They had been saying it was 10 years away for ~50 years, so that's progress. Soon it will be 1 month away, for another two years. And when they say it's really here for real, there will still be a year of waiting.
> And when they say it's really here for real, there will still be a year of waiting.
Indeed. Although, there's a surprising number of people claiming it's already here now.
And to describe the typical cycle completely, the final step is usually a few years after most people agree it's obvious it's already been here for a while yet no one can agree on which which year in the past it actually arrived.
> Although, there's a surprising number of people claiming it's already here now.
why is that surprising? nobody really agrees on what the threshold for AGI is, and if you break it down:
is it artificial? yes.
is it general? yes. you can ask it questions across almost any domain.
is it intelligent? yes. like people say things like "my dog is intelligent" (rightly so). well is chatgpt more intelligent than a dog? yeah. hell it might give many undergrads a run for their money.
a literal reading suggests agi is here. any claim to the negative is either homocentrism or just vibes.
Sure, I've been pointing out that literal sense myself, but to be fair, that's not what people mean by AGI. They mean real understanding, which is clearly missing. You just have to dig a bit deeper to realize that. One example is contradictory sentences in the same breath. Just last week I was asking Gemini 2.5 how I can see my wifi password on my iphone and it said that it's not possible and to do it I have to [...proceeding to correctly explain how to get it]. It's pretty telling, and no amount of phd-level problem solving can push this kind of stuff under the rug.
"Nothing dumb anywhere" is an unreasonably high bar for AGI. Even Isaac Newton spent 1/3 of his career trying to predict future events from reading the Bible. Not to mention all the insane ego-driven decisions like Hamilton's voluntary duel with Burr.
Sure, Gemini may spit out obviously self-contradictory answers 2% of the time. How does that compare to even the brightest humans? People slip up all the time.
There's dumb and there's incoherent. If a person would be incoherent at this level even one time, they would be well advised see a neurologist. Unless they are in some other way incapacitated (i.e. drunk or drugged). Same if they wouldn't be able to count the r's in "strawberry", attempt after attempt, getting more and more lost in again incoherent mock-reasoning.
I disagree completely - consider asking a color blind person to describe the color of flowers. Conversation would only be frustrating. This is analogous to LLMs seeing the world in tokens rather than characters, so character counts are simply not part of their input spectra in the same way that a blind person doesn’t get visual inputs.
Consider also all the smart people who get obsessed with conspiracy theories and spew out endless “mock reasoning” about them. Again, if “nothing incoherent anywhere” is your benchmark for intelligence, humans ain’t it. I mean, what would a computer say about a human that forgot where he just put his keys because he was thinking about dinner - “what, you can’t even store the last 10 seconds of history and search it?” Undergrads’ hit rates on mental double digit multiplication are probably <50%. In many, many ways we look completely idiotic. Surely intelligence is defined by what we can do.
Do you accept any positive definition for AGI, as in if they can achieve X result (write a bestselling novel, solve the Riemann Hypothesis) you would consider it intelligent? I find that negative definitions, as well as theoretical arguments about the techniques rather than the results (eg “LLMs cannot be AGI because they were trained the predict the next word”) to be basically useless for discussion compared to thresholds for positive results. The former will never be achieved (it is trivial to find cases of intelligent people being dumb) and the latter is totally subjective.
> I'd be prepared to argue that most humans aren't guessing most of the time.
Research suggests otherwise[1]. Action seems largely based on intuition or other non-verbal processes in the brain with rationalization happening post-hoc.
I've figured for an age that this is because consciously reasoning through anything using language as a tool takes time. Whereas survival requires me to react to the attacking tiger immediately.
> I'd be prepared to argue that most humans aren't guessing most of the time.
Almost everything we do is just an educated guess. The probability of it being correct is a function of our education (for whatever kind of education is applicable).
For example: I guess that when I get out of bed in the morning, my ankles will support my weight. They might not, but for most people, the answer is probably going to be their best guess.
It's easy to see this process in action among young children as another example. They're not born knowing that they won't fall over when they run, then they start assuming they can run safely, then they discovered skinned knees and hands.
> I'd be prepared to argue that most humans aren't guessing most of the time.
Honestly interested about your arguments here. While unprepared, i'd actually be guessing the opposite, saying that most people are guessing most of the time.
> They mean real understanding, which is clearly missing
is it clear? i don't know. until you can produce a falsifiable measure of understanding -- it's just vibes. so, you clearly lack understanding of my point which makes you not intelligent by your metric anyway ;-). i trust you're intelligent
It seems right that LLMs don't have an innate understanding of time, although you could analogize what you did with writing someone a letter and saying "please count to ten with a two-second pause between numbers". When you get a letter back in the mail, it presumably won't contain any visible pauses either.
That's because you used a LLM trained to produce text, but you asked it to produce actions, not just text. An agentic model would be able to do it, precisely by running that Python code. Someone could argue that a 3 year old does exactly that (produces a plan, then executes it). But these models have deeper issues of lack of comprehension and logical consistency, which prevents us (thankfully) from being able to completely remove the necessity of a man-in-the-middle who keeps an eye on things.
just because it doesn't do what you tell it to doesn't mean it's not intelligent. i would say doing something that gets you where you want when it knows? it can't do exactly what you asked for (because architecurally it's impossible) could be a sign of pretty intelligent sideways thinking!!? dare i say it displays a level of self awareness that i would not have expected.
While you can say that LLMs have each of A, G and I, you may argue that AGI is A·G·I and what we see is A+G+I. It is each of those things in isolation, but there is more to intelligence. We try to address the missing part as agency and self-improvement. While we can put the bar arbitrarily high for homocentric reasons, we can also try to break down what layers of intelligence there are between Singularity Overlord (peak AGI) and Superintelligent Labrador On Acid (what we have now). Kind of like what complexity theorists do between P and NP.
> a literal reading suggests agi is here. any claim to the negative is either homocentrism or just vibes.
Or disagreeing with your definition. AGI would need to be human-level across the board, not just chat bots. That includes robotics. Manipulating the real world is even more important for "human-level" intelligence than generating convincing and useful content. Also, there are still plenty of developers who don't think the LLMs are good enough to replace programmers yet. So not quite AGI. And the last 10% of solving a problem tends to be the hardest and takes the longest time.
ChatGPT would easily have passed any test in 1995 that programmers / philosophers would have set for AGI at that time. There was definitely no assumption that a computer would need to equal humans in manual dexterity tests to be considered intelligent.
We've basically redefined AGI in a human centric way so that we don't have to say ChatGPT is AGI.
Any test?? It's failing plenty of tests not of intelligence, but of... let's call it not-entirely-dumbness. Like counting letters in words. Frontier models (like Gemini 2.5 pro) are frequently producing answers where one sentence is directly contradicted by another sentence in the same response. Also check out the ARC suite of problems easily solved by most humans but difficult for LLMs.
yeah but a lot of those failures fail because of underlying architecture issues. this would be like a bee saying "ha ha a human is not intelligent" because a human would fail to perceive uv patterns on plant petals.
That's just not true. Star Trek Data was understood in the 90s to be a good science fiction example of what an AGI (known as Strong AI back then) could do. HAL was even older one. Then Skynet with it's army of terminators. The thing they all had common was the ability to manipulate the world as well or better than humans.
The holodeck also existed as a well known science fiction example, and people did not consider the holodeck computer to be a good example of AGI despite how good it was at generating 3D worlds for the Star Trek crew.
Many human beings don’t match “human intelligence” in all areas. I think any definition of AGI has to be a test that 95% of humans pass (or you admit your definition is biased and isn’t based on an objective standard).
Which is why we have checklist and process that get us to #3. And we automate some of them to further reduce the chance of errors. The nice thing about automation is that you can just prove that it works once and you don't need to care that much after (deterministic process).
I’d say it is not intelligent. At all. Not capable of any reasoning, understanding or problem solving. A dog is vastly more intelligent than the most capable current ai.
The output sometimes looks intelligent, but it can just as well be complete nonsense.
I don’t believe llms have much more potential for improvement either. Something else entirely is needed.
Indeed. Although, there's a surprising number of people claiming it's already here now.
And to describe the typical cycle completely, the final step is usually a few years after most people agree it's obvious it's already been here for a while yet no one can agree on which which year in the past it actually arrived.