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The projects themselves specified that lying is okay. Output at all costs, at all parameters, as interpolating is a feature, not a bug. It could just error out
by InDubioProRubio 2y ago
The projects themselves specified that lying is okay. Output at all costs, at all parameters, as interpolating is a feature, not a bug. It could just error out at loss of certainty, but then you would stand there, having nothing most of the time.
- ithkuil 2y agoInterpolating is an awesome feature, very practical: summarization, style transfer. Instruction following is also useful and unlocks another tier of features. The fuzziness of the model behaviour plays a useful role because natural language is imprecise. The ability to interpolate this remains useful. Once machines understand natural language our own psychology kicks in and assigns properties like "wisdom" and "knowledge" to agents that can "talk well". This may lead us to expect something from tools that haven't been designed to perform a given task. For example our current LLMs are not very good at precise information retrieval because they haven't been designed for that. They happen to be able to perform information retrieval as a side product of the mechanism that teaches them how to speak in the first place. The raw output of the broca area in our brains is probably not something you want to connect directly to the mouth without mediation
- InDubioProRubio 2y agoWe need training exercises that teach us, how to think like a llm. Less like a human, more like a free association machine, dreaming a specific association flow, starting from a input. https://en.wikipedia.org/wiki/Ulysses_(novel) https://en.wikipedia.org/wiki/Ulysses_(novel) but with a feeling of dread, as the interpolations pile upon one another.. you can feel the thinness of the construction, as you are several layers out over ground truth on a thin tight rope.