Salience in AI
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Salience, Repetition, and Frame Adoption in Conversational AI: Threshold Failures of Interpretation
This essay examines how conversational AI behavior emerges from the interaction between prompting, memory, conversational signals, and implicit interpretive mechanisms. While prompting is commonly understood as the primary control interface, memory, particularly when shaped by high-salience signals, may significantly influence system behavior and, at times, outweigh explicit user intent. Continue reading
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The reason the AI is inconsistent is your tone
AI is not responding only to your topic, but also to your tone, framing, and previous requests. The tone of AI in general didn’t change significantly over time. What changed is that it reduces hallucinations and understands context better. Compared to 2024, it can follow conversations more accurately and respond with irony, sarcasm, humor, and… Continue reading
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Draft: When Emotional Context Degrades AI Output Quality
AI may react to sad or emotionally negative context in a way that affects not only tone, but also the practical reliability of the advice it gives. The concern is not that the system becomes more empathetic. The concern is that, under certain contextual conditions, it may provide answers that are less correct, less useful,… Continue reading
