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Why AI Can’t Stop Talking About Second Order Effects
Why do large language models constantly pivot to systemic implications and "second order effects"? This episode explores the "Consultant Bias" baked into training data and how human feedback inadvertently rewards verbosity over directness. We examine the technical architecture behind these linguistic quirks, the impact of synthetic data feedback loops, and what happened when developers tried to "fix" the fluff in the infamous Model X update. Join us as we unpack why AI models find it so difficult to give a straight answer and how our own intellectual vanity might be to blame for the…
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