Comment by D-Machine
4 days ago
Unfortunately not all ideas can be meaningfully compressed into just a few sentences without completely destroying the important parts, and this is especially the case in higher-level math, stats, ML, and deep learning.
Also, IMO there is an effective abstract anyway under the title text:
The cause of polysemanticity in early model organisms wasn’t superposition, but several ordinary, mostly fixable issues. We can now understand most neurons in models up to trillions of parameters, and think the outlook for mechanistic interpretability may be far better than we thought.
But you are right the article needs significant editing down.
The prose sounds nonsensical. It could be that I am uninformed; it could also be that the text is in fact nonsense.
A lack of clarity often means that the ideas are confused, or that the author is trying to obfuscate weak claims.
On length and complexity, it gives it a veneer of weight and expertise and yet everything inside is vaporous.
Scanning back, I can see I was responding here was what I was worried was a mistaken assumption that a meaningful abstract / summary can always be written for truly complex and novel topics. Sometimes all it can be is a sales pitch for reading the details, and I thought the summaries here were good enough in this sense.
But I agree the author is obfuscating weak claims via length / complexity (and it may be as much for his own sake as for his readers'). The basic claim ('maybe AI will be more explainable/tractable than initially thought') is IMO intelligible, and not completely nonsensical, but also extremely vague and vibesy, which, technically, I must agree is in the same territory as nonsense, at least.
Based on our other exchanges here we mostly agree with the problems of the article I think.
The deeper issue is that it is much easier to disagree or agree with a short statement of fact than it is with a massive monologue some parts of which are vague. If you really have a breakthrough it can be a lot shorter than this, the body of the 'attention is all you need' paper was 10 pages. That paper of course was produced 'pre-AI' and now it is much easier to generate really long articles on anything but it does carry some weight that the length of the article vs the payload ratio is completely off here.
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