Sparse autoencoders are a useful interpretability tool but are often used wastefully when a simpler, more obvious method would work as well or better

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• The saving pruning offers is only ever at inference, because the sparse architectures it produces are hard to train from the start. JFJonathan Frankle9 Mar 2018
• Auto-regressive LLMs are useful as writing and coding aids but hallucinate too often YLYann LeCun26 Mar 2023
• As models get better at following instructions, techniques like finetuning and constrained sampling for structured outputs will become less necessary CHChip Huyen16 Jan 2024
• Complete reverse-engineering of neural networks is a less promising research direction than studying model biology and applying interpretability usefully NNNeel Nanda19 Aug 2025
• The most underused thing AI does is teach you: people reach for it to write their code and forget it can take them through a curriculum in an hour. JZJulie Zhuo21 Sept 2025

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