If all you're saying is that neural networks could develop consciousness one day, sure, and nothing I said contradicts that. Our brains are neural networks, so it stands to reason they could do what our brains can do. But the technical hurdles are huge.

You need at least two things to get there:

1. Enough computing power to support it.
2. Insight into how consciousness is structured.

1 is hard because a single brain alone is about as powerful as a significant chunk of worldwide computing, the gulf between our current power and what we would need is about... 100% of what we would need. We are so woefully under resourced for that. You also need to solve how to power the computers without cooking the planet, which is not something we're even close to solving currently.

2 means that we can't just throw more power or training at the problem. Modern NN modules have an underlying theory that makes them work. They're essentially statistical curve-fitting machines. We don't currently have a good theoretical model that would allow us to structure the NN to create a consciousness. It's not even on the horizon yet.

Those are two enormous hurdles. I think saying modern NN design can create consciousness is like Jules Verne in 1867 saying we can get to the Moon with a cannon because of "what progress artillery science has made in the last few years".

Moon rockets are essentially artillery science in many ways, yes, but Jules Verne was still a century away in terms of supporting technologies, raw power, and essential insights into how to do it.

We're on the same page about consciousness then. My original comment only pointed out that current AI have problems that we have because they replicate how we work and it seems that people don't like recognising that very obvious fact that we have the exact problems that LLMs have. LLMs aren't rational because we inherently are not rational. That was the only point I was originally trying to make.

For AGI or UGI to exist, massive hurdles will need to be made, likely an entire restructuring of it. I think LLMs will continue to get smarter and likely exceed us but it will not be perfect without a massive rework.

Personally and this is pure speculation, I wouldn't be surprised if AGI or UGI is only possible with the help of a highly advanced AI. Similar to how microbiologist are only now starting to unravel protein synthesis with the help of AI. I think the shear volume of data that needs processing requires something like a highly evolved AI to understand, and that current technology is purely a stepping stone for something more.

LOL you didn't really make the point you thought you did. It isn't an "improper comparison" (it's called a false equivalency FYI), because there isn't a real distinction between information and this thing you just made up called "basic action on data", but anyway have it your way:

Your comment is still exactly like saying an audio pipeline isn't really playing music because it's actually just doing basic math.

Do LLMs not exhibit emergent behaviour? But who am I, a simple skin-bag of chemicals, to really say.

People that can not do Matrix multiplication do not possess the basic concepts of intelligence now? Or is software that can do matrix multiplication intelligent?

To write the second line, the model had to satisfy two constraints at the same time: the need to rhyme (with "grab it"), and the need to make sense (why did he grab the carrot?). Our guess was that Claude was writing word-by-word without much forethought until the end of the line, where it would make sure to pick a word that rhymes. We therefore expected to see a circuit with parallel paths, one for ensuring the final word made sense, and one for ensuring it rhymes.

Instead, we found that Claude plans ahead. Before starting the second line, it began "thinking" of potential on-topic words that would rhyme with "grab it". Then, with these plans in mind, it writes a line to end with the planned word.

actually read the research?

So close, LLMs work via matrix multiplication, which is well understood by many meat bags and matrix math can’t think. If a meat bag can’t do matrix math, that’s ok, because the meat bag doesn’t work via matrix multiplication. lol imagine forgetting how to do matrix multiplication and disappearing into a singularity or something

The environmental toll doesn’t have to be that bad. You can get decent results from single high-end gaming GPU.

I was channeling the Interstellar docking computer (“improper contact” in such a sassy voice)

There is a distinction between data and an action you perform on data (matrix maths, codec algorithm, etc.). It’s literally completely different.

An audio codec (not a pipeline) is just actually doing math - just like the workings of an LLM. There’s plenty of work to be done after the audio codec decodes the m4a to get to tunes in your ears. Same for an LLM, sandwiching those matrix multiplications that make the magic happen are layers that crunch the prompts and assemble the tokens you see it spit out.

LLMs can’t think, that’s just the fact of how they work. The problem is that AI companies are happy to describe them in terms that make you think they can think to sell their product! I literally cannot be wrong that LLMs cannot think or reason, there’s no room for debate, it’s settled long ago. AI companies will string the LLMs together and let them chew for a while to try make themselves catch when they’re dropping bullshit. It’s still not thinking and reasoning though. They can be useful tools, but LLMs are just tools not sentient or verging on sentient

There is a distinction between data and an action you perform on data (matrix maths, codec algorithm, etc.). It’s literally completely different.

Incorrect. You might want to take an information theory class before speaking on subjects like this.

I literally cannot be wrong that LLMs cannot think or reason, there’s no room for debate, it’s settled long ago.

Lmao yup totally, it's not like this type of research currently gets huge funding at universities and institutions or anything like that it's a dead research field because it's already "settled". (You're wrong 🤭)

LLMs are just tools not sentient or verging on sentient

Correct. No one claimed they are "sentient" (you actually mean "sapient", not "sentient", but it's fine because people commonly mix these terms up. Sentience is about the physical senses. If you can respond to stimuli from your environment, you're sentient, if you can "I think, therefore I am", you're sapient). And no, LLMs are not sapient either, and sapience has nothing to do with neural networks' ability to mathematically reason or use logic, you're just moving the goalpost. But at least you moved it far enough to be actually correct?

It’s wild, we’re just completely talking past each other at this point! I don’t think I’ve ever gotten to a point where I’m like “it’s blue” and someone’s like “it’s gold” so clearly. And like I know enough to know what I’m talking about and that I’m not wrong (unis are not getting tons of grants to see “if AI can think”, no one but fart sniffing AI bros would fund that (see OP’s requested source is from an AI company about their own model), research funding goes towards making useful things not if ChatGPT is really going through it like the rest of us), but you are very confident in yourself as well. Your mention of information theory leads me to believe you’ve got a degree in the computer science field. The basis of machine learning is not in computer science but in stats (math). So I won’t change my understanding based on your claims since I don’t think you deeply know the basis just the application. The focus on using the “right words” as a gotchya bolsters that vibe. I know you won’t change your thoughts based on my input, so we’re at the age-old internet stalemate! Anyway, just wanted you to know why I decided not to entertain what you’ve been saying - I’m sure I’m in the same boat from your perspective