This guy generally does interesting work, but he's used an LLM to analyze the trends in a "creation science" journal over time, and I just don't think LLMs are effective for this kind of statistical task.

Or have a missed something and they can count now?

Thought I'd ask before leaving a comment about the possible issue.

I mean LLMs are based on statistics, and they will produce results that look like frequency charts. But these charts only attempt to approximate the expected content. They aren't based on counting articles that meet any set of criteria.

It's... nonsense, and not even people who pride themselves on spotting nonsense seem to understand this.

I mean LLMs are based on statistics, and they will produce results that look like frequency charts. But these charts only attempt to approximate the expected content. They aren't based on counting articles that meet any set of criteria.

It's... nonsense, and not even people who pride themselves on spotting nonsense seem to understand this.

@futurebird there are definitely automated/ML/NLP systems that can count and produce trend data, but LLMs are not one. they can only produce somethign that seems confident it has done so

The companies offering these products seem to be delighted that people are confused and using them to do things they simply aren't really doing.

@futurebird

Were the results tokens emitted by the LLM or were the results generated by analyzing the model's weights?

The LLM is just going to emit text, I suspect in the hands of someone who knows what they're doing it might be possible to extract interesting insights from how the model is grouping terms.

This guy generally does interesting work, but he's used an LLM to analyze the trends in a "creation science" journal over time, and I just don't think LLMs are effective for this kind of statistical task.

Or have a missed something and they can count now?

Thought I'd ask before leaving a comment about the possible issue.

@futurebird He even starts with a disqualifying lie: “I analyzed”. No you (he) didn’t—he entered a parcel of text into a statistics-based machine that is not itself capable of statistical analysis.

This guy generally does interesting work, but he's used an LLM to analyze the trends in a "creation science" journal over time, and I just don't think LLMs are effective for this kind of statistical task.

Or have a missed something and they can count now?

Thought I'd ask before leaving a comment about the possible issue.

@futurebird if you're talking about using LLMs as a classifier for arbitrary text, I've seen yougov do it for some polls where they ask people about what they've read in the news recently and the LLM classifies what topics were mentioned, this ability is advertised here https://yougov.com/business/products/ai-qualitative-explorer
Also I've seen data science articles from the economist using basically the same idea on larger corpuses of text. I think empirically the best LLMs today are very good at modelling humans so this is ~fine?

Seems like the more people pride themselves on spotting nonsense, the more they seem to be advocating this shit these days. People have entered into this weird phase of mass AI hysteria and only those that don't use it at all are sitting here like... Am I crazy or are the hoards of AI enthusiasts crazy? It's gotta be one or the other.

@Smoljaguar

Wouldn't you need to ask it about each article individually and track the results?

Not just give it a stack of articles and ask "how many of the articles mentioned X" ?

@futurebird yeah, that's what the correct thing to do would be, but it is still plausible that it could do the second, it's just more likely to make a mistake (though I think a task of this difficulty is pretty doable for current models with huge contexts (1M tokens), unlike older/cheaper models which had severe quality drop offs after maybe 10k tokens)

That's not even the point of what I said at all, but nm.

@Smoljaguar

If it says there are 67 articles that mention topic X, but you don't know if that number is correct, it's just a guess based on context and the bulk of text (and LLMs are also bad at following commands such as "consider only these sources" ... ) what is the point of saying the number.

Maybe could you ask if a topic is mentioned "frequently" or "infrequently" but beyond that I think it's deceptive and useless.

@futurebird @Smoljaguar I’d do it with a loop. For each document, does it contain X, Y or Z? I’d end up with a table of document names and booleans.

@Moss

Damn thing will sit there and tell you that's what it's doing.

But it can't count! It still can't count. I feel like I'm going crazy. Am I the only person who cares that the machine can't even count?