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What we call AI today isn’t really artificial intelligence. When you have a conversation with an AI chat bot you’re not talking to another thinking entity, you’re interacting with software that has been designed to give the illusion of conversing with another intelligent being. The technology has advanced enough that the illusion can be very convincing, but it is still only an illusion. That’s why I don’t fear LLMs being self aware and taking over the world, because they’re not real intelligences. They don’t have the ability to think for themselves because they don’t have the ability to think.
Edit: please read ricecake’s reply for an important correction to my comment.
Your conclusion is correct, but your terminology is wrong.
What we call AI today is AI, because AI doesn’t mean “capable of thought”, consciousness, sapience or anything like that.
It’s capable of producing a coherent output adapted to observed circumstances. That’s roughly as far as the notion of intelligence goes, and it’s a very low bar. You don’t need a lot of intelligence to be intelligent.The people who coined the term were interested in how you make computers react to their inputs dynamically instead of acting closer to what we might now think of as a saved macro.
“It’s intelligent because rather than comparing against a list of every known typo, it sees it’s not a word in its list, and then replaces it with the one requiring the fewest edits to reach. It learns by adding your corrections to the known word list.”
Do you belive current iteration of AI has the potential to become superhuman? I think it’s like trying to get to the moon by building a better ladder.
LLMs are a dead end.
Their only value is showing how fucked up our society is.
Suddenly and very publicly copyrights only matter if you’re poor, electricity is wasted on the poor, water is not for the poor… it’s always been like this, but the LLM bandwagon really showcased all of that in one shiny package.
The only good thing could be gathering public knowledge into a single space, but they don’t even do that.
So it’s all net negative in my eyes.
I respectfully disagree with the dead end part of your argument. A dead end would be if they provided no value.
While the environmental and social downsides are massive negatives on the tech, it is actually doing something.
Past iterations are completely useless, but more recent iterations show us a more polished side to LLMs that actually do enhance how we do some things.
Is it worth it? My gut says no, but its both too late and too early to call it. (late in the environmental and societal impact, too early in the tech iteration)
As far as the “dead end” argument goes, I have to say that’s a hard disagree. Humanity is filled with technological advances that “stand on the shoulders of giants” and improve on previous techs. Even if LLMs themselves don’t prove to be the thing that we’ve been promised by the people driving it, it is taking us one step closer to AGI (whether that’s a good goal or not, that’s still up for debate)
From here on, I think there’s still quite a bit these models can improve, and I hope a lot of that improvement goes into making it more energy efficient, more water efficient in turn.
If by a dead end you mean that we can’t reach an AGI from an LLM, I think that’s correct, however an LLM might help us figure out what is needed for an AGI.
You didn’t actually say what you think LLM’s are enhancing. Just that you feel that they are. Honestly I think that’s the biggest part, they’re big shiny things that look like they’re doing a lot. But they actually aren’t. LLMs are chatbots and they will never be anything more than just chatbots.
LLMs are not chat bots, they do natural language generation AKA: they can produce human readble text, they can also parse text; As of now, they take an input and follow patterns to guess what the output should be, it is really useful to be fair, they help in translation (see Deepl, a very good translator), they can take data and make it more readble to humans, summarize text*, parse text and data structures ex: i can give a JSON file to an LLM so i can get back a TOML file, document hard to read code etc etc
*but i’d argue that it’s rarely useful, you will hardly have to summarize a text for yourself because you usually need to know any detail in it but i can see someone needing a summary once
The fact that you think it’s bad at one thing in your list but adequate at the others is part of the problem. It’s bad at all of those things, because it’s a chatbot. Admittedly a very advanced chatbot, but still just a chatbot.
The most important take away here is what of your list was impossible before LLMs? Because the reality is that absolutely everything that you mentioned was possible before LLMs. All that LLMs have added is the chat interface part.
Granted, the technology that allowed LLM’s is likely to be very useful and already has been in places like protein folding, but that happened before LLMs.
- i am not saying that all of them were impossible before
- a chatbot is an LLM, an LLM is not always a chatbot, does this look like a chatbot to you?
