Oh wow, is that what you got from this?

It seems more like a non experienced guy asked the LLM to implement something and the LLM just output what and experienced guy did before, and it even gave him the credit

Copyright notices and signatures in generative AI output are generally a result of the expectation created by the training data that such things exist, and are generally unrelated to how much the output corresponds to any particular piece of training data, and especially to who exactly produced that work.

(It is, of course, exceptionally lazy to leave such things in if you are using the LLM to assist you with a task, and can cause problems of false attribution. Especially in this case where it seems to have just picked a name of one of the maintainers of the project)

Did you take a look at the code? Given your response I figure you did not because if you did you would see that the code was _not_ cloned but genuinely compiled by the LLM.

> then you're doing the opposite of what the author proposes

No, it’s exactly what the author is writing about. Just check his example, it’s pretty clear what he means by “thinking in math”

> Scientific conensus in math is Occam's Razor, or the principle of parsimony. In algebra, topology, logic and many other domains, this means that rather than having many computational steps (or a "simple mental model") to arrive to an answer, you introduce a concept that captures a class of problems and use that.

I don’t even know what you mean by this.

I really want to get into ocaml but the syntax is sooo ugly I feel like you need a great IDE set up to be able to be productive with it.

Might want to check out ReasonML.

> In this article, being "functional" is just serving as a proxy for code quality.

It is not, it is being very specific about what it means and what it is referring to

> It doesn’t really matter why it’s not working.

It does, because it changes the strategy.

If you think the ads are working and have 10k potential customers then you start thinking about how to increase your conversion rate thinking you could get a chunk of those 10k, you might think distribution is solved.

But if it turns out only 2.5k are real humans then your conversion rate might not even be an issue and it’s just the marketing strategy that needs tweaking.

The whole point is that they are giving you fraudulent traffic which you use as real data to figure out the next steps. If you don’t know it’s fraudulent or how much of the clicks are fraudulent then you are taking decisions under the wrong assumptions.

> You can’t stop fraudulent clicks just like you can’t stop your SuperBowl ad from playing while your viewers are in the bathroom

That’s not even a good analogy, we are taking clicks, not impressions.

That’s the point, without the fraudulent clicks you would just move on to some other strategy because the pricing would not be worth it.

Fake clicks give the illusion that ads are working and instead you have to optimize your funnel or whatever else.

> Does it cease to be a good metric?

Yes if you run anything other than the 100m

Would we live with the same standards today if we had never printed any money?

arguably we would have better standards because it would mean less spent on wars, which are pure destruction of value

Value “creation” and money supply have nothing to do with each other.

Earlier today I was scrolling at the “work at a startup” posts.

Seems like everyone is doing LLM stuff. We are back at the “uber for X” but now it is “ChatGPT for X”. I get it, but I’ve never felt more uninspired looking at what yc startups are working on today. For the first time they all feel incredibly generic

Finally we've managed to disintermediate everything. Even the cutting out of middlemen can now be automated.

A machine stamping out cookiecutter saas businesses. Business model: Uber for "Uber for x".

Who wants to start a goat farming co-op?

That's an old trend in AI time. The new trend is "Cursor for X". YC is all over that.