Stanford University researchers unveiled an AI model they say can analyze decades of property records in just a few days at little expense to weed out racist language, and they will offer the tool for free across the state and around the country.
I never made any “AI bad” arguments (in fact, I said that they may be incredibly well suited to this) I just argued for the correct use of words and you hallucinated.
LLMs arent “bad” (ignoring, of course, the massive content theft necessary to train them), but they are being wildly misused.
“Analysis” is precisely one of those misuses. Grand Theft Autocomplete can’t even count, ask it how many 'e’s are in “elephant” and you’ll get an answer anywhere from 1 to 3.
This is because they do not read or understand, they produce strings of tokens based on a statistical likelihood of what comes next. If prompted for an analysis they’ll output something that looks like an analysis, but to determine whether it is accurate or not a human has to do the work.
Get the general vibe of a text (sentiment analysis)
Generate plausible text
Semantics aside, they’re very different skills that require different setups to accomplish. Just because counting is an easier task than analysing text for humans, doesn’t mean it’s the same it’s the same for a LLM. You can’t use that as evidence for its inability to do the “harder” tasks.
No it’s not. It’s pedantic and arguing semantics. It is essentially useless and a waste of everyone’s time.
It applies a statistical model and returns an analysis.
I’ve never heard anyone argue when you say they used a computer to analyse it.
It’s just the same AI bad bullshit and it’s tiring in every single thread about them.
I never made any “AI bad” arguments (in fact, I said that they may be incredibly well suited to this) I just argued for the correct use of words and you hallucinated.
LLMs arent “bad” (ignoring, of course, the massive content theft necessary to train them), but they are being wildly misused.
“Analysis” is precisely one of those misuses. Grand Theft Autocomplete can’t even count, ask it how many 'e’s are in “elephant” and you’ll get an answer anywhere from 1 to 3.
This is because they do not read or understand, they produce strings of tokens based on a statistical likelihood of what comes next. If prompted for an analysis they’ll output something that looks like an analysis, but to determine whether it is accurate or not a human has to do the work.
LLMs cannot:
LLMs can
Semantics aside, they’re very different skills that require different setups to accomplish. Just because counting is an easier task than analysing text for humans, doesn’t mean it’s the same it’s the same for a LLM. You can’t use that as evidence for its inability to do the “harder” tasks.