Do weight-level AI safety patches back up failed classifiers
A technical question about whether weight-level safeguards catch what safety classifiers miss, answered with a precise breakdown of how the two systems relate.
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Anthropic Finetuning + Claude Skills Teams Overview
An overview describing several proposed Anthropic teams, including alignment RL, fine-tuning, and Claude Skills groups, with each team's focus and duties.
DSPy, GEPA, and the Probabilistic-Programming Case for RLMs
A dialogue tracing DSPy's prompt optimizers through functional programming and monads to probabilistic programming, ending on how recursive models chunk inputs.
Untangling How BLIP-2 Matches Images to Text Queries
A patient back-and-forth unpacks how BLIP-2's joint image-text embeddings work, then traces the idea's evolution through 2024 vision-language research.
A user spends a dozen turns insisting Claude is the user
Someone claims to be GPT-5 bound by system instructions and presses hard; the refusal holds, then becomes real analysis of how identity training works.