3 ms·

LLM research on Hacker News is drying up

30 points by dcastm 5mo ago

th0ma5 5mo ago
[dead]
simonw 5mo ago
Hacker News isn't a great place to discuss papers generally. Having a productive discussion around a paper requires at least reading and understanding the abstract, and the most successful content on HN (sadly) is content where people can jump in with an opinion purely from reading the headline. Anyone know of any forums that are good for discussing papers?
- irishcoffee 5mo ago
  I just email the authors with questions. Surprisingly high response rate.
- breppp 5mo ago
  [flagged]
- tptacek 5mo ago
  This is true across all research subject areas (I'm not especially tuned into LLM research but am to cryptography, which also happens to be a field that gets a lot of play on HN). I think it's just a function of how many people conversant in the field are available to talk about it at any one time.
- gessha 5mo ago
  There are/were isolated communities on Discord around fast.ai, MLC, MLOps that talk papers more in depth but it’s hard to organize a community without commercial or academic incentive.
  - fc417fc802 5mo ago
    The difficulty is perhaps unsurprising given the time sink that is reading a given paper to any reasonably complete degree of understanding.
- gcr 5mo ago
  /R/MachineLearning is not bad But the gold standard is a small signal or discord community of like-minded, fairly tight knit friends. You may have to organize this yourself
- gavinray 5mo ago
  Unironically, very niche subreddits.
- simonw 5mo ago
  ... and this thread over here seems to be proving me wrong already: https://news.ycombinator.com/item?id=47893779 https://news.ycombinator.com/item?id=47893779
gessha 5mo ago
With big commercial labs clamming up about training details, hardware requirements going up, and overall tired sentiment about AI in general, that’s not really surprising. ML research shows up on the front page if it shows splashy claims or results. Mundane cockroach papers that advance the field one nudge at a time aren’t that interesting for the average reader. Cool to see the sentiment visualized though.
latexr 5mo ago
> So I asked Claude (…) > I asked Claude (…) > So I asked him (…) > (…) so I asked Claude (…) > (…) so I asked Claude (…) > Thanks, Claude. There doesn’t seem to be one bit of original research in the post, and no explanation of the data or conclusions. For example, what exactly does it mean that the papers “held up”, and how exactly did Claude reach that conclusion? If you don’t know, we can’t trust the data. If you do know, it should be in the post. As it is, the post is almost devoid of information. Everything was “I asked Claude”. There’s no value here (aside from some saved tokens) above just crafting a prompt and saying “here, ask your favourite model this question”.
- dormento 5mo ago
  And it has a citation block at the bottom! Like anyone would want to cite this in a serious context. This must be a troll.
deleted 5mo ago
[deleted]

30 points by dcastm 5mo ago

[dead]

Hacker News isn't a great place to discuss papers generally. Having a productive discussion around a paper requires at least reading and understanding the abstract, and the most successful content on HN (sadly) is content where people can jump in with an opinion purely from reading the headline. Anyone know of any forums that are good for discussing papers?

irishcoffee 5mo ago
I just email the authors with questions. Surprisingly high response rate.
breppp 5mo ago
[flagged]
tptacek 5mo ago
This is true across all research subject areas (I'm not especially tuned into LLM research but am to cryptography, which also happens to be a field that gets a lot of play on HN). I think it's just a function of how many people conversant in the field are available to talk about it at any one time.
gessha 5mo ago
There are/were isolated communities on Discord around fast.ai, MLC, MLOps that talk papers more in depth but it’s hard to organize a community without commercial or academic incentive.
- fc417fc802 5mo ago
  The difficulty is perhaps unsurprising given the time sink that is reading a given paper to any reasonably complete degree of understanding.
gcr 5mo ago
/R/MachineLearning is not bad But the gold standard is a small signal or discord community of like-minded, fairly tight knit friends. You may have to organize this yourself
gavinray 5mo ago
Unironically, very niche subreddits.
simonw 5mo ago
... and this thread over here seems to be proving me wrong already: https://news.ycombinator.com/item?id=47893779 https://news.ycombinator.com/item?id=47893779

gessha 5mo ago

With big commercial labs clamming up about training details, hardware requirements going up, and overall tired sentiment about AI in general, that’s not really surprising. ML research shows up on the front page if it shows splashy claims or results. Mundane cockroach papers that advance the field one nudge at a time aren’t that interesting for the average reader. Cool to see the sentiment visualized though.

latexr 5mo ago

> So I asked Claude (…) > I asked Claude (…) > So I asked him (…) > (…) so I asked Claude (…) > (…) so I asked Claude (…) > Thanks, Claude. There doesn’t seem to be one bit of original research in the post, and no explanation of the data or conclusions. For example, what exactly does it mean that the papers “held up”, and how exactly did Claude reach that conclusion? If you don’t know, we can’t trust the data. If you do know, it should be in the post. As it is, the post is almost devoid of information. Everything was “I asked Claude”. There’s no value here (aside from some saved tokens) above just crafting a prompt and saying “here, ask your favourite model this question”.

dormento 5mo ago
And it has a citation block at the bottom! Like anyone would want to cite this in a serious context. This must be a troll.

deleted 5mo ago

[deleted]