Well a light refactor of deduplicating code would be a refinement that is generally easy to review and likely comfortably in the capability of the codegen.

Versus creating, which generally is harder to review and requires the submitter to explain the rationale behind the change.

Volume of code and nature of change.

Of that comes to pass, they can change it.

The codegen is a particularly big problem for famous open source projects. All of a sudden you have a flood of people trying to get their name on your project and flooding you with low quality stuff. Codegen enables folks without good ideas to generate submissions that demand a lot of review. Being about to shoot down obviously AI content without deeper review is pretty critical to keep the project viable. There may be good things tossed out with the bathwater, but it is a ton of bathwater. Besides, if there’s something real behind it, a good human is likely to emerge to take it forward more credibly.

Closed source or personal projects can enjoy a bit more judgement. You can evaluate the people independent of the submissions and may be able to have an even more nuanced take.

It’s not like it is a legally binding agreement that needs a high level of quality in adjucation. If things seem off then it can be cited and you don’t have to prove it. Conversely, if something passes human review despite being codegen, well then I guess the codegen isn’t that bad

I’ve seen a pull request that was ultimately nonsensical but plausible and short, and purported to be needed in a configuration none of the maintainers had access to. It was a pretty harmless change either way so they were inclined to accept it. But they sought a little clarification and the clearly LLM response in comment got it shut down. No human stepped up to actually explain an understanding and the LLM sounded like a TV show writer writing tech, sentences that sounded credible but to anyone with understanding was nonsensical bullshit.

LLM code can sometimes be hard to tell in a short code change, but the prose when things are anything vaguely needing explanation is just so very very obvious.

Yeah, but you’ll have to submit to every known provider and hope the user used one of the ones that provide this checking service, and didn’t do something like ask a local model to just randomize synonyms in a text.

You still have choices.

Variable names are pretty free form.

A switch statement or if/else might be a choice that achieves the same thing. Waffling between them would be highly suspect, since a person isn’t going to be so wishy washy. So you could use structural choices too.

AI code tends to look more obviously AI than prose anyway.

Well, they got the 1 off-site bit…

Dude lamenting women not being attracted to intelligence checks out as he use a picture that clearly focuses on a woman’s intelligence.

Hence why openAI seems now to want to stall IPO as long as they can…

And you are right, they singlehandedly are most of the problem despite not even being in the strongest position even if you are bullish on AI.

He is technically correct, the best kind of correct!

Volumes are going to be down, but they want the same revenue, so they increase unit price, comfy in the reality that it will still be, percentage wise, not worth it for most to care. Will it make it unaffordable for some? Probably not appreciably more than the hardware is doing all by itself.

So in short, it is just because they can.

Not just that, but had to be born after 1945 to be considered “Boomer”. Clearly time travelers

In the same way it’s accurate to call the human brain a prediction machine

I have seen no evidience presented that the human brain is simply making statistical predictions.

This seems to be a relatively new thing some people are asserting, because they see the LLM behavior and have decided that absolutely it looks so human like it must act the same, and since we understand that LLM is fundamentally statistical prediction of a token, then obviously human consciousness must operate on the same principle.

Even the latest models generate the sort of mistakes that stem from the fundamental limitations. A lot has been done in some contexts for making that not matter so much (e.g. in software development, the strategy is that code may have some verifiable goal, and the models can let the mistakes fly, then take the feedback from the goal, and iterate more). So it still can be very useful, but clearly it isn’t human like because of some of the completely dumb behaviors that result from it not actually thinking about it. It is at it’s best when either mistakes don’t matter (particularly fiction) or at least first mistakes don’t matter and can be automatically reconciled with facts.

By nature, the meme examples will get better because everyone talks about it and suddenly having all that discussion in training data and in search results, the statistics fix. However the operating principle behind them remains the same.

LLM output makes everything stupider, even LLMs.

Sadly, often.

It is sticking the most common content into a blender and dispensing the result according to a few tweaks. I have seen a lot of people eat that up.

Same reason why there’s so much money in low-effort mobile gaming.

It’s one of the things that really sucks, people with creative talent that would otherwise be rewarded and have their vision shared for lack of too many other options being drowned out by a flood of no-effort slop that the masses are just fine with.

For reference, that was the year Vista came out with a minimum memory of 512MB, with 1GB suggested.

… I would like to subscribe to your newsletter.

Allow me to introduce the incels.

Hard to get that experience when no one wants to be around you at all, let alone naked.

For example, everyone knew the gallows were for Mike pence, but that doesn’t mean that Mike pence was doing the wrong thing… In that occasion…

You have to remember that the current investment level assumes that somehow everyone is going to use the AI stuff that much. It won’t do if the only heavy usage is code generation.

“Ai” has mostly wasted my time.

Particularly other people’s use of AI has wasted my time…