"Thousand-dimensional structure" by Geoffrey Irving, David Africa
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Glimmers of low-dimensional structure
Our understanding of AI training and alignment as a field is very poor. If sufficient alignment of superintelligent AI agents requires pinning down the precise meaning of alignment and turning that meaning into high-accuracy training data and algorithms, we are likely to fail. Modern LLMs have trillions of parameters: our understanding is unlikely to be sufficient to pin down a trillion separate numbers.
Happily, there is a growing literature on such low-dimensional structure in AI models, showing that intervening on one aspect of model behavior has strong downstream effects on other aspects:
Topic
Description
Emergent misalignment
Betley et al. 2025 found that LLMs fine-tuned to output insecure code can become broadly misaligned across many other behaviors. MacDiarmid et al. 2025 found [...]
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Outline:
(00:42) Glimmers of low-dimensional structure
(03:57) Intervening without hiding the structure
(06:34) Toy models of modern training
[... 4 more sections]
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First published:
July 30th, 2026
Source:
https://www.lesswrong.com/posts/sFhW3ZnPMJdnB4Dd6/thousand-dimensional-structure-1
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Narrated by TYPE III AUDIO.
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