It's like the infinite monkeys on typewrighters that will type whatever you are looking for, given infinite time. LLMs are just tuned to much better odds than the monkeys are. But it's still a lot of randomness, with random results.
In the monkey example the infinite time is doing a lot of work there. The fact that LLMs can search through semantic space and find reasonably correct paths in a reasonable time is directly tied to the reason why they are valuable.
Saying "these two things are similar except one can be useful and one can't" is not a great comparison.
For me the real lesson learned isn't how "smart" LLMs are, but rather how much human work is basically reducible to repeating past work with minor variation. Human's believe they are "reasoning" but so much code writen is just the human brain doing the same autocomplete style work that LLMs can do now.
This seems like a reasonable view to me. It's surprising just how much better priors matter and how we can develop those priors by training on a bunch of text. But it also explains, or at least hints at an explanation, for why LLM capabilities are so jagged, and in such inhuman ways.
Except it’s not at all the same process. The fact that LLM are non deterministic is not the same as churning out random garbage.
It’s training monkeys at typewriters through reinforcement.
So not random.
> acceptable outcome to humans
And not garbage.
It’s real weird to see people argue that LLM output is no different than random gibberish and then handwave over the fact that it’s clearly not with terms like “training”, as if a steam of random garbage is trainable.
I quite literally created and productized predictive linguistics and behavioral vectors at Google.
If you had stopped to consider what I explained; you’d understand that it’s the process of turning random garbage into increasingly acceptable outputs.
Ie training the monkeys.
The insight you are missing is the rule of networked scale. It turns out that any reactive node scaled enough can form sophisticated predictive system given reward over a training topography, even if it starts out at garbage or is literally made of monkeys.
So it is garbage. And you can turn garbage into semi-intelligence.
The act of successful training means it’s not garbage anymore.
> So it is garbage.
This statement is ultimately meaningless and I continue to find it weird that someone who works in this space would support this view. If you fundamentally change the nature of a thing, it’s no longer that original thing. Is tan HDD still random garbage after you fill it with family photos just because that’s how it starts?
You can start with garbage.
This is not human. Humans are billions of years in passed DNA learning. Babies are born to a sophistication level millions of times higher than this.
I’m pretty surprised you don’t know this.
I don’t believe that you can’t understand the distinction between “at one point this was garbage” and “at the present time this is still garbage”. You’re clearly smarter than that.
That's the part they are really good at. But they are really bad at taking complex decisions. Most of them are just guesses from a finite amount of solutions they were trained on, or from options they have in context.
And nothing about this makes your initial comment any less goofy. Anyone who has ever had to make a difficult decision knows more than half the battle is preparation. Where do you think complex decisions come from? Have current events left you with the impression that people just waltz into idk say the Situation Room and just big brain their way through world events? That's how the current administration seems to think the world works, with quite predictable results.
Society is already algorithmic. To optimize for humans being dumb. AI is nothing more than another advance along this continuum. No one is impressed by your ability to remember something years ago, many if not most mammals have the same capability. Human recall is also notoriously bad in many cases - see numerous studies on the reliability of eye witnesses testimony.
AI is smart because most people are dumb. Come to terms with the fact that your anthropocentrism need not be based on a notion of intellectual supremacy and you'll be a far less tedious person to deal with.
Launching a nuclear war is an interesting definition of "useful", not one I'd agree with and that exact scenario is what is being discussed.
So yes this is a perfectly valid and useful comparison in examining this particular, civilisation ending limitation.
You do have to successfully write something the first time
We already acknowledge this to a degree, what is experience other than having done something similar before?
That first time though, you've got to figure something out that time
So I can’t fully see how that’s related to the infinite monkeys. A typewriting monkey doesn’t have access to a verification function. And even if it did, it would not be the original concept anymore with infinite typewriting monkeys producing the works of Shakespeare.
Nevertheless, I upvoted your comment because it’s definitely insightful.
Agent reads a skill file about how to use a CLI tool. It tries to use the tool but gets an error about the input format. It tries again with a different format based on the error message, and sees that command succeeded. It compares what worked to what was in the skill file and notes the difference. On future invocations it continues to use the new format.
Is that not "understanding" how to use the tool?
They train on a billion "jobs". Which is not terribly efficient but oh man they do train.
This fact is currently the most limiting factor for LLMs.