morningsam

>"it's fine if you're an individual but not if you're large"

That's not what the GP said, they were referring to someone who "builds their own moat where they solely can profit and excludes others from the freedoms they themselves enjoyed".

I don't want to speak for them but I guess that LLM companies which release exclusively open weights models, or better yet, open weights plus training pipeline sources, would not fall into this category.

Currently-working-Nitter-instance URL for Cherny's tweet: https://shitter.thepixora.com/bcherny/status/210254334910233...

>I feel like coding will be dead soon, and what will be left are project management / team lead / product owner kind of jobs where you craft specs and steer AI agents on very high level.

And these will be gone, too, a couple months later. Or possibly even at the same time.

I've been wondering why ~everyone hasn't already been doing this, so my guess is that Twitter's API doesn't allow it.

I once met a guy who said the same thing and was convinced that this was the usual case, whereas me still getting them as an adult was very unusual (this came up when I got them, apparently his first time seeing an adult do so).

Not really, because you need a reputable source. The popular science article they linked is good enough for HN but WP would remove it.

>do LLMs generate D2 code as easily as Mermaid

Yes

>and do tools like Github and Confluence render them?

No

Finally someone says it. I read it like that every time and briefly imagine a Daily WTF style blog about the pitfalls and shortcomings of everyone's favorite IPC system, only to be sorely disappointed.

Why would any of this be a problem from the perspective of those who will own the remaining companies? They won't sell anything to normal humans who have no income anymore, true; but they don't need to, because their machines can produce for them whatever normal humans had been producing previously.

The preprint is interesting in that it predicts that on the way there, one can run into some kind of vicious cycle that leads to suboptimal outcomes even for the company owners. Navigating around this would certainly slow this process down, but I personally don't see it changing the ultimate outcome.

I would much prefer for a doctor who isn't sure to signal that fact somehow. It was annoying enough for LLMs to confidently lead you down wrong paths most of the time (they've gotten much better by now), we don't need humans doing it too. For lawyers it makes sense, of course.

Thank you. I wish they had used a pairwise comparison system like the one built by pil0u [1] for this. If I hadn't looked at all of them in advance, I would've had to go back to "normalize" my previous answers after seeing one that I especially like/hate.

[1]: https://news.ycombinator.com/item?id=49041625

Maybe this will lead to more business for tailors doing alterations, assuming the clothes people end up buying are expensive enough to justify it.

That basic idea is what made SO attractive in the first place, compared to forums where you had to scroll through pages and pages of in-jokes and tangents and animated-GIF signatures just to try and see if there is an answer.

Where they went wrong, in my opinion, is in the implementation details.

It's mostly death by a thousand cuts: Requiring reputation to gain the ability to post comments, then having one's answers deleted as "this should've been a comment". Overeager marking of questions as duplicates, e.g. despite the equivalence between two situations being non-obvious (e.g. someone asks about data type A, and it turns out that it's a subtype of B for which an answer that applies to both exists; that should not be a duplicate, the fact that it's a subtype is the answer!). Endless other decisions like that, which wouldn't have taken any extra effort to implement correctly.

One feature they could've built that would have taken effort but also greatly helped against the common newbie complaint of "hostility" would've been a "newcomer track", which would've been more forum-like and guided them towards either formulating a good question or seeing that's it's already answered. In the latter case, some of the keywords that came up during this process should've been fed back into SEO so that future newbies would become more likely find the answer via a search engine despite using clumsy terms. I think they tried a simpler and worse version of this idea towards the end with "staging ground" but by then it was too late.

And literally 3 sentences later he goes back to insulting him ("productivity fantasy fever dream"). Even if that is true, it's still an unwise post to publish in this form IMHO. If the goal was to defend Zig, that could've been done in a less personal manner.

This is how it's often done, but personally, I'd prefer if the information "With this comment I want to promote something I made" came first, so that people who aren't interested can skip it.

>but as soon as you approach ~$400/month they ask that you get a Claude/Codex Max subscription instead

While this seems to be allowed because the current ToS don't seem to explicitly forbid it, I'd be surprised if this loophole stayed open for long... Why would they even distinguish between business and (much cheaper) individual plans if companies can work around it by telling employees to just pay for the latter themselves?

Someone did an analysis and concluded that it appear to be at least partly (~10-15%) LLM-generated, or at least LLM-translated (see comments): https://www.lesswrong.com/posts/s58hDHX2GkFDbpGKD/linch-s-sh...

>some don't really seem to make sense.

This one stood out to me:

>Machine-scale infrastructure. [...] Git itself wasn't designed for that load, and bolting AI onto platforms not built for agents is the biggest mistake of this era. [...] Git itself is being reengineered for machine scale.

Git itself is so far down the list of bottlenecks that do or could hamper LLM-driven development, even projecting years into the future...

To be fair, any LLM project gets a lot of stupid tickets, by virtue of a) marketing to users who aren't really developers and b) bad developers being more likely to use LLMs. Both of these groups are more likely to write bogus or non-reproducible bug tickets, as well as feature requests that don't make any sense. My guess is 10% of those 10,000 open issues are actual bugs or sensible requests.

On the other hand, LLMs seem perfect for triage and finding duplicates, so it's still surprising that they've let it get this bad.

>the LLM constantly guesses arguments or dictionary formats wrong [...] it's better to avoid that whole class of runtime errors altogether.

Use Mypy in strict mode and run it in the post-turn hook of your LLM harness so the LLM has no choice but to obey it. And don't use overly general dictionary types when the keys are known at development time; use TypedDicts for annotations if you must use dicts at runtime.

LLM slop article. But as for the topic: To me, "Kanban with refinements and retrospectives" is the sweet spot. The concept of Sprint seems not only superfluous but to add unnecessary rigidity. But you do want everyone to understand the tickets, so refinements are useful, and you do want to try and improve "meta" issues where possible (and have the amount of effort going into that limited so you don't end up in the methodology equivalent of yak shave hell), so retrospectives are useful, too.

This sounds like it only changes the framing, but in reality it would lead to completely different behavior, so the "leave the gun alone" option would likely lead to far fewer deaths than the red button option, simply by virtue of organisms including humans being generally biased in favor of "do nothing" (= leave the gun alone).

You could do both experiments with dogs instead of humans and roughly 100% of dogs wouldn't manage to shoot themselves with the gun, whereas if you forced them to press one of the two buttons (e.g. keeping them in a room until they press one by chance), roughly 50% would press the red one. So the two experiments differ strongly w/r/t to how likely it is for a "non-thinking" organism to choose each option.

Made me stop reading a few paragraphs in. I don't have a "problem" in the ethical sense either, but as the sibling comment notes, the way LLMs write is rather grating. To make matters worse, a) people seem to use them to add pointless volume / "filler" to their texts, so now I have to wade through pages and pages of this stuff, and b) I have no easy way to distinguish between an article at least based on novel human insights vs entirely LLM-generated from a "write me something about X topic" prompt. I don't think it's a stretch to say that the latter just isn't worth reading given the state of the art.

What's the source of the claim that it was a Roblox cheat? Neither the report linked at the start of this article nor Context.ai's and Vercel's notices mention this.

>The technology is pushed forward by a simple psychological logic: every key global actor knows that if they don't build the technology, they will be outcompeted by other actors who do build the technology. No key actor thinks that they have the luxury of not building the technology even if they wanted to not build it.

I don't remember who, but someone made an interesting point about this around the time GPT-4 was released: If the major nuclear powers all understand this, doesn't that make nuclear war more likely the closer any of them get to AGI/ASI? After all, if the other side getting there first guarantees the complete and total defeat of one's own side, a leader may conclude that they don't have anything to lose anymore and launch a nuclear first strike. There are a few arguments for why this would be irrational (e.g. total defeat may, in expectation, be less bad than mutual genocide), but I think it's worth keeping in mind as a possibility.

Yudkowsky himself also posted a rebuttal today: https://x.com/ESYudkowsky/article/2043601524815716866

Exactly. This whole thing just seems like a repeat of Flappy Bird to me. What was the "lesson" of Flappy Bird for game developers? That you should make very small, very simple games? How has that worked out for the vast majority of copycats who tried? The truth is there isn't any lesson, other than "sometimes people play the lottery, get lucky and win". Most people who play won't, though.

And beyond the ethical points it makes (which I agree may or may not be relevant for LLMs - nobody can know for sure at this point), I find some of the details about how brain images are used in the story to have been very prescient of LLMs' uses and limitations.

E.g. it is mentioned that MMAcevedo performs better when told certain lies, predicting the "please help me write this, I have no fingers and can't do it myself" kinda system prompts people sometimes used in the GPT-4 days to squeeze a bit more performance out of the LLM.

The point about MMAcevedo's performance degrading the longer it has been booted up (due to exhaustion), mirroring LLMs getting "stupider" and making more mistakes the closer one gets to their context window limit.

And of course MMAcevedo's "base" model becoming less and less useful as the years go by and the world around it changes while it remains static, exactly analogous to LLMs being much worse at writing code that involves libraries which didn't yet exist when they were trained.

Was my first thought as well. I had no idea those little guys were based on something real.