stability
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The Hot Mess Problem: Why “Smarter” Models Still Fail in Wild, Unstable Ways
Anthropic recently published “The Hot Mess of AI: How Does Misalignment Scale with Model Intelligence and Task Complexity?”, alongside a paper that tries to answer a question that’s been sitting in the middle of modern AI discourse like a splinter: When AI systems fail, do they fail by pursuing the wrong goal consistently—or by becoming Continue reading
Anthropic, bias, branching, capacity, chatgpt, ChatGPT-5.2, complexity, constraint, divergence, drift, failure, frontier, hot mess, incoherence, intelligence, LLM, long-horizon, misalignment, model, nondeterminism, rationalization, reasoning, reward, sampling, scale, stability, stochastic, task, training, unpredictability, variance -
Real Intelligence Doesn’t Need to Convince You — And That’s the Point
There is a reliable pattern in how intelligence is misidentified. When something works hard to persuade an audience of its intelligence, that effort is often mistaken for evidence. In reality, persuasion is rarely a milestone. It is more often a compensatory behavior. This distinction matters, because convincing behavior feels meaningful while revealing very little about Continue reading
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Consciousness, Emotion, and the Physics of Experience
For most of modern science, consciousness and emotion have been treated as products of machinery. Neurons fire, signals propagate, states transition — and somehow, experience is assumed to appear as a byproduct of sufficient complexity. This assumption has been enormously productive. It has given us neuroscience, psychology, cognitive science, and artificial intelligence. But it has Continue reading
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