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This is not as black and white as you portray it to be.

Humans are inherently irrational, but that doesn't mean they can't make good decisions as a group [0].

But we can also be convinced to not trust our own eyes, at least in the short term.

[0]The Wisdom of Crowds by James Surowiecki (2004) is a great book covering this idea.

I wholeheartedly agree with this.

Engineering normally requires thinking long term and if you want to use LLMs it needs to be way more structured. For this use-case LLMs are on way more shaky ground.

No.. Like my barbers new website is great and he used AI for it.

Or like the internal tool I whipped up in a few days to try out how we can structure some specific data we have internally in our company.

Yes that's true - for a lot of use cases I don't care about software quality.

When pouring concrete, I'm not going to use expensive hardwood to frame the concrete base, I'm gonna use stuff that's just strong enough. It's going down the bin anyway.

A lot of internal tools are fine if they are just good enough, they don't really need to be that maintainable if 2 people are gonna use it every once in a while

This is just not true. LLMs are good at some development.

You may caveat what type of software you are talking about, like complex or out-of-the-ordinary, and say that llms are still bad at that. Fine. But LLMs are actively being used for developing thousands of websites all the time - you can see several examples of them on hackernews every week.

Amount of lines is irrelevant when talking about a landing page or a huge number of internal tools that people are building at the moment. At least until a certain point.

Child baking machine still human job, chip baking is harder

Soccer is not just physical - it's also team work, strategy, diet, tenacity, etc. A lot of those skills can be learned from almost any activity, including building lego sets online.

The best soccer players are incredibly intelligent and fast thinking.

That's true. However it does sometimes feel like our culture is being buried in slop.

I could do plenty of small bad things all the time and gain something small from it - yet I don't. I drive the speed limit when no one is around, I throw thrash in the right bag, I try to keep my general pollution levels at a reasonable place, etc.

I have plenty to gain from not following the rules, but I would not feel good about myself.

There is no language in the training of this, so there is no l.

Then nothing - that's awesome. People think that LLMs are the know-all do-all solution to every problem now.

Putting solutions in terms of cents is a great way to potentially win over some ai boosters imo. There are other ways to solve hard problems.

I read this as a response to the current hype around LLMs. He is showing computers can solve these issues, without using an LLM architecture. A lot of people have sort of forgot that machine learning is more than just LLMs these days.

I found it to be a very interesting angle.

Translating a client question to an actual technical question is the hard part I guess. Google-fu is still a thing, and absolutely a thing you were/are getting paid for it seems.

Bless the lord that it's not been presented to us yet, because you just know that it exists already.

A lot of reasons.

I think illegally using natural gas generators to power his datacenters in residential areas, is pretty high on that list.

We should also normalize paying for content at the same time then.

I think that was his argument as well. It looks like there is no more data to find, but then it becomes important to find more data - lo and behold we can make more.

Sounds like the oil scare from 90' - we thought we were gonna run out of oil. But as oil gets more expensive it pays to dig further down to find the stuff that didn't make sense to dig up before.

Did you get older over the last few years? That might make a difference.

Thanks for sharing - is this a normal feature request you are implementing in this example or is this a project from scratch? Trying to get an idea of how your workflow compares to mine.

I don't think I take LLMs for granted - but I've misclassified them as something else.

The reason why it's so cool now, is because we can run good models on our own machines now. That's really what makes it a hackable technology in my head. Calling an API is just another product.. Does that make sense to you?