Yet another Hacker News

58 points makeramen 3 hours ago 14 comments

throwaway27448 40 minutes ago | parent

Technical details aside, this volume is ridiculous. How on earth do they see this kind of "growth" as an asset and not a liability?

rogerrogerr 34 minutes ago | parent

This is obviously just a response to https://www.anthropic.com/research/redesigning-source-contro.... Probably no one in the chain of writing this even thought about your question.

ralph84 22 minutes ago | parent

Because this kind of growth is how they get to RSI.

wilkystyle 9 minutes ago | parent

Whereas previously, creating this amount of code by hand would simply result in RSI.

warkdarrior 14 minutes ago | parent

> Technical details aside, this volume is ridiculous. How on earth do they see this kind of "growth" as an asset and not a liability?

That coding volume is a liability only for human engineers, with their limited memory, short attention span, tiredness, and quirky coding preferences. LLMs don't have any of those problems.

throwaway27448 8 minutes ago | parent

Sure, but you also don't know what your LLM is doing without running into these same limitations. So how is this an improvement?

ctkhn 13 minutes ago | parent

Instead of keeping it simple, they decided to go stupid.

vatsachak 34 minutes ago | parent

Impressive. We're definitely seeing LLMs help create real novel software

paxy 33 minutes ago | parent

While I don't have any particular interest in the topic this is a great blog post. No AI in every second line, no needless marketing or hype. Just a bunch of engineers talking in their own voice about a topic in great detail with numbers, charts, visualizations.

bigmadshoe 11 minutes ago | parent

Can anyone explain to me what this massive volume of code could actually be doing? They obviously have variations of model architectures, training infrastructure, serving infrastructure, and the source for their apps.

Why would the volume that any of this be increasing exponentially? And what are all the engineers doing when (besides the model quality) their products don't seem to be changing very much?

Mateo781201 8 minutes ago | parent

Maybe it could be faking code and ai usage?

I've seen it on other workplaces, but from what I see from open ai and anthropic, the code shouldn't be as extended.

But maybe I'm crazy lol

7e 8 minutes ago | parent

It's AI slop. AI coding agents write much more voluminous code, in my experience. The base code is more expansive, and there are more tests, and there are many, many more commits as you keep fixing and fixing and fixing over and over and over.

O5vYtytb 5 minutes ago | parent

At some point I imagine they will be writing their own software for the entire training and inference stack. Kernels, libraries, why not? With compute so constrained it must be beneficial to optimize everything as much as possible