Skepticism isn't the same thing as fighting the future.

I will call something AGI when it can reliably solve novel problems it hasn't been pre-trained on. That's my goal post and I haven't moved it.

This is the kind of thing that I disagree with. Over the last 75 years we’ve seen enormous productivity gains.

You think that LLMs are a bigger productivity boost than moving from physically rewiring computers to using punch cards, from running programs as batch processes with printed output to getting immediate output, from programming in assembly to higher level languages, or even just moving from enterprise Java to Rails?

I have the complete opposite feeling. The layman understanding of the term "AI" is AGI, a term that only needs to exist because researchers and businessmen hype their latest creations as AI.

The goalposts for AI don't move but the definition isn't precise but we know it when we see it.

AI, to the layman, is Skynet/Terminator, Asimov's robots, Data, etc.

The goalposts moving that you're seeing is when something the tech bubble calls AI escapes the tech bubble and everyone else looks at it and says, no, that's not AI.

The problem is that everything that comes out of the research efforts toward AI, the tech industry calls AI despite it not achieving that goal by the common understanding of the term. LLMs were/are a hopeful AI candidate but, as of today, they aren't but that doesn't stop OpenAI from trying to raise money using the term.

If you want some semantic rigour use more specific terms like AGI, human equivalent AGI, super human AGI, exponentially self improving AGI, etc. Even those labels lack rigour, but at least they are less ambiguous.

LLMs are pretty clearly AI and AGI under commonly understood, lay definitions. LLMs are not human level AGI and perhaps will never be by themselves.

That's certainly not clear. For starters, I don't think there is a lay definition of AGI which is largely my point.

The only reason people are willing to call LLMs AI is because that's how they are being sold and the shine isn't yet off the rose.

How many people call Siri AI? It used to be but people have had time to feel around the edges where it fails to meet their expectations of AI.

You can tell what people think of AI by the kind of click bait surrounding LLMs. I read an article not too long ago with the headline about an LLM lying to try and not be turned off. Turns out it was intentionally prompted to do that but the point is that that kind of self preservation is what people expect of AI. Implicitly, they expect that AI has a "self".

ChatGPT doesn't have a self.

Engaging in semantic battles to try to change the meanings of those terms is just going to create more confusion, not less. Instead why not use more specific and descriptive labels to be clear about what you are saying.

Self-Aware AGI, Human Level AGI, Super-Human ANI, are all much more useful than trying to force general label to be used a specific way.

You're doing that. I've never seen someone state, as fact, that LLMs are AGI before now. Go ask someone on the street what Super-Human ANI means.

Then you probably haven't been paying attention.

https://deepmind.google/research/publications/66938/

> I've never seen someone state, as fact, that LLMs are AGI before now.

Many LLMs are AI that weren't designed / trained to solve a narrow problem scope. They can complete a wide range of tasks with varying levels of proficiency. That makes them artificial general intelligence or AGI.

You are confused because lots of people use "AGI" as a shorthand to talk about "human level" AGI that isn't limited to a narrow problem scope.

It's not wrong to use the term this way, but it is ambiguous and vague.

Even the term "human level" is poorly defined and if I wanted to use the term "Human level AGI" for any kind of discussion of what qualifies, I'd need to specify how I was defining that.

It's actually very funny to me that you are stating these definitions so authoritatively despite the terms not having any sort if rigor attached to either their definition or usage.

Huh? My entire point was that AI and AGI are loose, vague terms and if you want to be clear about what you are talkng about, you should use more specific terms.

EDIT - I see now. sorry.

For all intents and purposes of the public. AI == LLM. End of story. Doesn't matter what developers say.

This is interesting, because it's so clearly wrong. The developers are also the people who develop the LLMs, so obviously what they say is actually the factual matter of the situation. It absolutely does matter what they say.

But the public perception is that AI == LLM, agreed. Until it changes and the next development comes along, when suddenly public perception will change and LLMs will be old news, obviously not AI, and the new shiny will be AI. So not End of Story.

People are morons. Individuals are smart, intelligent, funny, interesting, etc. But in groups we're moronic.

Almost always, yes, because I know what I'm doing and I have a brain that can think. I actually think before I do anything, which leads to good results. Don't assume everyone is a junior.

>Didn't think so.

You don't know me at all.

Sure sometimes I do stuff I am not confident about to learn but then I don't say "here I solved the problem for you" without building confidence around the solution first.

Every competent senior engineer should be like this, if you aren't then you aren't competent. If you are confident in a solution then it should almost always work, else you are over confident and thus not competent. LLM are confident in solutions that are shit.

If you always use your first output then you are not a senior engineer, either your problem space is THAT simple that you can fit all your context in your head at the same time first try, or quite frankly you just bodge things together in non-optimal way.

It always takes some tries at a problem to grasp edge cases and to easier visualize the problem space.

This is not a fault of the users. These labels are pushed primarily by "AI" companies in order to hype their products to be far more capable than they are, which in turn increases their financial valuation. Starting with "AI" itself, "superintelligence", "reasoning", "chain of thought", "mixture of experts", and a bunch of other labels that anthropomorphize and aggrandize their products. This is a grifting tactic old as time itself.

From Sam Altman[1]:

> We are past the event horizon; the takeoff has started. Humanity is close to building digital superintelligence

Apologists will say "they're just words that best describe these products", repeat Dijkstra's "submarines don't swim" quote, but all of this is missing the point. These words are used deliberately because of their association to human concepts, when in reality the way the products work is not even close to what those words mean. In fact, the fuzzier the word's definition ("intelligence", "reasoning", "thought"), the more valuable it is, since it makes the product sound mysterious and magical, and makes it easier to shake off critics. This is an absolutely insidious marketing tactic.

The sooner companies start promoting their products honestly, the sooner their products will actually benefit humanity. Until then, we'll keep drowning in disinformation, and reaping the consequences of an unregulated marketplace of grifters.

[1]: https://blog.samaltman.com/the-gentle-singularity

Unfortunately, discourse has followed an epistemic trajectory influenced by Hollywood and science fiction, making clear communication on the subject nearly impossible without substantial misunderstanding.