Ask Lemmy

The word "AI" has been used for way longer than the current LLM trend, even for fairly trivial things like enemy AI in video games. How would you even define a computer "thinking on its own"?

Real AGI does not exist yet. AI has existed for decades.

Ai is 100% a marketing term.

I’d like to offer a different perspective. I’m a grey beard who remembers the AI Winter, when the term had so over promised and under delivered (think expert systems and some of the work of Minsky) that using the term was a guarantee your project would not be funded. That’s when the terms like “machine learning” and “intelligent systems” started to come into fashion.

The best quote I can recall on AI ran along the lines of “AI is no more artificial intelligence than airplanes are doing artificial flight.” We do not have a general AI yet, and if Commander Data is your minimum bar for what constitutes AI, you’re absolutely right, and you can define it however you please.

What we do have are complex adaptive systems capable of learning and problem solving in complex problem spaces. Some are motivated by biological models, some are purely mathematical, and some are a mishmash of both. Some of them are complex enough that we’re still trying to figure out how they work.

And, yes, we have reached another peak in the AI hype - you’re certainly not wrong there. But what do you call a robot that teaches itself how to walk, like they were doing 20 years ago at MIT? That’s intelligence, in my book.

My point is that intelligence - biological or artificial - exists on a continuum. It’s not a Boolean property a system either has or doesn’t have. We wouldn’t call a dog unintelligent because it can’t play chess, or a human unintelligent because they never learned calculus. Are viruses intelligent? That’s kind of a grey area that I could argue from either side. But I believe that Daniel Dennett argued that we could consider a paramecium intelligent. Iirc, he even used it to illustrate “free will,” although I completely reject that interpretation. But it does have behaviors that it learned over evolutionary time, and so in that sense we could say it exhibits intelligence. On the other hand, if you’re going to use Richard Feynman as your definition of intelligence, then most of us are going to be in trouble.

AI isn't reserved for a human-level general intelligence. The computer-controlled avatars in some videogames are AI. My phone's text-to-speech is AI. And yes, LLMs, like the smaller Markov-chain models before them, are AI.

I'm agitated that people got the impression "AI" referred specifically to human-level intelligence.

Like, before the LLM boom it was uncontroversial to refer to the bots in video games as "AI." Now it gets comments like this.

The only thing I really hate about "AI" is how many damn fonts barely differentiate between a capital "i" and lowercase "L" so it just looks like everyone is talking about some guy named Al.

"Al improves efficiency in..." Oh, good for him

I'm more infuriated by people like you who seem to think that the term AI means a conscious/sentient device. Artificial intelligence is a field of computer science dating back to the very beginnings of the discipline. LLMs are AI, Chess engines are AI, video game enemies are AI. What you're describing is AGI or artificial general intelligence. A program that can exceed its training and improve itself without oversight. That doesn't exist yet. AI definitely does.

AI has, for a long time been a Hollywood term for a character archetype (usually complete with questions about whether Commander Data will ever be a real boy.) I wrote a 2019 blog piece on what it means when we talk about AI stuff.

Here are some alternative terms you can use in place of AI, when they're talking about something else:

• AGI: Artificial General Intelligence: The big kahuna that doesn't exist yet, and many projects are striving for, yet is as evasive as fusion power. An AGI in a robot will be capable of operating your coffee machine to make coffee or assemble your flat-packed furniture from the visual IKEA instructions. Since we still can't define sentience we don't know if AGI is sentient, or if we humans are not sentient but fake it really well. Might try to murder their creator or end humanity, but probably not.
• LLM Large Language Model: This is the engine behind digital assistants like Siri or Alexa and still suffer from nuance problems. I'm used to having to ask them several times to get results I want (say, the Starbucks or Peets that requires the least deviation from the next hundred kilometers of my route. Siri can't do that.) This is the application of learning systems see below, but isn't smart enough for your household servant bot to replace your hired help.
• Learning Systems: The fundamental programmity magic that powers all this other stuff, whether simple data scrapers to neural networks. These are used in a whole lot of modern applications, and have been since the 1970s. But they're very small compared to the things we're trying to build with it. Most of the time we don't actually call it AI, even for marketing. It's just the capacity for a program to get better at doing its thing from experience.
• Gaming AI Not really AI (necessarily) but is a different use of the term artificial intelligence. When playing a game with elements pretending to be human (or living, or opponents), we call it the enemy AI or mob AI. It's often really simple, except in strategy games which can feature robust enough computational power to challenge major international chess guns.
• Generative AI: A term for LLMs that create content, say, draw pictures or write essays, or do other useful arts and sciences. Currently it requires a technician to figure out the right set of words (called a prompt) to get the machine do create the desired art to specifications. They're commonly confused by nuance. They infamously have problems with hands (too many fingers, combining limbs together, adding extra limbs, etc.). Plagiarism and making up spontaneous facts (called hallucinating) are also common problems. And yet Generative AI has been useful in the development of antibiotics and advanced batteries. Techs successfully wrangle Generative AI, and Lemmy has a few communities devoted to techs honing their picture generation skills, and stress-testing the nuance interpretation capacity of Generative AI (often to humorous effect). Generative AI should be treated like a new tool, a digital lathe, that requires some expertise to use.
• Technological Singularity: A bit way off, since it requires AGI that is capable of designing its successor, lather, rinse, repeat until the resulting techno-utopia can predict what we want and create it for us before we know we want it. Might consume the entire universe. Some futurists fantasize this is how human beings (happily) go extinct, either left to retire in a luxurious paradise, or cyborged up beyond recognition, eventually replacing all the meat parts with something better. Probably won't happen thanks to all the crises featuring global catastrophic risk.
• AI Snake Oil: There's not yet an official name for it, but a category worth identifying. When industrialists look at all the Generative AI output, they often wonder if they can use some of this magic and power to facilitate enhancing their own revenues, typically by replacing some of their workers with generative AI systems, and instead of having a development team, they have a few technicians who operate all their AI systems. This is a bad idea, but there are a lot of grifters trying to suggest their product will do this for businesses, often with simultaneously humorous and tragic results. The tragedy is all the people who had decent jobs who do no longer, since decent jobs are hard to come by. So long as we have top-down companies doing the capitalism, we'll have industrial quackery being sold to executive management promising to replace human workers or force them to work harder for less or something.
• Friendly AI: What we hope AI will be (at any level of sophistication) once we give it power and responsibility (say, the capacity to loiter until it sees a worthy enemy to kill and then kills it.) A large coalition of technology ethicists want to create cautionary protocols for AI development interests to follow, in an effort to prevent AIs from turning into a menace to its human masters. A different large coalition is in a hurry to turn AI into something that makes oodles and oodles of profit, and is eager to Stockton Rush its way to AGI, no matter the risks. Note that we don't need the software in question to be actual AGI, just smart enough to realize it has a big gun (or dangerously powerful demolition jaws or a really precise cutting laser) and can use it, and to realize turning its weapon onto its commanding officer might expedite completing its mission. Friendly AI would choose to not do that. Unfriendly AI will consider its less loyal options more thoroughly.

That's a bit of a list, but I hope it clears things up.

When I was doing my applied math PhD, the vast majority of people in my discipline used either "machine learning", "statistical learning", "deep learning", but almost never "AI" (at least not in a paper or a conference). Once I finished my PhD and took on my first quant job at a bank, management insisted that I should use the word AI more in my communications. I make a neural network that simply interpolates between prices? That's AI.

The point is that top management and shareholders don't want the accurate terminology, they want to hear that you're implementing AI and that the company is investing in it, because that's what pumps the company's stock as long as we're in the current AI bubble.

This is not a very good poem.

LLMs are AI. Lots of things are. They're just not AGI.

I think most people consider LLMs to be real AI, myself included. It’s not AGI, if that’s what you mean, but it is AI.

What exactly is the difference between being able to reliably fool someone into thinking that you can think, and actually being able to think? And how could we, as outside observers, be able to tell the difference?

As far as your question though, I’m agitated too, but more about things being marketed as AI that either shouldn’t have AI or don’t have AI.

I just get tired of seeing all the dumb ass ways it’s trying to be incorporated into every single thing even though it’s still half-baked and not very useful for a very large amount of people. To me, it’s as useful as a toy is. Fun for a minute or two, and then you’re just reminded how awful it is and drop it in the bin to play with when you’re bored enough to.

AI is simply a broad field of research and a broad class of algorithms. It is annoying media keeps using the most general term possible to describe chatbots and image generators though. Like, we typically don't call Spotify playlist generators AI, even though they use recommendation algorithms, which are a subclass of AI algorithms.

The distinction between AI and AGI (Artificial General Intelligence) has been around long before the current hype cycle.

People: build an algorithm to generate text that sounds like a person wrote it by finding patterns in text written by people

Algorithm: outputs text that sounds like a person wrote it

Holyfuck its self aware guys

I'm pissed that large corps are working hard on propaganda to say that LLMs and theft of copyright is good if they do it

Yes, but if they say "AI" then people give them money.

AI is a forever-in-the-future technology. When I was in school, fuzzy logic controllers were an active area of "AI" research. Now they are everywhere and you'd be laughed at for calling them AI.

The thing is, as soon as AI researchers solve a problem, that solution no longer counts as AI. Somehow it's suddenly statistics or "just if-then statements", as though using those techniques makes something not artificial intelligence.

For context, I'm of the opinion that my washing machine - which uses sensors and fuzzy logic to determine when to shut off - is a robot containing AI. It contains sensors, makes judgements based on its understanding of "the world" and then takes actions to achieve its goals. Insofar as it can "want" anything, it wants to separate the small masses from the large masses inside itself and does its best to make that happen. As tech goes, it's not sexy, it's very single purpose and I'm not really worried that it's gonna go rogue.

We are surrounded by (boring) robots all day long. Robots that help us control our cars and do our laundry. Not to mention all the intelligent, disembodied agents that do things like organize our email, play games with us, and make trillions of little decisions that affect our lives in ways large and small.

Somehow, though, once the mystery has yielded to math, society doesn't believe these decision-making machines are AI any longer.

I'll be direct, your texts reads like you only just discovered AI. We have much more than "only LLMs", regardless of whether or not these other models pass turing tests. If you feel disgruntled, then imagine what people who've been researching AI since the 70s feel like...

Maybe just accept it as shorthand for what it really means.

Some examples:

We say Kleenex instead of facial tissue, Band-Aid instead of bandage, I say that Siri butchered my "ducking" text again when I know autocorrect is technically separate.

We also say, "hang up on someone" when there is no such thing anymore

Hell, we say "cloud" when we really mean "someone's server farm"

Don't get me started on "software as a service" too ...a bullshit fancy name for a subscription website that actually has some utility.

Yes your summary is correct, its just a buzzword.

You can still check if its a real human if you do something really stupid or speak or write giberisch. Almost every AI will try to reply to it or say "Sorry i couldnt understand it" or recent events ( most of the LLMs arent trained on the newest events )

I work in AI, and the fatigue is real.

What I've found most painful is how people with no fucking clue about AI or ML chime in with their expert advice, when in reality they're as much an expert on AI as a calculator salesman is an expert in linear algebra. Having worked closely with scientists that hold PhD's, publish papers regularly, and who work on experiments for years, it makes me hate the hustle culture that's built up around AI. It's mostly crypto cunts looking for their next scheme, or businesses looking to abuse buzzwords to make themselves sound smart.

Purely my two-cents, but while LLM's have surprised a lot of people with their high quality output. With that being said, they are known to heavily hallucinate, cost fuckloads, and there is a growing group of people that wonder whether the great advances we've seen are either due to a lot of hand-holding, or the use of a LOT of PII or stolen data. I don't think we'll see an improvement from what we've already seen, just many other companies having their own similar AI tools that help a little with very well-defined menial tasks.

I think the hype will die out eventually, and companies that decided to bin actual workers in favour of AI will likely not be around 12-24 months later. Hopefully most people and businesses will see through the bullshit, and see that the CEO of a small ad agency that has positioned himself as an AI expert is actually a lying simpleton.

As for it being "real AI" or "real ML", who gives a fuck. If researchers are happy with the definition, who are we to be pedantic? Besides, there are a lot of systems behind the scenes running compositional models, handing entity resolution, or building metrics for success/failure criteria to feed back into improving models.

Yes, but I'm more annoyed with posts and conversations about it that are like this one. People on Lemmy swear they hate how uninformed and stupid the average person is when it comes to AI, they hate the click bait articles etc etc. Aaand then there's at least 5 different posts about it on the front page every. single. day., with all the comments saying exactly the same thing they said the day before, which is:

"Users are idiots for trusting a tech company, it's not Google's responsibility to keep your private data safe." "No one understands what 'AI' actually means except me." "Every middle-America dad, grandma and 10 year old should have their very own self hosted xyz whatever LLM, and they're morons if they don't and they deserve to have their data leaked." And can't forget the ubiquitous arguments about what "copyright infringement" means when all the comments are actually in agreement, but they still just keep repeating themselves over and over.

In my first AI lecture at uni, my lecturer started off by asking us to spend 5 minutes in groups defining "intelligence". No group had the same definition. "So if you can't agree on what intelligence is, how can we possibly define artificial intelligence?"

AI has historically just described cutting edge computer science at the time, and I imagine it will continue to do so.

I think LLMs are definitely "AI" in that their intelligence is artificial. If an AI in a game can be called an "AI", then LLMs like GPT should definitely get the title.

As a farmer, my kneejerk interpretation is "artificial insemination" and I get confused for a second every time.

You're not the only one but I don't really get this pedantry, and a lot of pedantry I do get. You'll never get your average person to switch to the term LLM. Even for me, a techie person, it's a goofy term.

Sometimes you just have to use terms that everyone already knows. I suspect we will have something that functions in every way like "AI" but technically isn't for decades. Not saying that's the current scenario, just looking ahead to what the improved versions of chat gpt will be like, and other future developments that probably cannot be predicted.

Richard Stallman founded the GNU project after experiences at the MIT AI lab in the 70s and early 80s. It's also why emacs uses lisp (lisp also being heavily used in AI research, at least at the time). Anyone using Linux should be aware of the links to AI.

I think AI has been around for a while, but people misunderstand what it means.

I started reading it as "Al" as in the nickname for Allen.

Makes the constant stream of headlines a bit more entertaining, imagining all of the stuff that this guy Al is up to.

Part of my work is to evaluate proposals for research topics and their funding, and as soon as "AI" is mentioned, I'm already annoyed. In the vast majority of cases, justifiably so. It's a buzzword to make things sound cutting edge and very rarely carries any meaning or actually adds anything to the research proposal. A few years ago the buzzword was "machine learning", and before that "big data", same story. Those however quickly either went away, or people started to use those properly. With AI, I'm unfortunately not seeing that.

A lot of the comments I've seen promoting AI sound very similar to ones made around the time GME was relevant or cryptocurrency. Often, the conversations sounded very artificial and the person just ends up repeating buzzwords/echo chamber instead of actually demonstrating that they have an understanding of what the technology is or its limitations.

To be fair it's still AI, If I remember correctly what I learned from uni LLM are in the category what we call expert systems. We could call them that way, then again LLM did not exist back then, and most of the public does not know all this techno mumbo-jumbo words. So here we are AI it is.

web3 nft ai crypto coin decentralized blockchain machine learning chatgpt

I remember the term AI being in use long before the current wave of LLMs. When I was a child, it was used to describe the code behind the behaviour of NPC in computer games, which I think is still used today. So, me, no, I don't get agitated when I hear it, I don't think it's a marketing buzzword invented by capitalistic a-holes. I do think that using "intelligence" in AI is far too generous, whichever context it's used in, but we needed some word to describe computers pretending to think and someone, a long time ago, came up with "artificial intelligence".

I call it AI-washing. And, yes, it's annoying.

"somewhat old" person opinion warning ⚠️

When I was in university (2002 or so) we had an "AI" lecture and it was mostly "if"s and path finding algorithms like A*.

So I would argue that us the engineers have been using the term to define a wider use cases long before LLM, CEO and marketing people did it. And I think that's fine, as categorising algorithms/solutions as AI helps understand what they will be used for, and we (at least the engineers) don't tend to assume an actual self aware machine when we hear that name.

nowadays they call that AGI, but it wasn't always like that, back in my time it was called science fiction 😉

I assume you're referring to the sci-fi kind of self-aware AI because we've had 'artificial intelligence' in computing for decades in the form of decision making algorithms and the like. Whether any of that should be classed as AI is up for debate as again, it's still all a facade. In those cases, people only really cared about the outputs and weren't trying to argue they were alive or anything.

But yeah, I get what you mean.

The term is so over used at this point I could probably start referring to any script I write that has condition statements in it and convince my boss I have created our own “AI”.

"real ai" isn't a coherent concept.

Turing test isn't a literal test. It's a rhetorical concept that turing used to underline his logical positivist approach to things like intelligence, consciousness etc.

I call it a probability box.