BobbyJo

How so? Space has no locals, and the sun never sets up there.

This describes Intel perfectly circa 2010

I disagree with basically all of your suppositions here.

What data are you referring to?

Immigration is a temporary fix. Seems they aren't willing to completely change their countries racial and cultural demographics to put a bandaid on a change in how the world works.

> Ah yes. "all the magic the people say work 100% of the time"

I don't see how this rebutts the implication.

> This again assumes that people working on high stakes projects only work on one single project.

No it doesn't. It's a very straightforward yes or no question.

> This again assumes that people finding issues with LLM-generated code have not tried every magic recipe under the sun from people claiming their hair growth elixir is 100% a working solution.

He's just describing very common failure modes that come from a lack of structure/linting.

You're framing things like this is some grand conspiracy. OP is literally describing flat tires and your rebuttal is "these magical round tires i keep hearing about." It's very strange.

LLMs will dedupe code if you give them structures to find the duplication. It's not magic. I do it every day.

I think it's a good assumption. Their comment implies they aren't harnessing the coding agent very strongly given the failure modes they mention.

Do you think it's better to experiment with high stakes projects? Do you think it'll be easier to avoid defaulting to line by line auditing of a project that is high stakes?

I think the intended takeaway is to learn to solve those problems without line by line review. Start by being hands off on a low stakes project, and see how the model fails. Then, come up with, and try, solutions that aren't you doing archeology.

> Throughout history and throughout cultures there's a universal: children, adults, and the elderly all like to feel like they have some kind of purpose in their community.

There is a sample bias there where the people who are recorded are the kinds of people who feel that way, and the people who don't feel that way are lost to time.

> I think you gravely underestimate how important this is, and how bored and dismal life would be if you didn't have some kind of purpose in your community.

I'm speaking from experience. I have a large family of low achievers I grew up with, and not one of them has ever voiced a concern about purpose, only annoyance with effort. I think this worrying about our place in the universe and where we fit in and "what am I living my life for" is only a concern for a narrow piece of the population, and it happens to be the same slice that talks a lot online.

Most people only worry about their skills and place in the world relative to their ability to survive comfortably. They will happily spend their days idle, going to church, playing games, exercising, whatever, and really only experience any degree of existential dread as it relates to their own impending mortality.

South Park really spread "ginger" as the term in the US. Since that episode, everyone I know uses ginger instead of redhead, whereas I only learned the word ginger from that episode.

The vast majority of people just want to hang out with other people and do whatever they want IME. It is a small and useful fraction of the population that worries about purpose and needs productive work to get it.

I look forward to the world where my skills are irrelevant. That is a beautiful world IMO.

An industry being able to deliver the same value to society with less human capital isn't a "downfall." It sucks for the people who used to be able to extract lots of value for themselves, but for society and the industry, it's a plus.

I think you're making a mistake in thinking the digital world is the only one reachable to AI. Robotics and sensing would be opened up by a sufficiently capable AI.

It's a matter of bandwidth. The more I can offload onto the model, the more I can accomplish. For example, I had to do a lot of security work over the last 2 weeks to get ready for an event. This requires handholding current models on many fronts, like: 1) Do they actually implement the security fixes correctly. 2) Do their fixes create any new edge cases. 3) Do their fixes compromise existing interfaces or API surfaces.

I cannot trust current models to find all the necessary context, or to make what I consider to be good trade offs. A much more capable model would be able to see my existing patterns (or at least not have context rot make them blind to my convention docs) and make trade offs I agree with much more consistently, and I'd be able to do more with my time.

I've actually found models to be pretty poor at driving things I don't know well, so I generally don't do that unless its general design/product exploration and the end product code is throw-away.