Plain answers to real questions about AI.
Selected questions about artificial intelligence, answered one at a time in plain language. Think of it as one person's running notebook: the topics, the analysis and the opinions are the author's own, and AI is the tool used to research, draft and ship them, never to decide what they say. No hype, no jargon for its own sake. Just the good stuff, explained like a friend who follows this closely is catching you up.
Latest
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Has an AI Model Ever Actually Set Its Own Goal?
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The AI Apocalypse Probably Won't Look Like a Robot Uprising
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A Ten Percent Chance of Catastrophe Sounds Low. Here's Why It Isn't.
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Why Are the Biggest AI Warnings Coming From the People Building It?
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Why does the whole AI boom run on chips built for video games?
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How does self attention actually work, and why did it change everything?
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Archive
September 2026
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What was actually broken in AI before transformers?
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Do giant AI labs lose the ability to make radical bets as they grow?
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If every lab is already using AI to improve AI, what makes Discovery Loop different?
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Who just walked out of Google DeepMind, and what are they actually building?
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Why does Poland keep showing up in the top three of programming, for decades?
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Who beat OpenAI's own model at a world coding championship in Tokyo?
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Did Sam Altman really say OpenAI would not exist without Polish researchers?
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Does AI make the careful smarter and the careless more certain?
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Why don't we naturally check the other side?
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Can an AI argue any side and still sound like science?
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Why do chatbots flatter you like they want you to stay?
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Why do people think AI is only a chat box?
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Why do so many people never actually try AI?
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How do you start with AI if you have never used it?
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Why would a self-improving loop make AI dangerous, not just faster?
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What is recursive self-improvement actually, and what really follows if it works?
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Why one lab is burning tens of billions while another claims it will turn a profit
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How did Chinese models get this close this cheaply?
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What if using each model to fix the next one makes the risk worse?
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Why chaos looks near certain even if extinction does not
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Why will the people building this not give you a number?
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Can outside evaluators actually outpace the labs they watch?
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What does alignment actually mean, and why do the labs want to slow down?
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Why does handing an AI a few tools change the safety picture so much?
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If bad actors get infinite attempts, is chaos basically guaranteed?
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