361–370 of 445 posts
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> Can't we just send LLMs back to the drawing board until they have some semblance of reliability? Well at this point they've certainly proven a net gain for everyone regardless of the occasional nonsense they spew.
That is... debatable. You may be entirely inside the bubble, there.
I just gave it a whirl. Pretty neat, but definitely watch out for hallucinations. For instance, I asked it to compile a report on myself (vain, I know.) In this 500-word report (ok, I'm not that important, I guess), it made at least three errors. It stated that I had 47,000 reputation points on Stack Overflow -- quite a surprise to me, given my minimal activity on Stack Overflow over the years. I popped over to the l…
A report full of factual errors that a careful intern wouldn't make is worse than useless (yes, yes, I've mentored interns).
If the hard part is the language, then do the research yourself, write an outline, and have the LLM turn it into complete sentences. That would at least be faster.
Here's the thing, though: If you do that, you're effectively proving that prose style is the low-value part of the work, and may be unnecessary. Which, as much as it pains to me say as a former English major, is largely true.
Still not seeing access on my account.
they're not giving it to us lowly $20/month users yet :( gotta take out a second mortgage and throw them 200/month if you want it now
So far I tried it on one problem and it seems limited by the "front end" being 4o-mini. It ignored most of my initial prompt and also ignored the previous research it asked for which I provided. The final output was high quality and definitely was enriched by the web searching it did, but it left out a crucially important dimension of the problem because it was unable to ingest the background info I provided adequately.
I'd like to see a version of it where the front end model is o1-pro
I just gave it a whirl. Pretty neat, but definitely watch out for hallucinations. For instance, I asked it to compile a report on myself (vain, I know.) In this 500-word report (ok, I'm not that important, I guess), it made at least three errors. It stated that I had 47,000 reputation points on Stack Overflow -- quite a surprise to me, given my minimal activity on Stack Overflow over the years. I popped over to the l…
"Pretty neat, but definitely watch out for hallucinations." We'd never hire someone who just makes stuff up (or at least keep them employed for long). Why are we okay with calling "AI" tools like this anything other than curious research projects? Can't we just send LLMs back to the drawing board until they have some semblance of reliability?
This is contrary to my experience.
To anyone who's tried it: how does it handle captchas? I can't imagine that OpenAI's IP addresses are anyone's favorites for unfettered access to web properties these days.
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That is... debatable. You may be entirely inside the bubble, there.
Not sure if this was posted as humour, but I don't feel that way. In today's world, where I certainly would consider taking the blue pill, I'm having a blast with LLMs! It has helped me learn stuff incredibly faster. Especially I find them useful for filling the gaps of knowledge and exploring new topics in my own way and language, without needing to wait an answer from a human (that could also be wrong). Why does it…
and then you verify every single fact it tells you via traditional methods by confirming them in human-written documents, right?
Otherwise, how do you use the LLM for learning? If you don't know the answer to what you're asking, you can't tell if it's lying. It also can't tell if it's lying, so you can't ask it.
If you have to look up every fact it outputs after it does, using traditional methods, why not skip to just looking things up the old fashioned way and save time?
Occasionally an LLM helps me surface unknown keywords that make traditional searches easier, but they can't teach anything because they don't know anything. They can imagine things you might be able to learn from a real authority, but that's it. That can be useful! But it's not useful for learning alone.
And if you're not verifying literally everything an LLM tells you.. are you sure you're learning anything real?
I just gave it a whirl. Pretty neat, but definitely watch out for hallucinations. For instance, I asked it to compile a report on myself (vain, I know.) In this 500-word report (ok, I'm not that important, I guess), it made at least three errors. It stated that I had 47,000 reputation points on Stack Overflow -- quite a surprise to me, given my minimal activity on Stack Overflow over the years. I popped over to the l…
Interesting! I wonder if it’s carried over too much of that ‘helpful’ DNA from 4o’s RLHF. In that case, maybe asking for 500 words was the difficult part — it just didn’t have enough to say based on one SO post and one article, but the overall directives assume there is, and so the model is put into a place where it must publish.. Put another way, it seems this model faithfully replicates the incentives most academic…
It didn't pick up my HN comments, probably because my first and last name are not in my profile, though obviously that is my handle in a smooshed-together form.
Earlier quoted context omitted.
"Pretty neat, but definitely watch out for hallucinations." We'd never hire someone who just makes stuff up (or at least keep them employed for long). Why are we okay with calling "AI" tools like this anything other than curious research projects? Can't we just send LLMs back to the drawing board until they have some semblance of reliability?
> Can't we just send LLMs back to the drawing board until they have some semblance of reliability? Well at this point they've certainly proven a net gain for everyone regardless of the occasional nonsense they spew.
Problem is - LLMs pull answers from their behind, just like a lazy student on the exam. "Halucinations" is the word people use to describe this.
Those are extremely hard to spot - unless you happen to know the right answer already, at which point - why ask? And those are everywhere.
One example - recently there was quite a discussion about llm being able to understand (and answer) base16 (aka "hex") encoding on the fly, so I went on to try base64, gzipped base64, zstd-compressed base64, etc...
To my surprise, LLM got most of those encoding/compressions right, decoded/uncompressed the question, and answered it flawlessly.
But with few encodings, LLM detected base64 correctly, got compression algorithm correctly, and then... instead of decompressing, made up a completely different payload, and proceeded to answer that. Without any hint of anything sinister going.
We really need LLMs to reliably calculate and express confidence. Otherwise they will remain mere toys.
Earlier quoted context omitted.
Not sure if this was posted as humour, but I don't feel that way. In today's world, where I certainly would consider taking the blue pill, I'm having a blast with LLMs! It has helped me learn stuff incredibly faster. Especially I find them useful for filling the gaps of knowledge and exploring new topics in my own way and language, without needing to wait an answer from a human (that could also be wrong). Why does it…
>It has helped me learn stuff incredibly faster. Especially I find them useful for filling the gaps of knowledge and exploring new topics in my own way and language and then you verify every single fact it tells you via traditional methods by confirming them in human-written documents, right? Otherwise, how do you use the LLM for learning? If you don't know the answer to what you're asking, you can't tell if it's lyi…
Earlier quoted context omitted.
Either you care about being correct or you don't. If you don't care then it doesn't matter whether you made it up or the AI did. If you care then you'll fact check before publishing. I don't see why this changes.
It's a bit like saying "my kids are going to hit themselves anyway, so it doesn't matter if I give them foam rods or metal rods".