The words 'lead to' there cover a lot. I don't think we'll get AGI just by giving more compute to the models but modifying the algorithms could cover a lot of things.

Like at the moment I think during training new data changes all the model weights which is very compute intensive and makes it hard to learn new things after training. The human brain seems to do it in a more compartmentalised way - learning about a new animal say does not rewrite the neurons for playing chess or speaking French for example. You could maybe modify the LLM algo along those lines without throwing it away entirely.

The need for new data seems like it has outpaced the rate at which real data is being generated. And most of the new data is llm slop.

So you might improve algorithms (by doing matrix multiplications in a different order.... it's always matrix multiplications) but you'll be feeding them junk.

So they need ever increasing amounts of data but they are also the cause of the ever increasing shortage of good data. They have dug their own grave.

...Why?

Because always/never are absolutes that are either very easy or very hard to see through. For example, 'I will never die', 'I will never tell a lie', 'I will never eat a pie' all suffer through this despite dying being the most implausible. And it gets worse as we get most abstract:

'Machine will always know where to go from here on now'.

AGI might be possible with more Param+Data scaling for LLM. It is not completely within the realm of impossible given that there is no proof yet of "limits" of LLM. Current limitation is definitely on the hardware side.

This is what I'm talking about. The correct tech would enable the strands of information in a vector to "see" each other and "talk" to each other without any intervention. This isn't the same as using a shovel to bash someone's head in. AGI would need tech that finds a previously undocumented solution to a problem by relating many things together, making a hypothesis, testing it, proving it, then acting on it. LLM tech will never do this. Something else might. Maybe someone will invent Asimov's positronic brain.

I think _maybe_ quantum computing might be the tech that moves AGI closer. But I'm 99.9999% certain it won't be LLM tech. (Even I can't seriously say 100% for most things, though I am 100% certain a monkey will not fly out of my butt today)

Quantum compute would definite make a leap to moving closer to AGI. Calculating probability vector is very natural for quantum computer or more precisely any analog compute system would do. qubits==size(vocab) with some acceptable precision would work i believe.

LMAO! That Bruce Almighty reference had me rolling. Good one.

The processing capability of today’s CPU’s and GPU’s is insane. From handheld devices to data centers, the capability to manipulate absurd amounts of data in fractions of a second is everywhere.

It’s not the hardware, it’s the algorithms.

Maybe it is the algorithms. But just by doing a op for an 10^25 param llm is definitely not feasible on todays hardware. Emergent properties does happen at high density. Emergent properties might even look as AGI.