Bullshit. These people know exactly how LLMs work.
LLMs reproduce the form of language without any meaning being transmitted. That’s called parroting.
Comment on I wish I was as bold as these authors.
JackGreenEarth@lemm.ee 6 days agoWhenever any advance is made in AI, AI critics redefine AI so its not achieved yet according to their definition. Deep Blue Chess was an AI, an artificial intelligence. If you mean human or beyond level general intelligence, you’re probably talking about AGI or ASI (general or super intelligence, respectively).
And the second comment about LLMs being parrots arises from a misunderstanding of how LLMs work. The early chatbots were actual parrots, saying prewritten sentences that they had either been preprogrammed with or got from their users. LLMs work differently, statistically predicting the next token (roughly equivalent to a word) based on all those that came before it, and parameters finetuned during training. Their temperature can be changed to give more or less predictable output, and as such, they have the potential for actually original output, unlike their parrot predecessors.
Prunebutt@slrpnk.net 6 days ago
fartsparkles@sh.itjust.works 6 days ago
[deleted]Prunebutt@slrpnk.net 6 days ago
AI is a marketing buzzword. When someone claims that so-called “AGI” is close, they’re either doing marketing or falling for marketing.
Since you didn°t address the “parroting” part, I’m assuming that you retract yopr point.
lunarul@lemmy.world 6 days ago
LLMs reproduce the form of language without any meaning being transmitted. That’s called parroting.
Even if an AGI is going to be achieved, there will be people calling it parroting by your definition. That’s the Chinese room argument
Prunebutt@slrpnk.net 6 days ago
You’re moving the goalposts.
lunarul@lemmy.world 6 days ago
Me? How can I move goalposts in a single sentence? We’ve had no previous conversation… And I’m not agreeing with the previous poster either…
Tar_alcaran@sh.itjust.works 6 days ago
LLMs work differently, statistically predicting the next token (roughly equivalent to a word) based on all those that came before it, and parameters finetuned during training.
Which is what a parrot does.
naevaTheRat@lemmy.dbzer0.com 6 days ago
Yeah this is the exact criticism. They recombine language pieces without really doing language. The end result looks like language, but it lacks any of the important characteristics of language such as meaning and intention.
If I say “Two plus two is four” I am communicating my belief about mathematics.
If an llm emits “two plus two is four” it is outputting a stochastically selected series of tokens linked by probabilities derived from training data. If the statement is true or false then that is accidental.
Hence, stochastic parrot.
ignotum@lemmy.world 6 days ago
If i train an LLM to do math, for the training data i generate
a+b=cstatements, never showing it the same one twice.It would be pointless for it to “memorize” every single question and answer it gets since it would never see that question again. The only way it would be able to generate correct answers would be if it gained a concept of what numbers are, and how the add operation operates on them to create a new number.
Rather than memorizing and parroting it would have to actually understand it in order to generate responses.It’s called generalization, it’s why large amounts of data is required (if you show the same data again and again then memorizing becomes a viable strategy)
If I say “Two plus two is four” I am communicating my belief about mathematics.
Seems like a pointless distinction, you were told it so you believe it to be the case? Why can’t we say the LLM outputs what it believes is the correct answer? You’re both just making some statement based on your prior experiences which may or may not be true
naevaTheRat@lemmy.dbzer0.com 6 days ago
You’re arguing against a position I didn’t put forward. Also
Seems like a pointless distinction, you were told it so you believe it to be the case? Why can’t we say the LLM outputs what it believes is the correct answer? You’re both just making some statement based on your prior experiences which may or may not be true
This is what excessive reduction does to a mfer. That is just such a hysterically absurd take.
kogasa@programming.dev 6 days ago
If you fine tune a LLM on math equations, odds are it won’t actually learn how to reliably solve novel problems. Just the same as it won’t become a subject matter expert on any topic, but it’s a lot harder to write simple math that “looks, but is not, correct” than it is to waffle vaguely about a topic. The idea of a LLM creating a robust model of the semantics of the text it’s trained on is, at face value, plausible; it just doesn’t seem to actually happen in practice.
doubtingtammy@lemmy.ml 6 days ago
This is parrot libel
ignotum@lemmy.world 6 days ago
You take in some information, combine that with some precious experiences, and then output words
Which is what an LLM does.
WalnutLum@lemmy.ml 6 days ago
Flat epistemological statements like this are why I feel like more STEM people need to take Philosophy.
ignotum@lemmy.world 6 days ago
Big fan of philosophy, so please do tell me how my joke is wrong? Does knowledge and beliefs not come from life experiences?
lunarul@lemmy.world 6 days ago
AI hasn’t been redefined. For people familiar with the field it has always been a broad term meaning code that learns (and subdivided in many types of AI), and for people unfamiliar with the field it has always been a term synonymous with AGI. So when people in the former category put out a product and label it as AI, people in the latter category then run with it using their own definition.
For a long time ML had been the popular buzzword in tech and people outside the field didn’t care about it. But then Google and OpenAI started calling ML and LLMs simply “AI” and that became the popular buzzword. And when everyone is talking about AI, and most people conflate that with AGI, the results are funny and scary at the same time.
force@lemmy.world 6 days ago
and for people unfamiliar with the field it has always been a term synonymous with AGI.
Gamers screaming about the AI of bots/NPCs making them mad beg to differ
lunarul@lemmy.world 6 days ago
I was going to add a note about the exception of video games but decided I’m digressing
WagyuSneakers@lemmy.world 5 days ago
LLMs have more in common with chatbots than AI.
JackGreenEarth@lemm.ee 5 days ago
You are very skilled in the art of missing the point. LLMs can absolutely be used as chatbots, amongst other things. They are more advanced than their predecessors in this, and work in a different way. That does not stop them from being a form of artificial intelligence. Chatbots and AI are not mutually exclusive terms, the first is a subset of the second. And you may indeed be referring to AGI or ASI as AI, a misconception I addressed in my earlier comment.
WagyuSneakers@lemmy.world 5 days ago
I work on ML projects. I’m telling you, as a matter of fact, you do not understand what you are talking about.
Try being less smug and pedantic.
JackGreenEarth@lemm.ee 5 days ago
Oh, wow! You ‘work in ML projects’, do you?
Then maybe you could point out specific examples of me not knowing what I’m talking about, instead of general dismissiveness?
Seraph@fedia.io 6 days ago
I appreciate you taking the time to clarify thank you!
SkyNTP@lemmy.ml 6 days ago
You completely missed the point. The point is people have been lead to believe LLM can do jobs that humans do because the output of LLMs sounds like the jobs people do, when in reality, speech is just one small part of these jobs. It turns, reasoning is a big part of these jobs, and LLMs simply don’t reason.