Wasn’t all that obvious to anyone who read the original post when they got to the section that explicitly explained what the author of this post is now summarizing?

Sure if you only read the title and brief at the top you’d walk away without the full picture though.

This is a better response imo: https://news.ycombinator.com/item?id=50344861

Given that the top comment yesterday said “this is insane […] I’m shook” I’d say no, it wasn’t all that obvious to everyone.

As someone who uses LLMs in their coding but doesn’t pay attention to every development this is why I find it all so exhausting. I keep feeling like I need to keep up to date but there’s no point reading incremental updates because everything is so overhyped.

If you read comments about the paper it's pretty obvious people are misled. People think that the method read in Qwen weights directly to improve it. That's not what it did --- it authored a program to analyse and fix the weights.

What's confusing is they do have experiments that read raw weights, and the abstract is misleadingly written to make it sound like that's how the Qwen experiment works.

As someone who has been working in ML for 30+ years, and has designed and trained too many NNs to keep count, this is the first time I've seen anyone twiddling the weights directly. Usually you play with the training set, exemplar weights, model's hyperparameters, etc. I've never seen a trained network being modified by hand.

> who read the original post

I think there's your answer. A hell of a lot of people will often read the title without reading the contents of the article. I admit I'm often guilty of that

At this moment on the front page (early morning in the US), this post is #1 and the other one is #2, so it's working like a warning about the other one being misleading before clicking on it.

So you mean that the "The 'Astra can read and write weights to improve Qwen' post is misleading" post is misleading? You should post that.

Yeah. The article is not misleading. The title is, but you know, headlines are all lies that's why you read the article.

There’s some Dunning-Kruger effect going on. Many are looking to more knowledgeable commentators in hackernews for a digestible eli5 takeaway, myself included as the original article flew over my head.

Unfortunately it’s hard to distinguish who to trust in threads as many commentators sound overly confident and knowledgeable. They think they understand the article and its nuances, but they actually don’t and end up perpetuating false info.

Yeah, I was disappointed reading the title of this post because the work it is referencing was very exciting. But after reading this post, it's clear that the author is just pulling an "uhm, ackchyually" and responding to an abstract audience of laymen readers who don't know (or care) about any of the details of these results.

Anybody who actually read the original research site was fully aware of the details of the experiments because it's a well-written research site that made everything very clear. This author is clearly just jumping on the hype as a sort of contrarian where they were frustrated with how much excitement the research was generating and wanted to "correct the record" for the set of people who don't matter in this space.

LLMs are extremely hyped up right now. It's like when everyone was crypto-crazy, and threads were full of people who had no idea what was going on but were very excited.

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