>Leave a comment on your pet definition for “human-level AGI” which is
>
>testable
>
>falsifiable
>
>robust

I can't even give you a definition like that for "general human intelligence".

Obviously your timeline will also vary depending on your definition, so this needs to be two different discussions.

LLMs are at least relatively "general", as opposed to earlier approaches that were restricted to a specific task. So within the domain of language, we made some insane progress in the past 7 years. Whether that constitutes "intelligence" really depends on what you think that is, which nobody agrees on.

Unless someone can define "human general intelligence" and "artificial general intelligence" for me, the discussion of timeline just detracts from the actual progress and near-term implications of recent developments. That's my 2 cents

Which human?

GPT-4 outperforms my aunt Carol on the bar-exam, so AGI is here!

My informal definition of "human-level AGI," is a system whose only mistakes are indistinguishable from mistakes a human could make, given the same context.

I vote for 2030-2040 if you put an AI into my body nobody who know me would notice any difference. I.e. he can fake me perfectly. But 2030 I am sure many people will start to at least believe there is already agi.

>Making the bold an unscientific assumption that this sub is at least decently representative of people “in the know” on ML,.

The increasing number of posts like this indicate that it may no longer be the case.

I’m not trying to be snarky or mean when I say this, but these sorts of posts offer pretty much zero insight or discussion value. There are a lot of very knowledgeable minds on this subreddit, but you won’t be able to get much out of it by asking such vague and sweeping questions.

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Relevant publication: https://cdn.openai.com/papers/gpt-4.pdf

I can take comfort in knowing that while GPT-4 is 10-percentile better than me in GRE Verbal, I still score (slightly) better than GPT-4 in GRE Quantitative and very similarly in GRE-Writing. (English is not my first language)

Side note: I am surprised how poorly GPT-4 do in AP English Language and AP English Lit; I thought as a large language model, it would have an advantage in those sort of questions. (Sorry, not an American, i could be misunderstanding what exactly is being tested in those subjects)

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Really depends on how "general" you define AGI to be.

To me, AGI means developing agents that can operate autonomously in the real world and make sensible decisions across a wide range of situations and domains. I don't think we're currently very close to developing these sorts of agents, although it probably isn't more than a couple decades away.

GPT-4 likely surpasses pretty much anyone with IQ under 70.

Can be determined by a Turing test, where the person guessing is of that IQ level.

Exactly. LLMs mimic intelligence by just generating text, and since they are trained on civilization-level knowledge/data they do it very well and can seem as intelligent as humans.

The real test is to put them to novel scenarios and see how their intelligence can produce solutions to these, i.e. put it in an some sort of escape room and see if they can escape.

GPT4 is already smarter than the people that said 2100+

it also outperforms her on like 50000 other topics, in 50 different languages, while simultaneously talking to a million other people about a million different things

oh, but someone asked it a trick question and it reflexively gave the wrong answer, nevermind

I don't know if IQ is exactly a good metric here because LLMs merely replicate training data so it would be likely that the training data (which is very big) contains information regarding IQ tests. It would be an indirect comparison because you'd be comparing sheer training data amount with a person's ability to produce thoughts. It would be way more interesting to give GPT4 complex situations that require advanced problem solving skills. Say you got a message that you need to decode and it has multiple layers of encryption and you only have a few hints on how you might go about it, since there's no way to replicate responses based on previous training data I'd be curious to see how far it gets, or let's say a hacking CTF, which is something that not only takes pure coding skill, but also a creative thought process.

You are missing the idea entirely. I am sticking to the idea of the original Turing test to determine if AI is human-level already or not yet.

The original Turing test is dead simple and can be applied to ChatGPT easily.

The only other thing in my comment is that "human-level" is vague, as intelligence differs from human to human, which allows for goalpost moving like in your comment. IQ is the best measure of intelligence we have. So it is reasonable to turn the idea of Turing test into a plethora of different tests Turing(I) which is like any regular Turing test, but the IQ of the humans participating in the tests (both machine's opponent, and the person who needs to guess which one is the machine) is <= I.

My claim is that I believe ChatGPT or ChatGPT + some trivial form of memory enhancements (like feeding previous failures back into prompts) quite possibly can already pass Turing(70).