We really need to stop calling things “AI” like it’s an algorithm. There’s image recognition, collective intelligence, neural networks, path finding, and pattern recognition, sure, and they’ve all been called AI, but functionally they have almost nothing to do with each other.
For computer scientists this year has been a sonofabitch to communicate through.
But “AI” is the umbrella term for all of them. What you said is the equivalent of saying:
we really need to stop calling things “vehicles”. There’s cars, trucks, airplanes, submarines, and space shuttles and they’ve all been called vehicles, but functionally they have almost nothing to do with each other
All of the things you’ve mentioned are correctly referred to as AI, and since most people do not understand the nuances of neural networks vs hard coded algorithms (and anything in-between), AI is an acceptable term for something that demonstrates results that comes about from a computer “thinking” and making shaved intelligent decisions.
Btw, just about every image recognition system out there is a neural network itself or has a neural network in the processing chain.
No. No AI is NOT the umbrella term for all of them.
No computer scientist will ever genuinely call basic algorithmic tasks “AI”. Stop saying things you literally do not know.
We are not talking about what what the word means to normies colloquially. We’re talking about what it actually means. The entire point it is a separate term from those other things.
Engineers would REALLY appreciate it if marketing morons would stop misapplying terminology just to make something sound cooler… NONE of those things are “AI”. That’s the fucking point. Marketing gimmicks should not get to choose our terms. (as much as they still do)
If I pull up to your house on a bicycle and tell you, “quickly, get in my vehicle so I can drive us to the store.” You SHOULD look at that person weirdly: They’re treating a bicycle like it’s a car capable of getting on the freeway with passengers.
What I’ve learned as a huge nerd is that people will take a term and use it as an umbrella term for shit and they’re always incorrect but there’s never any point in correcting the use because that’s the way the collective has decided words work and it’s how they will work.
Now the collective has decided that AI is an umbrella term for executing “more complex tasks” which we cannot understand the technical workings of but need to get done.
Sometimes, but there are many cases where the nerds win. Like with technology. How many times do we hear old people misuse terms because they don’t care about the difference just for some young person to laugh and make fun of their lack of perspective?
I’ve seen it quite a lot, and I have full confidance it will happen here so long as an actual generalized intelligence comes along to show everyone the HUGE difference every nerd talks about.
This is in fact how common language works, and also how jargon develops. No one in this thread outside of the specific people pointing out the problem cares what it is beyond the colloquial use, keep jargon to the in group, or you’ll just alienate the out-group and your entire point will be missed.
No computer scientist will ever genuinely call basic algorithmic tasks “AI”. Stop saying things you literally do not know.
Speak for yourself. Many of us fought that battle literally years ago and then accepted reality and moved on with our lives. Show me an actual computer scientist still hung up on this little bit of not-so-new-anymore language and I’ll show you a dying curmudgeon who has let the world pass them by. We frequently use AI to refer to these technologies that we have today and we’ve started to use more descriptive language such as post-singularity AI or Artificial General Intelligence (AGI).
Hard agree. I don’t consider myself a “computer scientist”, but I do have a CS degree. The public use of AI is so far gone it’s just what it is now. I still wouldn’t consider path finding AI, but when you say an AI image creator, or AI chat bot it gets the point across well enough since we all know what is meant.
Calm down , language is fluid, you may not like it, but if enough people start using it as an umbrella term, that is what it’s colloquially and eventually officially going to be soon. You can’t expect to have such hard set rules this early on in the technology, it’s foolish
To be fair, AI was coined to mean programs written in LISP and it changes every time new techniques are developed. It’s definitely just a marketing term, but for grant money.
You’re talking in a forum to a bunch of normies using words colloquially, or to a bunch of media buffoons who report to nornies who are familiar with colloquial terms. I get your point if you’re talking to engineers, but you’re not
That is completely and utterly a separate issue. These aren’t words being changed over time. These are words being directly misapplied by morons, NOT for any ironic effect.
People mean it when they “misuse” literally. People who misuse AI don’t know what AI is. This is a technical term being misused. Not a normal word being redefined.
For a different word, “narcissism” DOES NOT magically mean, “a mean person” just because morons misuse a technical term. Stop being a piece of shit that wants to sound smart and start using terms correctly or not at all.
I just think you seem way more angry about this than you should be. It’s not really something to pop a blood vessel over. And “literally” becoming “figuratively” was also because of the misuse by morons. The fact one is a technical term is irrelevant. The not-as-educated masses water down language, particularly “technical” language because of course the general public aren’t going to know the nuances. But it’s not like most of them are talking about any of this stuff on a level where those nuances matter. Referring to the general field of “computers kinda thinking like people” as AI gets the point across for them, and it’s not hurting you. So chill.
You’re describing jargon vs colloquial use. If you’re talking to your engineer buddy, yeah, use the terms properly or be prepared to offer clarification, because in that context it’s pretty important. If you’re talking to a psychiatrist, same thing for narcissist.
When it comes to general public, people will use words however they’re most commonly used, and that’s perfectly fine. The average person doesn’t know, can’t be expected to learn, and has no use for knowing the definition of jargon that’s outside of their day-to-day use.
If the use of colloquial terms is causing you or someone else confusion or losing clarity, ask clarifying questions. That’s how professionals or just more knowledgeable people on the subject in general, have had to interface with the average person for like… How long have we had language?
You’re smart right? So, who’s there more of, normies or computer scientists? Just make the tech, if that really is what you do, but marketing and the masses are always going to decide what we call stuff not some cartoonist engineer.
Uhhhh who do you think defines these specialized words in the first place? Not normies. That is the dumbest shit I’ve ever heard, thanks for the laugh.
I’m pleased you are entertained. But being correct doesn’t make you any less wrong. I’m sorry that you don’t understand how language works. Now go build us some more toys.
In general conversation? The people there are more of define it lol. In a professional setting yeah, be specific, but… Wait, where are we? Oh the fucking comments section on lemmy. Pretty much the exact opposite of a professional setting. Use the words how the people around you are using it, or you’ll be misunderstood and have to explain yourself.
While this is true, I think of AI in the sci fi sense of a programmed machine intelligence rivaling human problem solving, communication, and opinion forming. Everything else to me is ML.
But like Turing thought, how can we really tell the difference
Turing’s question wasn’t a philosophical one. It was a literal one, that he tried to answer.
What the person said is NOT true. Nobody like Turing would EVER call those things AI, because they are very specifically NOT any form of “intelligence”. Fooling a layman in to mislabeling something is not the same as developing the actual thing that’d pass a Turing test.
What you’re referring to in movies is properly known as Artificial General Intelligence (AGI).
AI is correctly applied to systems that process in a “biologically similar” fashion. Basically something a human or “smart” animal could do. Things like object detection, natural language processing, facial recognition, etc, are things you can’t program (there’s more to facial recognition, but I’m simplifying for this discussion) and they need to be trained via a neural network. And that process is remarkably similar to how biological systems learn and work.
Machine learning, on the other hand, are processes that are intelligent but are not intrinsically “human”. A good example is song recommendations. The more often you listen to a genre of music, the more likely you are to enjoy other songs in that genre. So a system can count the number of songs you listen to the most in a specific genre, and then recommend that genre more than others. Fairly straightforward to program and doesn’t require any training, yet it gets better the more you use it.
How is my comment “gatekeeping” by any stretch of the defintion? I had one comment and the one making jest that you replied to. I only asked that there should be a catch all term and provided examples to go with it. How is that gatekeeping…?
It’s more to due with social media tropes. Someone sees a downvoted comment and does the same without even reading.
Edit and more proof it has nothing to do with the stuff you claimed, it’s now upvoted since the initial wave of people have stopped and people who care to read the meat of the comments now have and have established balance.
You’re right, but so is the previous poster. Actual AI doesn’t exist yet, and when/if it does it’s going to confuse the hell out of people who don’t get the hype over something we’ve had for years.
But calling things like machine learning algorithms “AI” definitely isn’t going away… we’ll probably just end up making a new term for it when it actually becomes a thing… “Digital Intelligence” or something. /shrug.
I dunno… I’ve heard that argument, but when something gives you >1000 answers, among which the correct answer might be buried somewhere, and a human is paid to dig through it and return something that looks vaguely presentable, is that really “intelligence”, of any sort?
Aka, 1 + 1 = 13, which is a real result that AI can and almost certainly has recently offer(ed).
People are right to be excited about the potential that generative AI offers in the future, but we are far from that atm. Also it is vulnerable to misinformation presented in the training data - though some say that that process might even affect humans too (I know, you are shocked, right? well, hopefully not that shocked:-P).
Oh wait, nevermind I take it all back: I forgot that Steven Huffman / Elon Musk / etc. exist, and if that is considered intelligence, then AI has definitely passed that level of Turing equivalence, so you’re absolutely right, erstatz it is, apparently!?
ChatGPT was caught, and I think later admitted, to not actually using fully automated processes to determine those answers, iirc. Instead, a real human would curate the answers first before they went out. That human might reject answers to a question like “Computer: what is 1+1?” ten times before finally accepting one of the given answers (“you’re mother”, hehe with improper apostrophe intact:-P). So really, when you were asking for an “AI answer”, what you were asking was another human on the other end of that conversation!!!
Then again, I think that was a feature for an earlier version of the program, that might no longer be necessary? On the other hand, if they SAY that they aren’t using human curation, but that is also what they said earlier before they admitted that they had lied, do we really believe it? Watch any video of these “tech Bros” and it’s obvious in less than a minute - these people are slimy.
And to some extent it doesn’t matter bc you can download some open source AI programs and run them yourself, but in general from what I understand, when people say things nowadays like “this was made from an AI”, it seems like it is always a hand-picked item from among the set of answers returned. So like, “oooh” and “aaaahhhhh” and all that, that such a thing could come from AI, but it’s not quite the same thing as simply asking a computer for an answer and it returning the correct answer right away! “1+1=?” giving the correct answer of 13 is MUCH less impressive when you find that out of a thousand attempts at asking, it was only returned a couple times. And the situation gets even worse(-r) when you find out that ChatGPT has been getting stupider(-est?) for awhile now - https://www.defenseone.com/technology/2023/07/ai-supposed-become-smarter-over-time-chatgpt-can-become-dumber/388826/.
So reading through your post and the article, I think you’re a bit confused about the “curated response” thing. I believe what they’re referring to is the user ability to give answers a “good answer” or “bad answer” flag that would then later be used for retraining. This could also explain the AIs drop in quality, of enough people are upvoting bad answers or downvoting good ones.
The article also describes “commanders” reviewing and having the code team be responsive to changing the algorithm. Again this isn’t picking responses for the AI. Instead ,it’s reviewing responses it’s given and deciding if they’re good or bad, and making changes to the algorithm to get more accurate answers in the future.
I have not heard anything like what you’re describing, with real people generating the responses real time for gpt users. I’m open to being wrong, though, if you have another article.
I might be guilty of misinformation here - perhaps it was a forerunner to ChatGPT, or even a different (competing) chatbot entirely, where they would read an answer from the machine before deciding whether to send it on to the end user, whereas the novelty of ChatGPT was in throwing off such shackles present in an older incarnation? I do recall a story along the lines that I mentioned, but I cannot find it now so that lends some credence to that thought. In any case it would have been multiple generations behind the modern ones, so you are correct that it is not so relevant anymore.
There’s no way that’s the case now, the answers are generated way too quickly for a human to formulate. I can certainly believe it did happen at one point.
Yes, and the fact that the quality suddenly declined awhile back - e.g. that article I linked to explained more - tracks along with those lines as well: when humans were curating the answers it took longer, whereas now the algorithm is unchained, hence able to move faster, and yet with far less accuracy than before.
This problem was kinda solved by adding AGI term meaning “AI but not what is now AI, what we imagined AI to be”
Not going to say that this helps with confusion much 😅 and to be fair, stuff like autocomplete in office soft was called AI long time ago but it was far from LLMs of now
Enemies in Doom have AI. We’ve been calling simple algorythms in a handful lines of code AI for a long time, the trend has nothing to do with languege models etc.
Computer vision is AI. If they literally want a robot eye to scan their cluttered pantry and figure out what is there, that’ll require some hefty neural net.
Edit: seeing these downvotes and surprised at the tech illiteracy on lemmy. I thought this was a better informed community. Look for computer vision papers in CVPR, IJCNN, and AAAI and try to tell me that being able to understand the 3D world isn’t AI.
Computer vision is scanning the differentials of an image and determining the statistical likelihood of two three-dimensional objects being the same base mesh from a different angle, then making a boolean decision on it. It requires a database, not a neutral net, though sometimes they are used.
A neutral net is a tool used to compare an input sequence to previous reinforced sequences and determine a likely ideal output sequence based on its training. It can be applied, carefully, for computer vision. It usually actually isn’t to any significant extent; we were identifying faces from camera footage back in the 90s with no such element in sight. Computer vision is about differential geometry.
Computer vision deals with how computers can gain high level understanding of images and videos. It involves much more than just object reconstruction. And more importantly, neural networks are a core component is just about any computer vision application since deep learning took off in the 2010s. Most computer vision is powered by some convolutional neural network or another.
Your comment contains several misconceptions and overlooks the critical role of neural networks, particularly CNNs, which are fundamental to most contemporary computer vision applications.
Thanks, you saved me the trouble of writing out a rant. I wonder if the other guy is actually a computer scientist or just a programmer who got a CS degree. Imagine attending a CV track at AAAI or the whole of CVPR and then saying CV isn’t a sub field of AI.
I imagine it’s because all of these technologies combine to make a sci-fi-esque computer assistant that talks to you, and most pop culture depictions of AI are just computer assistants that talk to you. The language already existed before the technology, it already took root before we got the chance to call it anything else.
Computer science involves all sciences of computing. It has materials science, logics, maths galore, just to do basic circuitry and chip design. It spirals on and on and on to get a real computer.
The point is it is a culmination of MANY different disciplines, and the people who think it’s only “this” or “that” are demonstrating their great lack of knowledge on the subject.
It is a generic term because it takes MANY different things to complete the picture. Pidgeonholing things when you do not even understand them is only an excercise of ignorant stereotyping.
Language is fluid, and there is plenty of terminology that is dumb or imprecise to someone in the field, but A-ok to the wider populace. “Cloud” is also not actually a formation of water droplets, but someone’s else’s datacenter, but to some people the cloud is everything from Gmail to AWS.
If I say AI today and most people associate the same thing with it (these days that usually means generative AI
, i.e. mostly diffusion or transformer models) then that’s fine for me. Call it Plumbus for all I care.
Those are all very specific intelligences. The goal is to unite them all under a so-called general intelligence. You’re right, that’s the dream, but there are many steps along the way that are fairly called intelligence.
We really need to stop calling things “AI” like it’s an algorithm. There’s image recognition, collective intelligence, neural networks, path finding, and pattern recognition, sure, and they’ve all been called AI, but functionally they have almost nothing to do with each other.
For computer scientists this year has been a sonofabitch to communicate through.
But “AI” is the umbrella term for all of them. What you said is the equivalent of saying:
All of the things you’ve mentioned are correctly referred to as AI, and since most people do not understand the nuances of neural networks vs hard coded algorithms (and anything in-between), AI is an acceptable term for something that demonstrates results that comes about from a computer “thinking” and making
shavedintelligent decisions.Btw, just about every image recognition system out there is a neural network itself or has a neural network in the processing chain.
Edit: fixed an autocorrect typo
No. No AI is NOT the umbrella term for all of them.
No computer scientist will ever genuinely call basic algorithmic tasks “AI”. Stop saying things you literally do not know.
We are not talking about what what the word means to normies colloquially. We’re talking about what it actually means. The entire point it is a separate term from those other things.
Engineers would REALLY appreciate it if marketing morons would stop misapplying terminology just to make something sound cooler… NONE of those things are “AI”. That’s the fucking point. Marketing gimmicks should not get to choose our terms. (as much as they still do)
If I pull up to your house on a bicycle and tell you, “quickly, get in my vehicle so I can drive us to the store.” You SHOULD look at that person weirdly: They’re treating a bicycle like it’s a car capable of getting on the freeway with passengers.
What I’ve learned as a huge nerd is that people will take a term and use it as an umbrella term for shit and they’re always incorrect but there’s never any point in correcting the use because that’s the way the collective has decided words work and it’s how they will work.
Now the collective has decided that AI is an umbrella term for executing “more complex tasks” which we cannot understand the technical workings of but need to get done.
Sometimes, but there are many cases where the nerds win. Like with technology. How many times do we hear old people misuse terms because they don’t care about the difference just for some young person to laugh and make fun of their lack of perspective?
I’ve seen it quite a lot, and I have full confidance it will happen here so long as an actual generalized intelligence comes along to show everyone the HUGE difference every nerd talks about.
But it will be called something different so almost nobody will notice that they now should see the difference
This is in fact how common language works, and also how jargon develops. No one in this thread outside of the specific people pointing out the problem cares what it is beyond the colloquial use, keep jargon to the in group, or you’ll just alienate the out-group and your entire point will be missed.
Yep
Speak for yourself. Many of us fought that battle literally years ago and then accepted reality and moved on with our lives. Show me an actual computer scientist still hung up on this little bit of not-so-new-anymore language and I’ll show you a dying curmudgeon who has let the world pass them by. We frequently use AI to refer to these technologies that we have today and we’ve started to use more descriptive language such as post-singularity AI or Artificial General Intelligence (AGI).
Hard agree. I don’t consider myself a “computer scientist”, but I do have a CS degree. The public use of AI is so far gone it’s just what it is now. I still wouldn’t consider path finding AI, but when you say an AI image creator, or AI chat bot it gets the point across well enough since we all know what is meant.
Calm down , language is fluid, you may not like it, but if enough people start using it as an umbrella term, that is what it’s colloquially and eventually officially going to be soon. You can’t expect to have such hard set rules this early on in the technology, it’s foolish
OP was not only speaking about “AI”. You are strawmanning what I said in order to be correct.
😔
To be fair, AI was coined to mean programs written in LISP and it changes every time new techniques are developed. It’s definitely just a marketing term, but for grant money.
Xerox, Velcro, and Google agree with you. To bad the general public doesn’t.
Extra song from Velcro here that agrees with what you’re saying
You’re talking in a forum to a bunch of normies using words colloquially, or to a bunch of media buffoons who report to nornies who are familiar with colloquial terms. I get your point if you’re talking to engineers, but you’re not
Yeah, and these days “literally” means “figuratively” whether I like it or not. Find a different hill to die on.
That is completely and utterly a separate issue. These aren’t words being changed over time. These are words being directly misapplied by morons, NOT for any ironic effect.
People mean it when they “misuse” literally. People who misuse AI don’t know what AI is. This is a technical term being misused. Not a normal word being redefined.
For a different word, “narcissism” DOES NOT magically mean, “a mean person” just because morons misuse a technical term. Stop being a piece of shit that wants to sound smart and start using terms correctly or not at all.
I just think you seem way more angry about this than you should be. It’s not really something to pop a blood vessel over. And “literally” becoming “figuratively” was also because of the misuse by morons. The fact one is a technical term is irrelevant. The not-as-educated masses water down language, particularly “technical” language because of course the general public aren’t going to know the nuances. But it’s not like most of them are talking about any of this stuff on a level where those nuances matter. Referring to the general field of “computers kinda thinking like people” as AI gets the point across for them, and it’s not hurting you. So chill.
Notice how OP was speaking about more than “AI”.
I did notice, and my point still stands.
Notice how the person you replied to never once mentioned AI, and was talking in pretty broad terms.
You’re describing jargon vs colloquial use. If you’re talking to your engineer buddy, yeah, use the terms properly or be prepared to offer clarification, because in that context it’s pretty important. If you’re talking to a psychiatrist, same thing for narcissist.
When it comes to general public, people will use words however they’re most commonly used, and that’s perfectly fine. The average person doesn’t know, can’t be expected to learn, and has no use for knowing the definition of jargon that’s outside of their day-to-day use.
If the use of colloquial terms is causing you or someone else confusion or losing clarity, ask clarifying questions. That’s how professionals or just more knowledgeable people on the subject in general, have had to interface with the average person for like… How long have we had language?
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That’s just like your opinion, man - The Dude
You’re smart right? So, who’s there more of, normies or computer scientists? Just make the tech, if that really is what you do, but marketing and the masses are always going to decide what we call stuff not some
cartoonistengineer.Uhhhh who do you think defines these specialized words in the first place? Not normies. That is the dumbest shit I’ve ever heard, thanks for the laugh.
I’m pleased you are entertained. But being correct doesn’t make you any less wrong. I’m sorry that you don’t understand how language works. Now go build us some more toys.
In general conversation? The people there are more of define it lol. In a professional setting yeah, be specific, but… Wait, where are we? Oh the fucking comments section on lemmy. Pretty much the exact opposite of a professional setting. Use the words how the people around you are using it, or you’ll be misunderstood and have to explain yourself.
They are the same picture.
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While this is true, I think of AI in the sci fi sense of a programmed machine intelligence rivaling human problem solving, communication, and opinion forming. Everything else to me is ML.
But like Turing thought, how can we really tell the difference
Turing’s question wasn’t a philosophical one. It was a literal one, that he tried to answer.
What the person said is NOT true. Nobody like Turing would EVER call those things AI, because they are very specifically NOT any form of “intelligence”. Fooling a layman in to mislabeling something is not the same as developing the actual thing that’d pass a Turing test.
What you’re referring to in movies is properly known as Artificial General Intelligence (AGI).
AI is correctly applied to systems that process in a “biologically similar” fashion. Basically something a human or “smart” animal could do. Things like object detection, natural language processing, facial recognition, etc, are things you can’t program (there’s more to facial recognition, but I’m simplifying for this discussion) and they need to be trained via a neural network. And that process is remarkably similar to how biological systems learn and work.
Machine learning, on the other hand, are processes that are intelligent but are not intrinsically “human”. A good example is song recommendations. The more often you listen to a genre of music, the more likely you are to enjoy other songs in that genre. So a system can count the number of songs you listen to the most in a specific genre, and then recommend that genre more than others. Fairly straightforward to program and doesn’t require any training, yet it gets better the more you use it.
As far as taking scifi terms for real things, at least this one is somewhat close. I’m still pissed about hover boards. And Androids are right out!
I like how you stole my comment and I’m downvoted.
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How is my comment “gatekeeping” by any stretch of the defintion? I had one comment and the one making jest that you replied to. I only asked that there should be a catch all term and provided examples to go with it. How is that gatekeeping…?
It’s more to due with social media tropes. Someone sees a downvoted comment and does the same without even reading.
Edit and more proof it has nothing to do with the stuff you claimed, it’s now upvoted since the initial wave of people have stopped and people who care to read the meat of the comments now have and have established balance.
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I didn’t steal anything. When I posted my comment there were only two other comments in the whole thread.
I know, it’s just funny how two very similar thoughts can be be taking two different ways deepening on who sees it first and interacts with it.
I think you’re fighting a losing battle.
You’re right, but so is the previous poster. Actual AI doesn’t exist yet, and when/if it does it’s going to confuse the hell out of people who don’t get the hype over something we’ve had for years.
But calling things like machine learning algorithms “AI” definitely isn’t going away… we’ll probably just end up making a new term for it when it actually becomes a thing… “Digital Intelligence” or something. /shrug.
It isn’t human-level, but you could argue it’s still intelligence of a sort, just erstatz
I dunno… I’ve heard that argument, but when something gives you >1000 answers, among which the correct answer might be buried somewhere, and a human is paid to dig through it and return something that looks vaguely presentable, is that really “intelligence”, of any sort?
Aka, 1 + 1 = 13, which is a real result that AI can and almost certainly has recently offer(ed).
People are right to be excited about the potential that generative AI offers in the future, but we are far from that atm. Also it is vulnerable to misinformation presented in the training data - though some say that that process might even affect humans too (I know, you are shocked, right? well, hopefully not that shocked:-P).
Oh wait, nevermind I take it all back: I forgot that Steven Huffman / Elon Musk / etc. exist, and if that is considered intelligence, then AI has definitely passed that level of Turing equivalence, so you’re absolutely right, erstatz it is, apparently!?
What’s the human digging through answers thing? I haven’t heard anything about that.
ChatGPT was caught, and I think later admitted, to not actually using fully automated processes to determine those answers, iirc. Instead, a real human would curate the answers first before they went out. That human might reject answers to a question like “Computer: what is 1+1?” ten times before finally accepting one of the given answers (“you’re mother”, hehe with improper apostrophe intact:-P). So really, when you were asking for an “AI answer”, what you were asking was another human on the other end of that conversation!!!
Then again, I think that was a feature for an earlier version of the program, that might no longer be necessary? On the other hand, if they SAY that they aren’t using human curation, but that is also what they said earlier before they admitted that they had lied, do we really believe it? Watch any video of these “tech Bros” and it’s obvious in less than a minute - these people are slimy.
And to some extent it doesn’t matter bc you can download some open source AI programs and run them yourself, but in general from what I understand, when people say things nowadays like “this was made from an AI”, it seems like it is always a hand-picked item from among the set of answers returned. So like, “oooh” and “aaaahhhhh” and all that, that such a thing could come from AI, but it’s not quite the same thing as simply asking a computer for an answer and it returning the correct answer right away! “1+1=?” giving the correct answer of 13 is MUCH less impressive when you find that out of a thousand attempts at asking, it was only returned a couple times. And the situation gets even worse(-r) when you find out that ChatGPT has been getting stupider(-est?) for awhile now - https://www.defenseone.com/technology/2023/07/ai-supposed-become-smarter-over-time-chatgpt-can-become-dumber/388826/.
So reading through your post and the article, I think you’re a bit confused about the “curated response” thing. I believe what they’re referring to is the user ability to give answers a “good answer” or “bad answer” flag that would then later be used for retraining. This could also explain the AIs drop in quality, of enough people are upvoting bad answers or downvoting good ones.
The article also describes “commanders” reviewing and having the code team be responsive to changing the algorithm. Again this isn’t picking responses for the AI. Instead ,it’s reviewing responses it’s given and deciding if they’re good or bad, and making changes to the algorithm to get more accurate answers in the future.
I have not heard anything like what you’re describing, with real people generating the responses real time for gpt users. I’m open to being wrong, though, if you have another article.
I might be guilty of misinformation here - perhaps it was a forerunner to ChatGPT, or even a different (competing) chatbot entirely, where they would read an answer from the machine before deciding whether to send it on to the end user, whereas the novelty of ChatGPT was in throwing off such shackles present in an older incarnation? I do recall a story along the lines that I mentioned, but I cannot find it now so that lends some credence to that thought. In any case it would have been multiple generations behind the modern ones, so you are correct that it is not so relevant anymore.
There’s no way that’s the case now, the answers are generated way too quickly for a human to formulate. I can certainly believe it did happen at one point.
Yes, and the fact that the quality suddenly declined awhile back - e.g. that article I linked to explained more - tracks along with those lines as well: when humans were curating the answers it took longer, whereas now the algorithm is unchained, hence able to move faster, and yet with far less accuracy than before.
This problem was kinda solved by adding AGI term meaning “AI but not what is now AI, what we imagined AI to be”
Not going to say that this helps with confusion much 😅 and to be fair, stuff like autocomplete in office soft was called AI long time ago but it was far from LLMs of now
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Enemies in Doom have AI. We’ve been calling simple algorythms in a handful lines of code AI for a long time, the trend has nothing to do with languege models etc.
I’m not fighting, I’m just disgusted. As someone’s wise grandma once said, “[BoastfulDaedra], you are not the fuckface whisperer.”
AI = “magic”, or like “synergy” and other buzzwords that will soon become bereft of all meaning as a result of people abusing it.
There’s whole countries that refer to the entire internet itself as Facebook, once something takes root it ain’t going anywhere
Computer vision is AI. If they literally want a robot eye to scan their cluttered pantry and figure out what is there, that’ll require some hefty neural net.
Edit: seeing these downvotes and surprised at the tech illiteracy on lemmy. I thought this was a better informed community. Look for computer vision papers in CVPR, IJCNN, and AAAI and try to tell me that being able to understand the 3D world isn’t AI.
You’re very wrong.
Computer vision is scanning the differentials of an image and determining the statistical likelihood of two three-dimensional objects being the same base mesh from a different angle, then making a boolean decision on it. It requires a database, not a neutral net, though sometimes they are used.
A neutral net is a tool used to compare an input sequence to previous reinforced sequences and determine a likely ideal output sequence based on its training. It can be applied, carefully, for computer vision. It usually actually isn’t to any significant extent; we were identifying faces from camera footage back in the 90s with no such element in sight. Computer vision is about differential geometry.
Computer vision deals with how computers can gain high level understanding of images and videos. It involves much more than just object reconstruction. And more importantly, neural networks are a core component is just about any computer vision application since deep learning took off in the 2010s. Most computer vision is powered by some convolutional neural network or another.
Your comment contains several misconceptions and overlooks the critical role of neural networks, particularly CNNs, which are fundamental to most contemporary computer vision applications.
Thanks, you saved me the trouble of writing out a rant. I wonder if the other guy is actually a computer scientist or just a programmer who got a CS degree. Imagine attending a CV track at AAAI or the whole of CVPR and then saying CV isn’t a sub field of AI.
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I imagine it’s because all of these technologies combine to make a sci-fi-esque computer assistant that talks to you, and most pop culture depictions of AI are just computer assistants that talk to you. The language already existed before the technology, it already took root before we got the chance to call it anything else.
Shouldn’t there be a catch all term to explain the broader scope of the specifics?
Science is a broad term for multiple different studies, vehicle is a broad term for cars and trucks.
Machine learning?
Glorified chatbots. Tops. But definitely not something with any kind of intelligence.
Yesterday I prompted gpt4 to convert a power shell script to Haskell. It did it in one shot. This happens more and more frequently for me.
I don’t want to oversell llms, but you are definitely underselling them.
Is that not a type of AI already?
Well, there’s an argument over not calling machine learning AI in this very thread, so… ¯\_(ツ)_/¯
So why suggest it for the catch all term for AI when it’s only one portion of the argument itself? Such a strange suggestion,
“Computer Science”
So people think of programming instead?
Computer science involves all sciences of computing. It has materials science, logics, maths galore, just to do basic circuitry and chip design. It spirals on and on and on to get a real computer.
The point is it is a culmination of MANY different disciplines, and the people who think it’s only “this” or “that” are demonstrating their great lack of knowledge on the subject.
It is a generic term because it takes MANY different things to complete the picture. Pidgeonholing things when you do not even understand them is only an excercise of ignorant stereotyping.
That’s too broad, there’s a reason there is already computer science, science itself, science of chemistry/physics/biology/space etc.
Language is fluid, not accepting change just shows how ignorant you are of the broader aspects of the world.
Language is fluid, and there is plenty of terminology that is dumb or imprecise to someone in the field, but A-ok to the wider populace. “Cloud” is also not actually a formation of water droplets, but someone’s else’s datacenter, but to some people the cloud is everything from Gmail to AWS.
If I say AI today and most people associate the same thing with it (these days that usually means generative AI , i.e. mostly diffusion or transformer models) then that’s fine for me. Call it Plumbus for all I care.
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Those are all very specific intelligences. The goal is to unite them all under a so-called general intelligence. You’re right, that’s the dream, but there are many steps along the way that are fairly called intelligence.