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CrimsonRain • today at 9:40 AM • 1 reply • view on HN

Have you ever wrote some code/algo that seemed "simple/obvious" to you yet to someone else, it seemed incomprehensible?

If you have a 20-40 IQ points gap with another developer, this happens a lot.

The baseline of "simplify" is wildly different based on your IQ points. That's precisely why exceptional students are usually bad in teaching. They try to break things down, simplify, but things still go over the head of normies.

However, we can intervene/train the models. So it should be possible to focus on the simplification, and as you said, it will come eventually.


Replies

juliusjh • today at 12:34 PM

I've been mostly reading here but created an account to disagree with this statement: The smartest people I know were always amazing at explaining. This was true for me as undergrad and graduate student where the smartest peers and the most renowned professor were always also the best at explaining, and it is true now at research level in a related field. When I am not sure if I really understood something to the core, I try to find a colleague who knows very little about it; if they understand my explanation well, that's a good sign.

Those who really understand a topic are usually also able (and great at) explaining it in very clear and "simple" terms. This may be part of my personal bias; I see theory builders as those who advance the field the most, and these are usually also amazing at explaining it. On the other hand, those who mostly "grind" through problems (approach them as complicated puzzles) with effort/time were often bad at explaining.

I observed the same for programming: the "architects" usually explain very well, the "debuggers" often don't. LLMs very much remind of the grind/puzzle approach. It does makes sense that RLVR, which in my understanding enables a lot of these results, would lead to a more mechanical approach.

Of course, I can't make any predictions on whether it will stay that way. But I strongly suspect that we need different ways of training for LLMs to write better text and explain better (I suspect the vagueness of LLM language is the result of RLHF as vague expression is less often incorrect).