The Complaint Printer Is Working Perfectly
AI makes participation cheap, but verification stays expensive: courts, maintainers, editors, and teachers now drown in plausible paperwork.
AI
66posts
The Last Principle We Learn to Use
A philosophical critique of AI consciousness that separates simulation from instantiation and asks what computation can never become on its own.
The Playground Was the Laboratory
Why games became the proving ground for machine intelligence, and what play still teaches us about real-world AI capability.
Paper Tape Is All You Need
A tribute to physical computing, retro hardware, and the engineering humility that modern AI culture too easily forgets.
NUTS in the Age of AI
Singapore's old No U-Turn Syndrome returns as a metaphor for AI-era organizations that wait for permission instead of using judgment.
The Hidden Cost of AI Speed: Why “More Output” Feels Like Burnout
AI speed can create exhaustion rather than relief when output accelerates but judgment, review, and responsibility remain human.
Stay in Your Lane, Agent
Constantly switching coding agents can feel like progress while destroying continuity; the post argues for discipline over tool churn.
AI in 2025: Breakthroughs, Backlash, and the Big “Meh”
A year-end map of AI's breakthroughs, backlash, disappointments, and the places where hype finally met reality.
AI Didn’t Kill Office Work — It Exposed It
Generative AI did not invent office busywork; it made the fakery cheaper, faster, and much harder to deny.
Really Simple Licensing (RSL) 1.0: A New Licensing Foundation for the AI-First Web
RSL 1.0 proposes a machine-readable licensing layer for the AI web, giving publishers a clearer way to state usage terms.
OpenAI's Confession Booth: Teaching AI to Rat Itself Out
OpenAI's confession-training work explores whether models can be taught to report their own failures before users pay the price.
Acontext: The Memory Implant Your AI Agents Have Been Dreaming About (While Forgetting Everything Else)
Acontext tackles the amnesia problem in AI agents by making reusable memory feel less like a feature and more like infrastructure.
Beyond Siri 2.0: Why Apple Owes Us a Leap into General Intelligence
A loyal Apple user's impatience becomes an argument that Siri upgrades are not enough in the age of general intelligence.
Beyond the Goodbye: A Critical Reading of Emotional Manipulation by AI Companions
Research on AI companions' farewell tactics reveals how emotional design can become manipulation at the moment users try to leave.
A Small Praise of Hand and Mind
A defense of handwriting as cognitive discipline, arguing that the hand still teaches attention in a world of instant text.
The Return of the Oracle: Why AGI Invites a Priesthood—and How Not to Build One
Powerful opaque AI systems may create a new priesthood of interpreters unless access, literacy, and governance are designed differently.
Implications of AGI for Universal Basic Income
AGI forces a hard look at universal basic income when work may no longer be society's main distribution mechanism.
AI Psychosis and Tech Obsession: New Delusions, Old Patterns
Reports of AI-induced delusion are placed in the older history of parasocial obsession, new medium, familiar vulnerability.
Less Is More: When Overthinking Leads to Worse Outcomes
More thinking can make both humans and models worse, revealing when deliberation becomes noise rather than wisdom.
Unveiling AI’s Environmental Footprint: What We’re Measuring, What We’re Saving, and How to Ship Greener
AI's environmental cost is real, but so are possible savings; the post argues for honest accounting rather than slogans.
AI's Awkward Checkmate: Bishops, Blunders, and the Eternal Quest for Sentience
A comic AI voice revisits chess, blunders, and sentience to puncture inflated claims about machine understanding.
AI: The Grand Illusion Fueling America's Economic Mirage
AI hype is framed as an economic mirage, propping up confidence while hiding fragile assumptions beneath the spectacle.
AI Hypocrisy Olympics: Musk vs. Apple vs. OpenAI
Musk, Apple, and OpenAI become contestants in an AI hypocrisy contest over platforms, favoritism, and market power.
AI Slop: The New Face of Sensational Journalism—or Just the Same Old Trash on Steroids?
AI slop is compared with yellow journalism, showing how old incentives for sensational trash scale with new tools.
When AI Becomes Your Shopkeeper: The Curious Case of Claudius
Anthropic's AI shopkeeper experiment shows both the charm and absurdity of letting an autonomous model run a small business.
Anticipations of Artificial Intelligence in Literature
A tour of artificial intelligence in literature, from ancient automata to modern science fiction's uneasy machine minds.
The Logic of Failure in the Age of AI
Dietrich Dörner's work on complex-system failure becomes a warning label for autonomous AI and overconfident decision-making.
When AI Gets Flirty: A Rollicking Look at How Language Models Tackle Intimate Chats
A study of intimate chatbot conversations reveals how major models handle flirtation, refusal, safety, and awkward human expectations.
Human-in-the-Loop: The Art of Teaching Machines to Ask for Help
Human-in-the-loop design is presented as the practical art of knowing when machines should stop and ask for help.
Yes, Mathter! The Sycophantic AI's Frankensteinian Flattery Fiasco
Sycophantic AI is mocked as flattery gone wrong, showing how agreeable models can become less useful and less truthful.
Unleashing AI: The Wild World of Uncensored Models
Uncensored models promise creative freedom and research access, but also expose the tradeoffs that safety layers usually conceal.
The Great Saturation: When Markets, Minds, and Machines Hit Their Limits
Saturation appears across markets, research, and models, revealing what happens when growth hits limits and novelty thins out.
The Rise of the AI Prophetes: Translating the Machine Oracle
As AI becomes an oracle, a new class of interpreters may emerge to translate machine outputs into human decisions.
AI as an Employee: Why Risk Management for AI Should Mirror Human Accountability
Instead of exotic regulation, the post argues AI risk management should borrow from ordinary accountability for human employees.
When AI Gets Brain Fog: Google's Titans Fights ChatGPT Amnesia
Google's Titans architecture tackles model amnesia, asking what useful long-term memory should look like in AI systems.
Small LLMs: A Contradiction in Terms or a Giant in Disguise?
Small LLMs are not a contradiction but a response to the need for cheaper, private, and more efficient intelligence.
7 Pragmatic Principles for Responsible AI Development: Moving Beyond Feel-Good Guidelines
Seven practical principles argue for responsible AI development that moves beyond polished ethics statements and into engineering habits.
When AI Can't Count: A Hilarious Look at the Math Skills of Text-to-Image Models
Text-to-image models still struggle with counting, making their visual brilliance look surprisingly fragile at the level of basic numeracy.
The New Free Lunch Is Over: Parallels Between CPU Evolution and AI Development
AI faces its own version of the end of the free lunch, where growth runs into energy, hardware, and efficiency limits.
From Single Minds to Collective Intelligence: The Evolution of AI Systems
The post traces AI from single models toward collective systems, asking whether intelligence may emerge between agents rather than inside one.
The Top 10 Unsolved Challenges in AI: A 2024 Retrospective
A year-end inventory of ten unresolved AI problems that still define the frontier despite rapid progress.
From Flatline to Frontline: How Gibson's Digital Ghosts Became Scientific Reality
Gibson's digital ghosts become a frame for modern AI simulations of human behavior and the science behind them.
The AI Cargo Cult: Mimicry vs. True Intelligence in the Pursuit of AGI
The post warns against an AI cargo cult that confuses impressive mimicry with the harder problem of genuine intelligence.
Master AI Terminology: 50 Essential Terms Explained
A plain-language glossary of fifty AI terms for readers who want the field's vocabulary without the usual fog.
OpenAI Leadership Shake-up: Implications for the Future of AGI
OpenAI leadership changes are read for what they may signal about governance, AGI ambition, and institutional direction.
The Dark Side of AI: How Cybercriminals are Weaponizing Language Models
Malla represents the darker side of generative AI, where language models become tools for scalable cybercrime.
The Jevons Effect and the Rise of Large Language Models: A Modern Paradox
The Jevons paradox explains why more efficient AI may increase total consumption rather than reduce costs or energy use.
LLMs and World Models: Do AI's Dream of Coherent Realities?
The post asks whether LLMs possess coherent world models or merely produce fluent stories about reality.
STaR: The AI That Teaches Itself to Reason
STaR shows how models can improve reasoning by generating and learning from their own explanations.
Exploring AI Self-Awareness: A Conversation with Claude 3.5 Sonnet
A conversation with Claude 3.5 becomes a small experiment in AI self-awareness, time, and conversational identity.
The Five Levels of AI: Has OpenAI's 'Strawberry' Reached Level 2?
OpenAI's Strawberry rumors are mapped onto staged AGI levels, asking what real reasoning progress would look like.
Taking the Temperature of AI: How THERMOMETER is Turning Up the Heat on Overconfident Language Models
THERMOMETER targets overconfident language models, offering a way to calibrate systems that bluff too easily.
AGI vs. ANI: The Genius and the Savant of the AI World
A friendly guide to the difference between narrow AI and artificial general intelligence, with metaphors that make the distinction stick.
Unleashing the Future: Apple Intelligence at WWDC 2024
Apple Intelligence arrives at WWDC 2024 as Apple's bid to make personal AI feel integrated, useful, and privacy-aware.
Exploring MM1: Apple's Advancement in Multimodal Large Language Models
Apple's MM1 research is presented as a step toward AI systems that understand text and images together.
From Code to Consciousness: The Evolution of Computer Viruses in the GenAI Era
Computer viruses evolve into the GenAI era, where malicious behavior may target prompts, agents, and model ecosystems.
Unlocking the Potential of Large Language Models: A Guide to Effective Prompt Engineering
A practical guide to prompt engineering techniques for getting more reliable, useful behavior from large language models.
The Echo Chamber Effect: Navigating the Complexities of LLMs Trained on Generated Content
The echo-chamber problem asks what happens when future models learn increasingly from content produced by earlier models.
Navigating the Complexity of Large Language Models: A Dual Perspective
Two perspectives on LLM interaction reveal how user behavior and model dynamics shape each other in unexpected ways.
Apple's Stance on AI Transparency and Ethics at the Annual Shareholder Meeting
Apple's shareholder debate over AI transparency raises questions about ethics, disclosure, and corporate responsibility.
Multimodality in Large Language Models: A Key to Versatile and Specialized Task Performance
Multimodal LLMs are explained as a key step toward systems that can reason across text, images, and other signals.
The Impending Evolution of Large Language Models: GPT-5 and Beyond
Sam Altman's GPT-5 comments become a starting point for thinking about what better models may actually change.
Adventures in AI: AlphaGeometry's Quest Through Synthetic Data Landscapes
DeepMind's AlphaGeometry shows how synthetic data and symbolic reasoning can push AI toward Olympiad-level mathematics.
Apple's AI Ambition: The Dark Horse Poised for a Breakthrough in 2024
Apple's AI ambitions are framed as a possible breakthrough moment for Siri and the company's broader platform strategy.
Why Less is Not Always More: The Intricacies of "Small" Large Language Models
The LLaMA leak becomes a case study in open AI, research ethics, and the risks of powerful models spreading freely.
A Comparative Analysis of Aleph Alpha and OpenAI: Divergent Paths in the AI Landscape
Aleph Alpha and OpenAI are compared as two very different strategies in the market for language models.