rodspeed

11 ms·

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by rodspeed 6mo ago
Fair point on the title. I've emailed to mods to see if they can update the title. I don't think it's anthropomorphizing to study how vocabulary constraints change reasoning quality. The paper doesn't claim LLMs think. I
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Umwelt Engineering: Designing the Cognitive Worlds of Linguistic Agents(arxiv.org)
2 points by rodspeed 6mo ago|3 comments
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by rodspeed 6mo ago
I ran 4,470 trials across three language models (Claude Haiku, GPT-4o-mini, Gemini Flash Lite) on seven reasoning tasks, constraining them to write in E-Prime (no "to be") or without possessive "to have." The constraints
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by rodspeed 6mo ago
yep it's public: https://github.com/rodspeed/epistemic-memory The observations layer being append-only is smart, thats basically the same instinct as the tensions log. The raw data stays honest even when the inter
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by rodspeed 6mo ago
Wait a minute! Ha, just saw this. The knowledge graph I mentioned is a separate project (heartwood on my profile). Different angle from propstore but I think we're circling the same problem, conflicting claims that shouldn't be si
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by rodspeed 6mo ago
You're probably right long term. If LLMs eventually handle memory natively with confidence and decay built in, scaffolding like this becomes unnecessary. But right now they don't, and the gap between "stores everything flat&q
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by rodspeed 6mo ago
I'm one of those zero star repos. I've been using Claude Code for some weeks now and built a personal knowledge graph with a reasoning engine, belief revision, link prediction. None of it is designed for stars, its designed for me
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by rodspeed 6mo ago
I've been building persistent memory for Claude Code too, narrower focus though: the AI's model of the user specifically. Different goal but I kept hitting what I think is a universal problem with long-lived memory. Not all stored