huntrss ( @huntrss@feddit.de ) 68•5 months agoIt’s so human how - instead of admitting its error - it’s pulling this bs right out of its ass 🤣
darthfabulous42069 ( @darthfabulous42069@lemm.ee ) 11•5 months ago🤔 I wonder what the hell it is that’s so scary about admitting they’re wrong to other people.
Duranie ( @Duranie@literature.cafe ) 20•5 months agoGrowing up in an environment where mistakes were unacceptable sets the stage. Our willingness and ability to understand that that’s fucked up and change our attitudes about mistakes takes more growth.
For some people it’s easier to dig in their heels and double down.
darthfabulous42069 ( @darthfabulous42069@lemm.ee ) 8•5 months ago🤔🤔🤔 I guess I can empathize. People are always traumatized by whatever their parents tell them. What a shame.
voxel ( @vox@sopuli.xyz ) 43•5 months ago gerryflap ( @gerryflap@feddit.nl ) 29•5 months agoI think these models struggle with this because they don’t process text as individual characters, but rather as tokens that often contain parts of a word. So the model never sees the actual characters within a token, and can only infer the contents of a token from the training data itself if the training data contains more information about it. It can get it right, but this depends on how much it can infer from training data and context. It’s probably a bit like trying to infer what an English word sounds like when you’ve only heard 10% of the dictionary spoken aloud and knowing what it sounds like isn’t actually that important to you.
More info can be found here: https://platform.openai.com/tokenizer
Krauerking ( @Krauerking@lemy.lol ) 8•5 months agoOk, so, tokenization of the words is why I get that I have seen tech nerds get so excited about a system that allows for being able to come up with synonyms for words that were auto-generated that have a basic ability to sometimes be correct by looking at the words before and after it…
But it’s such a shitty way to look up synonyms! Using the words on either side doesn’t mean you found a synonym just that you found another word that might work and it still has to use the full horsepower of ridiculously overpowered system.
Or you could have a lookup table that just reads the frickin word and has alternate synonyms predefined and it was able to run in word 97.
It’s ridiculous that we think this is better in any meaningful way instead of just wasteful development.
Daxtron2 ( @Daxtron2@startrek.website ) 4•5 months agoBecause that’s not the point of an LLM lmao
Krauerking ( @Krauerking@lemy.lol ) 2•5 months agoSure but what is their purpose other than to create convincing sounding sentences? And use a lot of computer resources to do so?
Umbrias ( @Umbrias@beehaw.org ) 2•5 months agoIn all reality this tokenization and llm language processing is useful for all sorts of things which can be mathematically somewhat modeled similarly to language. Using them for shitty web searches is not ideal.
Daxtron2 ( @Daxtron2@startrek.website ) 2•5 months agoSure if you want to reduce it down to it’s most basic elements. Anything sounds useless like that. Video games are just dots changing color on a screen and use a lot of electricity. Banking software is just tracking changes to a number and also is extremely inefficient and resource intensive.
Krauerking ( @Krauerking@lemy.lol ) 2•5 months agoThis is not a convincing argument to say that other things can be reduced down arbitrarily, than explaining the usefulness of it.
Daxtron2 ( @Daxtron2@startrek.website ) 2•5 months agoWell I can personally say it has cut down the amount of busy work at my job down by a lot. Boilerplate code is easy and near instantaneous. I am also working on a project that can bridge the communication gap between highly technical text and non technical readers. It works extremely well at this task even with a non fine tuned model, which is my current step in development.
jkozaka ( @jkozaka@lemm.ee ) 25•5 months agoYou forgot the rest of the posts where the llm gaslights her after. There are too many images to put here, so I’ll link a post to them.
I’m not sure if this is the original post, but it’s where I found it. initially megopie ( @megopie@lemmy.blahaj.zone ) 22•5 months agoYah, people don’t seem to get that LLM can not consider the meaning or logic of the answers they give. They’re just assembling bits of language in patterns that are likely to come next based on their training data.
The technology of LLMs is fundamentally incapable of considering choices or doing critical thinking. Maybe new types of models will be able to do that but those models don’t exist yet.
Miss Brainfarts ( @miss_brainfarts@lemmy.blahaj.zone ) 20•5 months agoThe funniest thing is that even when the answer is correct, asking an LLM to explain its reasoning step by step can produce the dumbest results
MacStache ( @MacStache@sopuli.xyz ) 18•5 months agoArtificial Intelligencensence.
mondoman712 ( @mondoman712@lemmy.ml ) 16•5 months agoI just tried in google gemini
Bazz ( @Bazz@feddit.de ) 15•5 months agonnayonnaise
sverit ( @sverit@feddit.de ) 6•5 months agoKerning!
Kwakigra ( @Kwakigra@beehaw.org ) 3•5 months agoAnother victory for humanity.
Waluigi ( @Waluigi@feddit.de ) 6•5 months agoThat escalated quickly
katy ✨ ( @cupcakezealot@lemmy.blahaj.zone ) 5•5 months agocan’t spell mayonnaise without no
Pleb ( @pleb_maximus@feddit.de ) 4•5 months agoMhhh… Mayonnaise…
Daxtron2 ( @Daxtron2@startrek.website ) 3•5 months agoWow another repost of incorrectly prompting an LLM to produce garbage output. What great content!
Umbrias ( @Umbrias@beehaw.org ) 10•5 months agoThis is genuinely great content for demonstrating that ai search engines and chat bots are not in a place where you can trust them implicitly, though many do
Daxtron2 ( @Daxtron2@startrek.website ) 1•5 months agoWhich is exactly why every LLM explicitly says this before you start.
Umbrias ( @Umbrias@beehaw.org ) 12•5 months ago“Why, we aren’t at fault people are using the tool we are selling for the thing we marketed it for, we put a disclaimer!”
Daxtron2 ( @Daxtron2@startrek.website ) 1•5 months agoYou’ve seen marketing for the big LLMs that’s marketing them as search engines?
Umbrias ( @Umbrias@beehaw.org ) 3•5 months agohttps://www.microsoft.com/en-us/edge/features/the-new-bing?form=MA13FJ
It would have been easier for you to just search it up yourself, you know.
Daxtron2 ( @Daxtron2@startrek.website ) 1•5 months agoBing w/ LLM summarization of results is not an LLM being used as a search engine
Umbrias ( @Umbrias@beehaw.org ) 3•5 months agoLol.
ProgrammingSocks ( @ProgrammingSocks@pawb.social ) 1•4 months agoBing literally has a copilot frame pop up every time you search with it that tries to answer your question
Daxtron2 ( @Daxtron2@startrek.website ) 1•4 months agoAgain, LLM summarization of search results is not using an LLM as a search engine
Mac ( @Mac@mander.xyz ) 2•4 months ago:(