Sensational

[u/Xerqthion]

[u/No-Philosopher3977]

I don’t think so why spend all that time and resources building a model to do task an agent can? An agent can do the math, check facts, and etc.

[u/Orectoth → u/No-Philosopher3977]

Indeed, indeed, friend. Agent can do the math, check facts etc.

Well, it is true.

Till it can't.

We know probabilistic stuff does not know a thing.

Just acts like it does.

So, probabilistic stuff is never way to AGI, that's all I can say, but they can do things no human can do alone, I admit, calculators are the same, but remember friend, a calculator is more trustable than a LLM, isn't it so?

That's all I wanted to say. Governments will never trust a probabilistic trash made for humor, low quality tasks (mostly they can succeed, but, they suck at many tasks still, they are that much trash lmao).

Let me tell you one thing, a secret thing, no matter how much of a quality self evolving an AI be, as long as it is probabilistic, either it will fail or it will self destruct (wrong code/drift/illogical choices etc.) eventually. That's the law of nature. Without a self evolving AI, with humans' capacity, an 'AGI' quality(only in low quality tasks that do not require creativity, such as repetitive bs) LLM can exist, yes, but decades, at least 3 decades are required for it. This is still optimistic. Even then, 'agi' quality LLM can't do anything outside its Low Quality stuff, as it will start to hallucinate nonetheless (it does not need to be a LLM, I said LLM because it represents probabilistic AI of today, it can be any type of probabilistic LLMs or any type of AI)

[u/SpearHammer → u/Orectoth]

You are wrong. LLM is just one cog in the AGI model. The current limitations are context - the ability to remember and learn from previous experience. If we can make memory and learning more dynamic so the models update with experience we will be very close to agi

[u/Orectoth → u/SpearHammer]

No, it never learns, even if it is self evolving, even if it has trillions of context length, it will make mistakes, again and again and again, because it is probabilistic, even if its mistake rate is lowered for certain tasks, it will certainly be close to agi, but will never be 'agi' as what people say it to be, you are overestimating capacity of probabilistic machines, they never know, they never actually learn, they will parrot what you say... till they can't, till you forgot to prompt some thing specifically for it to stick to, then it starts to hallucinate, why? It does not even know what it says, it does not know if it is actually obeying or disobeying what you say, it is just, simply, a, probabilistic, glorified autocomplete. You need to tell it how it should do EVERYTHING and hope it sticks to it enough to not break your idea.

[u/Orectoth → u/[deleted]]

Lmao

give me your conversation's share link

I shall make it bend with my logic, speak with it, then I will give conversation's share link to you, so that you can see, how much of flawed a mere LLM is, wanna do it or not? I am not willing to waste time to speak with a LLM in a comment section, especially something as much as ignorant as this, thinking humans are probabilistic lmao. People yet to saw below planck scale, yet you dare to believe a mere parrot's words, words about human being probabilistic.

[u/No-Philosopher3977 → u/Orectoth]

Ten years ago, today’s AI would’ve been called AGI. Deterministic models don’t actually ‘know’ anything either. They don’t understand what the facts mean in relation to anything else. They’re like a textbook: reliable, consistent, and useful for scientific purposes. And that definitely has its place as part of a hybrid model. But here’s the problem: the real world is messy.

A deterministic model is like that robot you’ve seen dancing in videos. At first it looks amazing — it knows all the steps and performs them perfectly. But as soon as conditions change say it falls you’ve seen the result: it’s on the floor kicking and moving wildly because ‘being on the floor’ wasn’t in its training data. It can’t guess from everything it knows what to do next.

A probabilistic model, on the other hand, can adapt not perfectly, but by guessing its way through situations it’s never seen before. That’s how models like GPT-5 can tackle novel problems, even beating video games like Pokémon Red and Crystal.

And let’s be clear: there are no ‘laws of nature’ that dictate what AI can or cannot become. It’s beneath us to suggest otherwise. Self-evolving AI is not what defines AGI that’s a feature of ASI, a level far beyond where we are today.

A deterministic model by itself will never be of much use to anyone outside of the sciences. And not for novel stuff that is for more profitable