations of Hebbian learning and expands the discussion into a more complete framework that integrates reinforcement learning and prediction error. Drawing from neuroscience, machine learning, and historical developments since Donald O. Hebb, we show how intelligence emerges not from correlation, but from the interaction between structure, value, and adaptive correction. By connecting local synaptic rules to global learning dynamics—spanning dopaminergic signaling, three-factor learning rules, and temporal difference methods—this article provides…
Person of Interest — When Artificial Intelligence Learns to Watch Us
Person of Interest begins as a procedural thriller about a machine capable of predicting crimes, but gradually becomes one of television’s most powerful reflections on artificial intelligence, mass surveillance, privacy, free will, and artificial consciousness. The series shows that the real problem of AI is not merely technical, but moral: who decides which lives matter, which threats are relevant, and how much decision-making should be delegated to algorithmic systems. By contrasting the Machine, shaped by ethical limits, with Samaritan, driven by efficiency and control, the series anticipates many of today’s deepest dilemmas in digital society. In the end, Person of…
Those Who Can’t, Teach? Teaching, Academia, and the True Meaning of Knowledge
This essay begins with a personal experience in Physics education at UFMG to reflect on the meaning of teaching and the persistence of the cliché “those who can’t do, teach.” Drawing from the philosophical tradition of Aristotle—who understood teaching as an expression of true knowledge—and the irony of George Bernard Shaw, the text examines the contemporary tensions within higher education.
It argues that the phrase endures not because it is true, but because it reflects real problems: the devaluation of teaching, the expansion of bureaucracy, the dominance of academic metrics, the loss of social prestige, and the structural constraints of…
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