I had GPT 3.5 break down 6x 45-minute verbatim interviews into bulleted summaries and it did great. I even asked it to anonymize people’s names and it did that too. I did re-read the summaries to make sure no duplicate info or hallucinations existed and it only needed a couple of corrections.
Beats manually summarizing that info myself.
Maybe their prompt sucks?
I also use it for that pretty often. I always double check and usually it’s pretty good. Once in a great while it turns the summary into a complete shitshow but I always catch it on a reread, ask a second time, and it fixes things up. My biggest problem is that I’m dragged into too many useless meetings every week and this saves a ton of time over rereading entire transcripts and doing a poor job of summarizing because I have real work to get back to.
I also use it as a rubber duck. It works pretty well if you tell it what it’s doing and tell it to ask questions.
Isn’t the whole point of rubber duck debugging that the method works when talking to a literal rubber duck?
@RagnarokOnline @dgerard “They failed to say the magic spells correctly”
“tools” doesn’t mean “good”
good tools are designed well enough so it’s clear how they are used, held, or what-fucking-ever.
fuck these simpleton takes are a pain in the arse. They’re always pushed by these idiots that have based their whole world view on fortune cookie aphorisms
You could use them to know what the text is about, and if it’s worth your reading time. In this situation, it’s fine if the AI makes shit up, as you aren’t reading its output for the information itself anyway; and the distinction between summary and shortened version becomes moot.
However, here’s the catch. If the text is long enough to warrant the question “should I spend my time reading this?”, it should contain an introduction for that very purpose. In other words if the text is well-written you don’t need this sort of “Gemini/ChatGPT, tell me what this text is about” on first place.
EDIT: I’m not addressing documents in this. My bad, I know. [In my defence I’m reading shit in a screen the size of an ant.]
No, it’s just rambling. My bad.
I focused too much on using AI to summarise and ended not talking about it summarising documents, even if the text is about the later.
And… well, the later is such a dumb idea that I don’t feel like telling people “the text is right, don’t do that”, it’s obvious.
if the text is well-written you don’t need this sort of “Gemini/ChatGPT, tell me what this text is about” on first place.
And if it’s badly written then the LLM will shit itself.
Now let’s ask ourselves how much of the text in the world is “well-written”?
Or even better, you could apply this to Copilot. How much code in the world is good code? The answer is fucking none, mate.
ChatGPT gives you a bad summary full of hallucinations and, as a result, you choose not to read the text based on that summary.
(For clarity I’ll re-emphasise that my top comment is the result of misreading the word “documents” out, so I’m speaking on general grounds about AI “summaries”, not just about AI “summaries” of documents.)
The key here is that the LLM is likely to hallucinate the claims of the text being shortened, but not the topic. So provided that you care about the later but not the former, in order to decide if you’re going to read the whole thing, it’s good enough.
And that is useful in a few situations. For example, if you have a metaphorical pile of a hundred or so scientific papers, and you only need the ones about a specific topic (like “Indo-European urheimat” or “Argiope spiders” or “banana bonds”).
That backtracks to the OP. The issue with using AI summaries for documents is that you typically know the topic at hand, and you want the content instead. That’s bad because then the hallucinations won’t be “harmless”.
But the claims of the text are often why you read it in the first place! If you have a hundred scientific papers you’re going to read the ones that make claims either supporting or contradicting your research.
You might as well just skim the titles and guess.
The problem is not the LLMs, but what people are trying to do with them.
They are currently spoons, but people are desperately wishing they were katanas.
They work really well for soup, but they can’t cut steak. But they’re being hyped as super ninja steak knives, and people are getting pissed when they can’t cut steak.
If you give them watery, soupy tasks they can do successfully, they can lighten your workload, as long as you’re aware of what they are and aren’t good at.
What people want LLMs to be able to do, ie. “Steak” tasks:
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write complex documents
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apply complex knowledge/rules to a situation
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Write complex code and create entire programs based on vague description
What LLMs can currently do ie. “Soup” tasks:
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check this document and fix all spelling, punctuation and grammatical errors
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summarise this paragraph as dot points
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write a python program that sorts my photographs into folders based on the year they were taken
Half of Lemmy is hyping katanas, the other half is yelling “Why won’t my spoon cut this steak?!! AI is so dumb!!!”
Update: wow, the pure vitriol pouring out of the replies is just stunning. Seems there are a lot of you out there who have, in one way or another, tied your ego very strongly to either the success or failure of AI.
Take a step back, friends, and go outside for a while.
they don’t do any of that soup shit reliably either and reading the article might have told you that
I’d offer congratulations on obfuscating a bad claim with a poor analogy, but you didn’t even do that very well.
good god this entire post is the most tortured believer whataboutism I’ve encountered this month and there’s extremely strong competition here
are currently spoons, but people are desperately wishing they were katanas
ie. “Steak” tasks
you should make a youtube channel, The Katana Steak-Eater. I’d watch the shit out of that at least one saturday afternoon
What LLMs can currently do summarise this paragraph as dot points
The entire point here is that they can’t?
Clearly this post is about LLMs not succeeding at this task, but anecdotally I’ve seen it work OK and also fail. Just like humans, which is the benchmark but they are faster.
Food analogy
This level of discourse wouldn’t fly on 4chan, how is it so popular with LLM fans?
needs to be a car analogy
- What people want LLMs to do, i.e. Corvette tasks
- What LLMs actually do, i.e. Trabant tasks
“spoons and katanas” has got to be the most baby brained analogy. are you a child
Hahaha what a load of nonsense.
Ok? I don’t have another human available to skim a shitload of documents for me to find answers I need and I don’t have time to do ot myself. AI is my best option.
So long as you don’t care about whether they’re the right or relevant answers, you do you, I guess. Did you use AI to read the linked post too?
Yep. Go ahead and ignore all the cases where it’s getting answers correct and actually helping. We’re all just hallucinating, it’s in no way my lived experience. Your reality is the prime reality and we’re the NPC’s.
Go ahead and ignore all the cases where it’s getting answers correct
- Sir, half of the patients are dead!
- Ye sure, just ignore the half that survived then!
I didn’t read the post at all because its premise is irrelevant to my situation. If I had another human to read documentation for me I would do that. I don’t so the next best thing is AI. I have to double check its findings but it gets me 95% of the way there and saves hours of work. It’s a useful tool.
I didn’t read the post at all
rather refreshing to have someone come out and just say it. thank you for the chuckle