They’ll devalue the term into something that makes it so. The common conception of it however, no I don’t believe we are anywhere close to it.
It’s no different than how they moved the goalpost on the definition of AI at the start of this boom cycle
It’s no different than how they moved the goalpost on the definition of AI at the start of this boom cycle
Exactly. As soon as the money runs out, “AGI” will be whatever they’ve got by then.
But, at the same time, we have clearly passed a significant inflection point in the usefulness of this class of AI, and have progressed substantially beyond that inflection point as well.
So I don't really buy into the idea tha OpenAI have gone out of their way to foist a watered down view of AI upon the masses. I'm not completely absolving them but I'd probably be more inclined to point the finger at shabby and imprecise journalism from both tech and non-tech outlets, along with a ton of influencers and grifters jumping on the bandwagon. And let's be real: everyone's lapped it up because they've wanted to - because this is the first time any of them have encountered actually useful AI of any class that they can directly interact with. It seems powerful, mysterious, perhaps even agical, and maybe more than a little bit scary.
As a CTO how do you think it would have gone if I'd spent my time correcting peers, team members, consultants, salespeople, and the rest to the effect that, no, this isn't AI, it's one type of AI, it's an LLM, when ChatGPT became widely available? When a lot of these people, with no help or guidance from me, were already using it to do useful transformations and analyses on text?
It would have led to a huge number of unproductive and timewasting conversation, and I would have seemed like a stick in the mud.
Sometimes you just have to ride the wave, because the only other choice is to be swamped by it and drown.
Regardless of what limitations "AGI" has, it'll be given that monicker when a lot of people - many of them laypeople - feel like it's good enough. Whether or not that happens before the current LLM bubble bursts... tough to say.
I mean, once they "reach AGI", they will need a scale to measure advances within it.
Peter Norvig (former research director at Google and author of the most popular textbook on AI) offers a mainstream perspective that AGI is already here: https://www.noemamag.com/artificial-general-intelligence-is-...
If you described all the current capabilities of AI to 100 experts 10 years ago, they’d likely agree that the capabilities constitute AGI.
Yet, over time, the public will expect AGI to be capable of much, much more.
today's models are not able to think independently, nor are they conscious or able to mutate themselves to gain new information on the fly or make memories other than half baked solutions with putting stuff in the context window which just makes it use that to generate stuff related to it, imitating a story basically.
they're powerful when paired with a human operator, I.e. they "do" as told, but that is not "AGI" in my book
See "Self-Adapting Language Models" from a group out of MIT recently which really gets at exactly that.
Then it blew past that and now, what I think is honestly happening, is that we don't really have the grip on "what is intelligence" that we thought we had. Our sample size for intelligence is essentially 1, so it might take a while to get a grip again.
One thing they acknowledge but glance over, is the autonomy of current systems. When given more open ended, long term tasks, LLMs seem to get stuck at some point and get more and more confused and stop making progress.
This last problem may be solved soon, or maybe there's something more fundamental missing that will take decades to solve. Who knows?
But it does seem like the main barrier to declaring current models "general" intelligence.
I think that we're moving the goalposts, but we're moving them for a good reason: we're getting better at understanding the strengths and the weaknesses of the technology, and they're nothing like what we'd have guessed a decade ago.
All of our AI fiction envisioned inventing intelligence from first principles and ending up with systems that are infallible, infinitely resourceful, and capable of self-improvement - but fundamentally inhuman in how they think. Not subject to the same emotions and drives, struggling to see things our way.
Instead, we ended up with tools that basically mimic human reasoning, biases, and feelings with near-perfect fidelity. And they have read and approximately memorized every piece of knowledge we've ever created, but have no clear "knowledge takeoff path" past that point. So we have basement-dwelling turbo-nerds instead of Terminators.
This makes AGI a somewhat meaningless term. AGI in the sense that it can best most humans on knowledge tests? We already have that. AGI in the sense that you can let it loose and have it come up with meaningful things to do in its "life"? That you can give it arms and legs and watch it thrive? That's probably not coming any time soon.
Yes, and if they used it for awhile, they'd realize it is neither general nor intelligent. On paper sounds great though.
Because everyone knows that once you call a group of people an expert panel, that automatically means they can't be biased /s
Who is this "they" you speak of?
It's true the definition has changed, but not in the direction you seem to think.
Before this boom cycle the standard for "AI" was the Turing test. There is no doubt we have comprehensively passed that now.
eg: https://pmc.ncbi.nlm.nih.gov/articles/PMC10907317/
It's widely accepted that is has been passed. Eg Wikipeida:
> Since the mid-2020s, several large language models such as ChatGPT have passed modern, rigorous variants of the Turing test
People are being fooled in online forums all the time. That includes people who are naturally suspicious of online bullshittery. I'm sure I have been.
Stick a fork in the Turing test, it's done. The amount of goalpost-moving and hand-waving that's necessary to argue otherwise simply isn't worthwhile. The clichéd responses that people are mentioning are artifacts of intentional alignment, not limitations of the technology.
a problem similar to the turing test, "0 or more of these users is a bot, have fun in a discussion forum"
but there's no test or evaluation to see if any user successfully identified the bot, and there's no field to collect which users are actually bots, or partially using bots, or not at all, nor a field to capture the user's opinions about whether the others are bots
1) Look for spelling, grammar, and incorrect word usage; such as where vs were, typing out where our should be used.
2) Ask asinine questions that have no answers; _Why does the sun ravel around my finger in low quality gravity while dancing in the rain?_
ML likes to always come up with an answers no matter what. Human will shorten the conversation. It also is programmed to respond with _I understand_, _I hear what you are saying_, and make heavy use of your name if it has access to it. This fake interpersonal communication is key.
Do you think this goal during training cannot be changed to impersonate someone normal such that you cannot detect you are chatting with an LLM?
Before flight was understood some thought "magic" was involved. Do you think minds operate using "magic"? Are minds not machines? Their operation can not be duplicated?
1. Minds are machines and can (in principle) have their operation duplicated
2. LLMs are not doing this
I don't think so, because LLMs hallucinate by design, which will always produce oddities.
> Before flight was understood some thought "magic" was involved. Do you think minds operate using "magic"? Are minds not machines? Their operation can not be duplicated?
Might involve something we don't grasp, but despite that: only because something moves through air it's not flying and will never be, just like a thrown stone.
And the "agreeability" is not a hallucination, it's simply the path of least resistance, as in, the model can just take information that you said and use that to make a response, not to actually "think" and consider I'd what you even made sense or I'd it's weird or etc.
They almost never say "what do you mean?" to try to seek truth.
This is why I don't understand why some here claim that AGI being already here is some kind of coherent argument. I guess redefining AGI is how we'll reach it
If it wasn't structured as a coherent conversation, it will ask because it seems off, especially if you're early in the context window where I'm sure they've RLd it to push back, at least in the past year or so
And if it's going against common knowledge or etc which is prevalent in the training data, it will also push back which makes sense
Let's be real guys, it was created by Turing. The same guy who built the first general purpose computer. Man was without a doubt a genius, but it also isn't that reasonable to think he'd come up with a good definition or metric for a technology that was like 70 years away. Brilliant start, but it is also like looking at Newton's Laws and evaluating quantum mechanics based off of that. Doesn't make Newton dumb, just means we've made progress. I hope we can all agree we've made progress...
And arguably the Turing Test was passed by Eliza. Arguably . But hey, that's why we refine and make progress. We find the edge of our metrics and ideas and then iterate. Change isn't bad, it is a necessary thing. What matters is the direction of change. Like velocity vs speed.
We really really Really should Not define as our success function for AI (our future-overlords?) the ability of computers to deceive humans about what they are.
The Turing Test was a clever twist on (avoiding) defining intelligence 80 years ago.
Going forward, valuing it should be discarded post-haste by any serious researcher or engineer or message-board-philosopher, if not for ethical reasons then for not-promoting spam/slop reasons.
No, I did not. I tested it with questions that could not be answered by the Internet (spatial, logical, cultural, impossible coding tasks) and it failed in non-human-like ways, but also surprised me by answering some decently.
We might not _quite_ be at the era of "I'm sorry I can't let you do that Dave...", but on the spectrum, and from the perspective of a lay-person, we're waaaaay closer than we've ever been?
I'd counsel you to self-check what goalposts you might have moved in the past few years...
I say this fully aware that a kitted out tech company will be using LLMs to write code more conformant to style and higher volume with greater test coverage than I am able to individually.
And just like humans, they can be very confidently wrong. When any person tells us something, we assume there's some degree of imperfection in their statements. If a nurse at a hospital tells you the doctor's office is 3 doors down on the right, most people will still look at the first and second doors to make sure those are wrong, then look at the nameplate on the third door to verify that it's right. If the doctor's name is Smith but the door says Stein, most people will pause and consider that maybe the nurse made a mistake. We might also consider that she's right, but the nameplate is wrong for whatever reason. So we verify that info by asking someone else, or going in and asking the doctor themselves.
As a programmer, I'll ask other devs for some guidance on topics. Some people can be absolute geniuses but still dispense completely wrong advice from time to time. But oftentimes they'll lead me generally in the right way, but I still need to use my own head to analyze whether it's correct and implement the final solution myself.
The way AI dispenses its advice is quite human. The big problem is it's harder to validate much of its info, and that's because we're using it alone in a room and not comparing it against anyone else's info.
No they are not smart at all. Not even a little. They cannot reason about anything except that their training data overwhelmingly agrees or disagrees with their output nor can they learn and adept. They are just text compression and rearrangement machines. Brilliant and extremely useful tooling but if you use them enough it becomes painfully obvious.
edit: i'm very thankful my friend didn't end up winning more than he bet. idk what he would have done if his feelings towards the LLM was confirmed by adding money to his pocket..
E.g. I read all the time about gains from SWEs. But nobody questions how good of a SWE they even are. What proportion of SWEs can be deemed high quality?
LLMs are useful but that doesn't make them intelligent.