laterium

Industrial machines don't fail like humans yet they replaced human workers. Cars don't fail like horses yet they replaced them. ATMs don't fail like bank tellers... Why is this such a big requirement?

Basic building blocks are atoms. So, yes same. If you mean cells vs transistors, sure they're different. But we don't have to demonstrate anything to know that nature already made conscious intelligent AGI without it itself not understanding anything. Therefore AGI can be created without knowing what consciousness is. It happened at least once.

Why would it have to be a 1 to 1 replication? Isn't that a strawman argument? NNs can basically store the collective of knowledge of humanity in that miniscule amount of neurons. NNs also run at much much higher frequency than human brains. Does that make human brains inferior and not worthy of being called aware by the same line of argumentation? Why do these differences even matter? I can imagine a vastly different form of awareness than humans just fine. They can both be aware and not that similar.

What makes you think you can understand the subjective experience of LLMs then? It's out of reach of science, so the only way is to ask them? How can you be sure they don't have subjective experience? Remember that you forbade yourself from using science to answer it.

Also, if subjective experience has any effect on the material world, then we can measure it and test it, putting it in reach of science. If it doesn't, why does it even matter in this discussion? By definition it has no relation to the AGI discussion since that's an empirical matter.

Because LLMs don't have this special quality that you call "awareness", then they cannot have "cognition", neither of which you defined? This is along the lines of "There must be something special with my mind that LLMs don't have, I can just feel it" special pleading whether you call it awareness, consciousness, qualia etc.

As long as you cannot define it clearly or even show that you yourself have this quality, I think the burden of proof is on you to show why this has any real world implications rather than just being word play. We can build thinking, reasoning machines just fine without waiting for philosophers to finally answer what consciousness is.

that's half of a comment

Alphafold and protein folding.

Transformers do just fine on many deterministic tasks, and are not necessarily probabilistic. This is not the issue at all. So, it's hard for everyone else because they're not confidently wrong like you are.

How much compute does simulating the earth for 4.7 billion years at atomic precision take? Why would that be more efficient than current approaches? Evolutionary algorithms work but are extremely inefficient, we don't have the compute to evolve even a single bacteria, let alone the whole history of the planet so we can arrive at human-like species.

Why is retraining not allowed in this scenario? Yes, the model will know the breakthrough if you retrain. If you force the weights to stay static by fiat, then sure it's harder for them to learn, and will need go learn in-context or whatever. But that's true for you as well. If your brain is not allowed to update any connections I'm not sure how much you can learn either.

The reason that the models don't learn continuously is because it's currently prohibitively expensive. Imagine OpenAI retraining a model each time one of its 800m users sends a message. That'd make it aware instantly of every new development in the world or your life without any context engineering. There's a research gap here too but that'll be fixed with time and money.

But it's not a fundamental limitation of transformers as you make it out to be. To me it's just that things take time. The exact same architecture will be continuously learning in 2-3 years, and all the "This is the wrong path" people will need to shift goalposts. Note that I didn't argue for AGI, just that this isn't a fundamental limitiation.

It already IS ubiquitous. What is the path to non-ubiquity then? Most people are depending on it in many personal contexts. A lot of people are even using it in their jobs whether others agree with it or not. Everyday it's becoming more ubiquitous than before.

Smart phones are this way for example. You may see them as just tools, but we became centaurs with our phones. I don't think being a "tool" precludes it from being a centaur or ubiquitous. I agree with you on some points, but I don't think the distinction you're making is valid here.

It's not better as demonstrated by the revealed preferences of a vast majority of the users. People DO want algorithmic feeds and NOT chronological feeds. It's a common narrative here that everyone wants chronological feeds, but it's not true just like the claim "Everyone wants small phones". People say one thing and do another.

The real cost will matter at least from an allocation perspective. You can't keep relying on a treatment that costs $100m even if the patient pays nothing. Someone needs to pay that cost.

How do you learn how and when to use AI if you never use it? Just wait another decade to see what others do? Like Kodak and digital photography?

Why is the hope that value is proportional to wage being removed and not increased productivity? The problem with this thinking is it already assumes an AGI/ASI replacing all work, rather than a force multiplier like with industrialization, electricity, and computing. AI being touted as the "final solution" doesn't mean anything if AGI is not right around the corner, and it isn't.

If AI is so successful that it can replace even 10% of current work that will be reflected in higher GDP and worker producitivity in the economy. Everyone has this cynical assumption that all benefits will go to the rich, but it hasn't been that way with the previous revolutions either, has it? Did cars only benefit the rich? Trains, radio, television, computers? Initially, that always seems like the case. Who could buy computers in the 80s? But the technology diffuses into the whole economy over time.

As a follow-up, how would this workflow feel if the LLM generation were instantenous or cost nothing? What would the new bottleneck be? Running the tests? Network speed? The human reviewer?

Not what I said at all. Question it all what you want. But disproving outrageous CEO claims doesn't get you there. Whether LLMs are AGI/ASI that will replace everyone is seperate from whether they are useful today as tools. Attacking the first claim doesn't mean much for the second claim, which is the more interesting one.

It's a new technology which lends itself well to outrageous claims and marketing, but the analogy stands. The CEOs don't get to define the narrative or stand as strawman targets for anti-AI folks to dunk on, sorry. Elon has been repeating "self driving next year" for a decade+ at this point, that doesn't make what Waymo did unimpressive. This level of cynicism is unwarranted is what I'm saying.

They are lying, because their salary depends on them lying about it. Why does it even matter what they're saying? Why don't we listen to scientists, researchers, practicioners and the real users of the technology and stop repeating what the CEOs are saying?

The things they're saying are technically correct, the best kind of correct. The models beat human PhDs on certain benchmarks of knowledge and reasoning. They may write 70% of the easiest code in some specific scenario. It doesn't matter. They're useful tools that can make you slightly more productive. That's it.

When you see on tv that 9 out of 10 dentists recommend a toothpaste what do you do? Do you claim that brushing your teeth is a useless hype that's being pushed by big-tooth because they're exaggerating or misrepresenting what that means?

Why is the bar for it to do your job or completely replace you? It's a tool. If it makes you 5% better at your job, then great. There's a recent study showing it has 15-20% productivity benefits: not completely useless, not 10x. I hope we can have nuance in the conversation.