In the near future, it is projected that contrarians will gain self awareness.

Yeah this sounds about right. What was OP implying I’m a bit lost?

Depends on what you mean by general intelligence. I've seen a lot of people confuse Artificial General Intelligence and AI more broadly. Even something as simple as the K-nearest neighbor algorithm is artificial intelligence, as this is a much broader topic than AGI.

Wikipedia gives two definitions of AGI:

An artificial general intelligence (AGI) is a hypothetical type of intelligent agent which, if realized, could learn to accomplish any intellectual task that human beings or animals can perform. Alternatively, AGI has been defined as an autonomous system that surpasses human capabilities in the majority of economically valuable tasks.

If some task can be represented through text, an LLM can, in theory, be trained to perform it either through fine-tuning or few-shot learning. The question then is how general do LLMs have to be for one to consider them to be AGIs, and there's no hard metric for that question.

I can't pass the bar exam like GPT-4 did, and it also has a lot more general knowledge than me. Sure, it gets stuff wrong, but so do humans. We can interact with physical objects in ways that GPT-4 can't, but it is catching up. Plus Stephen Hawking couldn't move the same way that most people can either and we certainly wouldn't say that he didn't have general intelligence.

I'm rambling but I think you get the point. There's no clear threshold or way to calculate how "general" an AI has to be before we consider it an AGI, which is why some people argue that the best LLMs are already examples of general intelligence.

It depends a lot on how we perceive "intelligence". It's a lot more vague of a term than most, so people have very different views of it. Some people might have the idea of it meaning the response to stimuli & the output (language or art or any other form) being indistinguishable from humans. But many people may also agree that whales/dolphins have the same level of, or superior, "intelligence" to humans. The term is too vague to really prescribe with confidence, and more importantly people often use it to mean many completely different concepts ("intelligence" as a measurable/quantifiable property of either how quickly/efficiently a being can learn or use knowledge or more vaguely its "capacity to reason", "intelligence" as the idea of "consciousness" in general, "intelligence" to refer to amount of knowledge/experience one currently has or can memorize, etc.)

In computer science "artificial intelligence" has always simply referred to a program making decisions based on input. There was never any bar to reach for how "complex" it had to be to be considered AI. That's why minecraft zombies or shitty FPS bots are "AI", or a simple algorithm made to beat table games are "AI", even though clearly they're not all that smart and don't even "learn".

The damn Viet Cong 😒

OP didn't say general intelligence. LLMs mimic what actually intelligent beings do, AKA artificial intelligence.

Claiming AGI is the only "real" AI is like claiming Swiss army knives are the only "real" knives. It's just silly.

But also the people who seem to think we need a magic soul to perform useful work is way way too high.

The main problem is Idiots seem to have watched one too many movies about robots with souls and gotten confused between real life and fantasy - especially shitty journalists way out their depth.

This big gotcha 'they don't live upto the hype' is 100% people who heard 'ai' and thought of bad Will Smith movies. LLMs absolutely live upto the actual sensible things people hoped and have exceeded those expectations, they're also incredibly good at a huge range of very useful tasks which have traditionally been considered as requiring intelligence but they're not magically able everything, of course they're not that's not how anyone actually involved in anything said they would work or expected them to work.

I find this line of thinking tedious.

Even if LLM's can't be said to have 'true understanding' (however you're choosing to define it), there is very little to suggest they should be able to understand predict the correct response to a particular context, abstract meaning, and intent with what primitive tools they were built with.

If there's some as-yet uncrossed threshold to a bare-minimum 'understanding', it's because we simply don't have the language to describe what that threshold is or know when it has been crossed. If the assumption is that 'understanding' cannot be a quality granted to a transformer-based model -or even a quality granted to computers generally- then we need some other word to describe what LLM's are doing, because 'predicting the next-best word' is an insufficient description for what would otherwise be a slight-of-hand trick.

There's no doubt that there's a lot of exaggerated hype around these models and LLM companies, but some of these advancements published in 2022 surprised a lot of people in the field, and their significance shouldn't be slept on.

Certainly don't trust the billion-dollar companies hawking their wares, but don't ignore the technology they're building, either.

Yes. But the more advanced LLMs get, the less it matters in my opinion. I mean of you have two boxes, one of which is actually intelligent and the other is "just" a very advanced parrot - it doesn't matter, given they produce the same output. I'm sure that already LLMs can surpass some humans, at least at certain disciplines. In a couple years the difference of a parrot-box and something actually intelligent will only merely show at the very fringes of massively complicated tasks. And that is way beyond the capability threshold that allows to do nasty stuff with it, to shed a dystopian light on it.

LLMs definitely provide value its just debatable whether they're real AI or not. I believe they're going to be shoved in a round hole regardless.

I think a better way to view it is that it's a search engine that works on the word level of granularity. When library indexing systems were invented they allowed us to look up knowledge at the book level. Search engines allowed look ups at the document level. LLMs allow lookups at the word level, meaning all previously transcribed human knowledge can be synthesized into a response. That's huge, and where it becomes extra huge is that it can also pull on programming knowledge allowing it to meta program and perform complex tasks accurately. You can also hook them up with external APIs so they can do more tasks. What we have is basically a program that can write itself based on the entire corpus of human knowledge, and that will have a tremendous impact.

The next step is to understand much more and not get stuck on the most popular semantic trap

Then you can begin your journey man

There are so, so many llm chains that do way more than parrot. It's just the last popular catchphrase.

Very tiring to keep explaining that because just shallow research can make you understand more than it's a parrot comment. We are all parrots. It's extremely irrelevant to the ai safety and usefulness debates

Most llm implementations use frameworks to just develop different understandings, and it's shit, but it's just not true that they only parrot known things they have internal worlds especially when looking at agent networks

I love that this is clearly from a computer science course.

HHO generators

...What are these? Something to do with hydrogen? Despite it not making sense for you to write it that way if you meant H2O, I really enjoy the silly idea of a water generator (as in, making water, not running off water).

They are a bit like you'd take just the creative writing center of a human brain. So they are like one part of a human mind without sentience or understanding or long term memory. Just the creative part, even though they are mediocre at being creative atm. But it's shocking because we kind of expected that to be the last part of human minds to be able to be replicated.

Put enough of these "parts" of a human mind together and you might get a proper sentient mind sooner than later.

I have a silly little model I made for creating Vogoon poetry. One of the models is fed from Shakespeare. The system works by predicting the next letter rather than the next word (and whitespace is just another letter as far as it's concerned). Here's one from the Shakespeare generation:

KING RICHARD II:​

Exetery in thine eyes spoke of aid.​

Burkey, good my lord, good morrow now: my mother's said

This is silly nonsense, of course, and for its purpose, that's fine. That being said, as far as I can tell, "Exetery" is not an English word. Not even one of those made-up English words that Shakespeare created all the time. It's certainly not in the training dataset. However, it does sound like it might be something Shakespeare pulled out of his ass and expected his audience to understand through context, and that's interesting.

...yeah dude. Hence artificial intelligence.

There aren't any cherries in artificial cherry flavoring either 🤷‍♀️ and nobody is claiming there is

I wish there was a term without "Intelligence" in it because LLMs aren't intelligent.

I wish we called them VI's. It was a good distinction in their ability.

Though honestly I think our AI is more advanced in conversation than a VI in ME.

This was the first thing that came to my mind as well and VI is such an apt term too. But since we live in the shittiest timeline Electronic Arts would probably have taken the Blizzard/Nintendo route too and patented the term.

I love reading Geth references in the wild.

LLMs are intelligent in the same way books are intelligent. What makes LLMs really cool is that instead of searching at the book or page granularity, it searches at the word granularity. It's not thinking, but all the thinking was done for it already by humans who encoded their intelligence into words. It's still incredibly powerful, at it's best it could make it so no task ever needs to be performed by a human twice which would have immense efficiency gains for anything information based.

ah, yes, prejudice

They also reason which is really wierd

... Alexa literally is A.I.? You mean to say that Alexa isn't AGI. AI is the taking of inputs and outputting something rational. The first AI's were just large if-else complications called First Order Logic. Later AI utilized approximate or brute force state calculations such as probabilistic trees or minimax search. AI controls how people's lines are drawn in popular art programs such as Clip Studio when they use the helping functions. But none of these AI could tell me something new, only what they're designed to compute.

The term AI is a lot more broad than you think.

Alexa is AI. She's artificially intelligent. Moreso than an ant or a pigeon, and I'd call those animals pretty smart.

Nobody is claiming there is problem solving in LLMs, and you don't need problem solving skills to be artificially intelligent. The same way a knife doesn't have to be a Swiss army knife to be called a "knife."

Like almost all politicians?

If anything people really need to start experimenting beyond talking to it like its human or in a few years we will end up with a huge ai-illiterate population.

I’ve had someone fight me stubbornly talking about local llms as “a overhyped downloadable chatbot app” and saying the people on fossai are just a bunch of ai worshipping fools.

I was like tell me you now absolutely nothing you are talking about by pretending to know everything.

Have you ever considered you might be, you know, wrong?

No sorry you're definitely 100% correct. You hold a well-reasoned, evidenced scientific opinion, you just haven't found the right node yet.

Perhaps a mental gymnastics node would suit sir better? One without all us laymen and tech bros clogging up the place.

Or you could create your own instance populated by AIs where you can debate them about the origins of consciousness until androids dream of electric sheep?

All the stuff on the dbzero instance is pro open source and pro piracy so fairly anti corpo and not tech illiterate

P-Zombies, all of them. I happen to be the only one to actually exist. What are the odds, right? But it's true.

I look at all these kids glued to their phones and I ask 'Where's the Frankenstein Complex now that we really need it?"

That was never the goal... You might as well say that a bowling ball will never be effectively used to play golf.

Next you'll tell me that the enemies that I face in video games arent real AI either!

Buddy, nobody ever said it would

Keep seething

Keep projecting

I don't think actual parroting is the problem. The problem is they don't understand a word outside of how it is organized. They can't be told to do simple logic because they don't have a simple understanding of each word in their vocabulary. They can only reorganize things to varying degrees.

I feel that knowing what you don't know is the key here.

An LLM doesn't know what it doesn't know, and that's where what it spouts can be dangerous.

Of course there's a lot of actual people that applies to as well. And sadly they're often in positions of power.

Few people truly understand what understanding means at all, i got teacher in college that seriously thinked that you should not understand content of lessons but simply remember it to the letter

This is only one type of intelligence and LLMs are already better at humans at regurgitating facts. But I think people really underestimate how smart the average human is. We are incredible problem solvers, and AI can't even match us in something as simple as driving a car.

Jokes on them. I don't even calculate when I need to parrot. I am beyond such lowly needs.

That's actually pretty neat. I tried Kobold AI a few months ago but the novelty wore off quickly. You made me curious, I'm going to check out that option once I get home. Is it just a toggleable opyiont option or do you have to mess with some hidden settings?

People making content should immediately pivot to become the approvers, not the generators.

This post isn't true, LLMs do have an understanding of things.

SELF-RAG: Improving the Factual Accuracy of Large Language Models through Self-Reflection

Chess-GPT's Internal World Model

POKÉLLMON: A Human-Parity Agent for Pokémon Battle with Large Language Models

Language Models Represent Space and Time

you... you fucked the LLM?

AI: “Keep Summer safe”

There are specific terms for what you're talking about already. AI is all the ML algorithms that we are integrating into daily life, and AGI is human-level AI able to create it's own subjective experience.

I'm not OP, and frankly I don't really disagree with the characterization of ChatGPT as "fancy autocomplete". But...

I'm still in the process of reading this cover-to-cover, but Chapter 12.2 of Deep Learning: Foundations and Concepts by Bishop and Bishop explains how natural language transformers work, and then has a short section about LLMs. All of this is in the context of a detailed explanation of the fundamentals of deep learning. The book cites the original papers from which it is derived, most of which are on ArXiv. There's a nice copy on Library Genesis. It requires some multi-variable probability and statistics, and an assload of linear algebra, reviews of which are included.

So obviously when the CEO explains their product they're going to say anything to make the public accept it. Therefore, their word should not be trusted. However, I think that when AI researchers talk simply about their work, they're trying to shield people from the mathematical details. Fact of the matter is that behind even a basic AI is a shitload of complicated math.

At least from personal experience, people tend to get really aggressive when I try to explain math concepts to them. So they're probably assuming based on their experience that you would be better served by some clumsy heuristic explanation.

IMO it is super important for tech-inclined people interested in making the world a better place to learn the fundamentals and limitations of machine learning (what we typically call "AI") and bring their benefits to the common people. Clearly, these technologies are a boon for the wealthy and powerful, and like always, have been used to fuck over everyone else.

IMO, as it is, AI as a technology has inherent patterns that induce centralization of power, particularly with respect to the requirement of massive datasets, particularly for LLMs, and the requirement to understand mathematical fundamentals that only the wealthy can afford to go to school long enough to learn. However, I still think that we can leverage AI technologies for the common good, particularly by developing open-source alternatives, encouraging the use of open and ethically sourced datasets, and distributing the computing load so that people who can't afford a fancy TPU can still use AI somehow.

I wrote all this because I think that people dismiss AI because it is "needlessly" complex and therefore bullshit. In my view, it is necessarily complex because of the transformative potential it has. If and only if you can spare the time, then I encourage you to learn about machine learning, particularly deep learning and LLMs.

We use words to describe our thoughts and understanding. LLMs order words by following algorithms that predict what the user wants to hear. It doesn't understand the meaning or implications of the words it's returning.

It can tell you the definition of an apple, or how many people eat apples, or whatever apple data it was trained on, but it has no thoughts of it's own about apples.

That's the point that OOP was making. People confuse ordering words with understanding. It has no understanding about anything. It's a large language model - it's not capable of independent thought.

Umm penicillin? anaesthetic? the Haber process? the transistor? the microscope? steel?

I get it, the models are new and a bit exciting but GPT wont make it so you can survive surgery, or make rocks take the jobs of computers.

it is already a great tool for programmers. Which means programming anything, including new AI, will only go exponentially faster.

Yes to it being a tool. But right now all it can really do is bog standard stuff. Also have you read about that the use of Github Copilot seems to reduce the quality of code? This means we cannot yet rely on this type of technology. Again, it's a limited tool and that is it. At least for now.

Why is this the first step and not any of the other things that have been around for years?

We have logic reasoning in the form of prolog, bots that are fun to play against in computer games, computers that can win in chess and go against the best players in the world, and computer vision is starting to be useful.