[lukebuehler]

If cannot the say they are "thinking", "intelligent" while we do not have a good definition--or, even more difficult, unanimous agreement on a definition--then the discussion just becomes about output.

They are doing useful stuff, saving time, etc, which can be measured. Thus also the defintion of AGI has largely become: "can produce or surpass the economic output of a human knowledge worker".

But I think this detracts from the more interesting discussion of what they are more essentially. So, while I agree that we should push on getting our terms defined, I think I'd rather work with a hazy definition, than derail so many AI discussion to mere economic output.

[Rebuff5007]

Heres a definition. How impressive is the output relative to the input. And by input, I don't just mean the prompt, but all the training data itself.

Do you think someone who has only ever studied pre-calc would be able to work through a calculus book if they had sufficient time? how about a multi-variable calc book? How about grad level mathematics?

IMO intelligence and thinking is strictly about this ratio; what can you extrapolate from the smallest amount of information possible, and why? From this perspective, I dont think any of our LLMs are remotely intelligent despite what our tech leaders say.

[kryogen1c]

Hear, hear!

I have long thought this, but not had as good way to put it as you did.

If you think about geniuses like Einstein and ramanujen, they understood things before they had the mathematical language to express them. LLMs are the opposite; they fail to understand things after untold effort, training data, and training.

So the question is, how intelligent are LLMs when you reduce their training data and training? Since they rapidly devolve into nonsense, the answer must be that they have no internal intelligence

Ever had the experience of helping someone who's chronically doing the wrong thing, to eventually find they had an incorrect assumption, an incorrect reasoning generating deterministic wrong answers? LLMs dont do that; they just lack understanding. They'll hallucinate unrelated things because they dont know what they're talking about - you may have also had this experience with someone :)

[mycall]

Animals think but come with instincts which breaks the output relative to the input test you propose. Behaviors are essentially pre-programmed input from millions of years of evolution, stored in the DNA/neurology. The learning thus typically associative and domain-specific, not abstract extrapolation.

A crow bending a piece of wire into a hook to retrieve food demonstrates a novel solution extrapolated from minimal, non-instinctive, environmental input. This kind of zero-shot problem-solving aligns better with your definition of intelligence.

[tremon]

I'm not sure I understand what you're getting at. You seem to be on purpose comparing apples and oranges here: for an AI, we're supposed to include the entire training set in the definition of its input, but for a human we don't include the entirety of that human's experience and only look at the prompt?

[lukebuehler]

That an okay-ish definition, but to me this is more about whether this kind of "intelligence" is worth it, not whether it is intelligence itself. The current AI boom clearly thinks it is worth to put that much input to get the current frontier-model-level of output. Also, don't forget the input scales across roughly 1B weekly users at inference time.

I would say a good definition has to, minimally, take on the Turing test (even if you disagree, you should say why). Or in current vibe parlance, it does "feel" intelligent to many people--they see intelligence in it. In my book this allows us to call it intelligent, at least loosely.

[fragmede]

There are plenty of humans that will never "get" calculus, despite numerous attempts at the class and countless hours of 1:1 tutoring. Are those people not intelligent? Do they not think? We could say yes they aren't, but by the metric of making money, plenty of people are smart enough to be rich, while college math professors aren't. And while that's a facile way of measuring someone's worth or their contribution to society (some might even say "bad"), it remains that even if someone cant understand calculus, some of them are intelligent enough to understand humans enough to be rich through some fashion that wasn't simply handed to them.

[hodgehog11]

Yeah, that's compression. Although your later comments neglect the many years of physical experience that humans have as well as the billions of years of evolution.

And yes, by this definition, LLMs pass with flying colours.

[skeeter2020]

This feels too linear. Machines are great at ingesting huge volumes of data, following relatively simple rules and producing optimized output, but are LLMs sufficiently better than humans at finding windy, multi-step connections across seemingly unrelated topics & fields? Have they shown any penchant for novel conclusions from observational science? What I think your ratio misses is the value in making the targeted extrapolation or hypothesis that holds up out of a giant body of knowledge.

[jononor]

For more on this perspective, see the paper On the measure of intelligence (F. Chollet, 2019). And more recently, the ARC challenge/benchmarks, which are early attempts at using this kind of definition in practice to improve current systems.

[rolisz]

Is the millions of years of evolution part of the training data for humans?

[felipeerias]

The discussion about “AGI” is somewhat pointless, because the term is nebulous enough that it will probably end up being defined as whatever comes out of the ongoing huge investment in AI.

Nevertheless, we don’t have a good conceptual framework for thinking about these things, perhaps because we keep trying to apply human concepts to them.

The way I see it, a LLM crystallises a large (but incomplete and disembodied) slice of human culture, as represented by its training set. The fact that a LLM is able to generate human-sounding language

[roenxi]

Not quite pointless - something we have established with the advent of LLMs is that many humans have not attained general intelligence. So we've clarified something that a few people must have been getting wrong, I used to think that the bar was set so that almost all humans met it.

[idiotsecant]

I think it has a practical, easy definition. Can you drop an AI into a terminal, give it the same resources as a human, and reliably get independent work product greater than that human would produce across a wide domain? If so, it's an AGI.

[lukebuehler]

I agree that the term can muddy the waters, but as a shorthand for roughly "an agent calling an LLM (or several LLMs) in a loop producing similar economic output as a human knowledge-worker", then it is useful. And if you pay attention to the AI leaders, then that's what the defintion has become.

[keiferski]

Personally I think that kind of discussion is fruitless, not much more than entertainment.

If you’re asking big questions like “can a machine think?” Or “is an AI conscious?” without doing the work of clarifying your concepts, then you’re only going to get vague ideas, sci-fi cultural tropes, and a host of other things.

I think the output question is also interesting enough on its own, because we can talk about the pragmatic effects of ChatGPT on writing without falling into this woo trap of thinking ChatGPT is making the human capacity for expression somehow extinct. But this requires one to cut through the hype and reactionary anti-hype, which is not an easy thing to do.

That is how I myself see AI: immensely useful new tools, but in no way some kind of new entity or consciousness, at least without doing the real philosophical work to figure out what that actually means.

[jlaternman]

I agree with almost all of this.

IMO the issue is we won't be able to adequately answer this question before we first clearly describe what we mean of conscious thinking applied to ourselves. First we'd need to clearly define our own consciousness and what we mean by our own "conscious thinking" in a much, much clearer way than we currently do.

If we ever reach that point, I think we'd be able to fruitfully apply it to AI, etc., to assess.

Unfortunately we haven't been obstructed from answering this question about ourselves for centuries or millennia, but have failed to do so, so it's unlikely to happen suddenly now. Unless we use AIs to first solve that problem of defining our own consciousness, before applying it back on them. Which would be a deeply problematic order, since nobody would trust a breakthrough in the understanding of consciousness that came from AI, that is then potentially used to put them in the same class and define them as either thinking things or conscious things.

Kind of a shame we didn't get our own consciousness worked out before AI came along. Then again, wasn't for the lack of trying… Philosophy commanded the attention of great thinkers for a long time.

[lukebuehler]

I do think it raises interesting and important philosophical questions. Just look at all the literature around the Turing test--both supporters and detractors. This has been a fruitful avenue to talk about intelligence even before the advent of gpt.