For example, you need to know it uses gasoline (or diesel), it requires oil changes every certain amount of time, break pad replacement, etc.

You also probably need to know that you can't operate cars over a certain amount of water, that you need a driver's license, stopping at red lights, etc.

Sure, you might not need to be a mechanic, but that's far from not understanding how a car works, which to me sounds similar to knowing how to shoe a horse, which is different than being a horse vet.

At first, the ocean seems immense. So much so that dumping plastic and toxic chemicals makes no difference.

But then we humans are great at scaling things it seems, such that at some point ocean plastic pollution became a real problem.

I know that space is much much bigger than our oceans, but I wouldn't underestimate the ability of mankind to scale launches to the point where debris becomes a problem.

It's the only prod usage of Macaroons I know of, I think.

Third-party discharge seems like a great way to have human-in-the-loop gating, among other interesting things.

Would be great reading your thoughts if you ever write about the agentic use case, having all the fly.io experience

If I need a roundtrip to the auth server to attenuate, I am not necessarily going to do it as often.

It seems they were not of very much use in the past, but with the agentic-everything now, I see this as a great way of delegating permissions to subagents, third-party agents, etc.

Working on something along these lines but unfortunately I cannot dedicate as much time as I'd like.

Still, if anyone is reading, give Macaroons a try!

I used to do this kind of things decades ago, but there was also still a few things not ripped and uploaded you had _some_ chance of participating.

Nowadays I imagine ~everything under the sun is already ripped, so how can you contribute to seed ratio? (or is that not even a thing anymore?)

"Hello, world! Welcome to the classic programming greeting. It is the traditional test message used to introduce beginners to computer science and verify that a language's syntax is properly understood"

Which clearly shows that there will be an avalanche of issues when non-technical people discover the joys of non-deterministic results.

All the responsibility is still yours though.

Very seldomly does middle/upper management truly listens to engineers, unless there's buy-in from the CTO/VP to champion the ideas and complaints.

However I've discovered wonderful gems like this RAM video.

Indistinguishable From Magic: Manufacturing Modern Computer Chips

https://www.youtube.com/watch?v=NGFhc8R_uO4&t=2070s

It's quite old but I think there is no modern version of it.

I've tried posting to HN a few times but it hasn't gained traction for some reason, but I find it absolutely mind blowing.

I guess it's "good" to know that I'm not alone.

The amount of times I've searched for a ticket that I know it's there (because I either have it opened in a different tab, or because I just created it), but can't find, it's just way to many.

Comments URL: https://news.ycombinator.com/item?id=47591367

Points: 48

# Comments: 5

Personally, I've used LLMs to debug hard-to-track code issues and AWS issues among other things.

Regardless of whether that was done via next-token prediction or not, it definitely looked like AGI, or at least very close to it.

Is it infallible? Not by a long shot. I always have to double-check everything, but at least it gave me solid starting points to figure out said issues.

It would've taken me probably weeks to find out without LLMd instead of the 1 or 2 hours it did.

In that context, I have a hard time thinking how would a "real" AGI system look like, that it's not the current one.

Not saying current LLMs are unequivocally AGI, but they are darn close for sure IMO.

I mean ideally a proper SOC2 would mean there are processes in place to reduce the likelihood of this happening, and then also processes to recover from if it did ended up happening.

But the end result could've been essentially the same.