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Comment by Marha01 | Hacker News Reader

> So how exactly is Anthropic and OpenAI ever going to pay back the trillions that they plan on spending?

It's really simple: if they truly get to human-level AI (or even superhuman AI), then money and debts no longer matter, since our current economic system will be obsolete. They are betting everything on this outcome.

I don't know if they will manage to do it before their debts have to be repaid, but considering the rate of acceleration in the past few months, there is a non-trivial chance that they will, IMHO. We will see.

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That’s like building F1 cars and thinking you will soon have a rocket to land on the moon.

LLM has nothing to do with AGI.

I would perhaps agree with you just a year ago. But now I am not so sure. It is clear that scaling up Transformers still leads to significant improvements, and they are now solving math conjectures and finding real vulnerabilites in software. We don't really know where the capability ceiling of the current approach is, and anyone telling you that we know it is lying to you.

> We don't really know where the capability ceiling of the current approach is

We do know, that the ceiling is below AGI. And it's not a matter of opinion - LLMs can not achieve AGI due to their design. Anyone telling you otherwise is lying to you.

And it doesn't matter how many or how severe bugs they can find, because it's not about what they produce, but how they produce it.

> We do know, that the ceiling is below AGI. And it's not a matter of opinion - LLMs can not achieve AGI due to their design.

[citation definitely needed]

> And it doesn't matter how many or how severe bugs they can find, because it's not about what they produce, but how they produce it.

AGI is defined by the practical outcomes, not by the way the outcomes are achieved. You have no way to know that scaled-up Transformers predicting the next token will never result in human-level intelligence, since we currently have no idea where the ceiling of that approach is.

> [citation definitely needed]

If you're not even familiar with how LLMs work, perhaps you should restrain yourself from confidently talking about this topic until you educate yourself. You're only spreading misinformation.

> AGI is defined by the practical outcomes, not by the way the outcomes are achieved

That for sure would be a very convenient definition, especially for all those AI labs trying to convince investors that they achieved AGI. Unfortunately everyone knows, that knowing the right answer isn't the same as knowing where that answer came from.

> If you're not even familiar with how LLMs work, perhaps you should restrain yourself from confidently talking about this topic until you educate yourself. You're only spreading misinformation.

I am very familiar with how LLMs work, and I am telling you that there is no consensus that they cannot achieve AGI in the machine learning community. Some people think so (such as Yann LeCun), others disagree. We just don't know yet.

> That for sure would be a very convenient definition, especially for all those AI labs trying to convince investors that they achieved AGI. Unfortunately everyone knows, that knowing the right answer isn't the same as knowing where that answer came from.

AGI is defined by capabilities, not methods.

That's assuming that human-level AI is a possibility with current approaches.

No, it's assuming there's a non-trivial chance that they will.

I'd assume we want at least human-level intelligence, but better than human-level _decision making_. ;)

No need even for "human-level" per se. It just has to be useful enough that it upends the current economic order, which it's already well on the way into doing.

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