Comment by gerdesj
15 hours ago
No idea why you were dv'd.
It still takes roughly nine months to make a human baby, regardless of how many women or babies are involved!
15 hours ago
No idea why you were dv'd.
It still takes roughly nine months to make a human baby, regardless of how many women or babies are involved!
9 pregnant women produce one baby/month on average (assuming no miscarriages or late births,etc).
On paper your CPU can execute at least one instruction per core per cycle but that's on average too, if you actually only have one instruction to run it takes several cycles.
But the context is to throw 9 women at the problem of having no conception and the hope to get a baby within a month.
You're assuming all women in your cohort start not pregnant. However, given a random sampling of women across the entire human race, if you have approximately 14,000 women, statistics says you'll have a baby in a month. That is to say, the chances of one of those woman being 8 months pregnant reaches close enough to 1, given about 14,000 randomly selected women.
Also, you can get a baby tonight if you steal one from the maternity ward.
The real question is, how do LLMs turn the mythical man month on its head. If we accept AI generated code, can an agentic AI swarm make software faster simply by parallelizing in a way that 9 women can't make a baby in 1 month because they're am AI, not human, and communicate in a different way.
The pitfall of AI coding is that previously every shiny tangent that was a distraction, is now a rabbit hole to be leaped into for an afternoon, if you feel like it. It's like that ancient Chinese curse, may you live in interesting times. Everybody can recreate an MVP of Twitter in a weekend now when previously that was just a claim a certain type of people made.
I just looked up "may you live in interesting times" and learned that it is not, in fact, originally Chinese. Per wikipedia:
> The nearest related Chinese expression translates as "Better to be a dog in times of tranquility than a human in times of chaos."
https://en.wikipedia.org/wiki/May_you_live_in_interesting_ti...
> You're assuming all women in your cohort start not pregnant. However, given a random sampling of women across the entire human race, if you have approximately 14,000 women, statistics says you'll have a baby in a month. That is to say, the chances of one of those woman being 8 months pregnant reaches close enough to 1, given about 14,000 randomly selected women.
There's a good point in here along the lines of "if you need X in a month, and someone else has something that's 90% of what you want X to be, can you buy it from them before starting any crazy internal death marches instead?"
> The real question is, how do LLMs turn the mythical man month on its head. If we accept AI generated code, can an agentic AI swarm make software faster simply by parallelizing in a way that 9 women can't make a baby in 1 month because they're am AI, not human, and communicate in a different way.
This is quite possibly only a one-time switch from a changed baseline, though. Give it a few years and "the fastest way an LLM tool can do it" will be what gets tossed out a an estimate, and stakeholders will still want you to do it in a tenth the time...
that's still one woman per pregnancy, it's not 14k women collaborating on a single pregnancy.
> You're assuming all women in your cohort start not pregnant
As far as I know, all women everywhere start not pregnant
Tribbles, on the other hand...
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Sometimes HN doesn't like jokes, which is okay. I didn't really contribute much to discussion, so I probably deserve some downvotes. I'm ok with it.
Actually, I like quite a lot of the subtle jokes on HN. It is harder to notice, fewer to find, and I don’t get it many a times. But when I get it (or someone explains it to me, perhaps out of pity), I chuckle, laugh, and laugh again. And I remember those comments.
I think the occasional joke is fine but when you have too many then the comments get diluted. It's exactly that kind of thing that makes me hate Reddit and so many other places: spam.