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Comment by JimtheCoder | Hacker News Reader

I may be in the minority here, but if I want the opinion of Redditors on an issue, I will use a search engine to look for it specifically, thus knowing the provenance of the information I am receiving.

I don't really want the corpus of Reddit data influencing the output of a generative AI model...because it's Reddit, after all...

Even though I am pretty sure it is already included in the training dataset already...

I could be wrong, though...

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I genuinely don't understand the appeal of AI for search. The provenance of information is just as important as the resulting information for pretty much anything I search for. I almost never accept a single search result as authoritative unless I'm pretty familiar with the source.

Reddit in particular seems like a terrible set of training data. Pretty much any opinion is going to have a counter-opinion somewhere in the thread. Synthesizing multiple comments together requires nuance based on circumstances that I don't think I would trust to an automated process- which heuristics were applied, what was the reputation of the people on either side, etc.

Hell, I don't even stop at the first recipe I find if I'm looking for something new to cook for dinner. I look at a couple variations on a dish first.

The appeal is that now regular search engines are so bad at giving you useful content that using a LLM is now the equivalent of "google-dorking" to find relevant information.

Only because the LLM didn't have any AI generated blogspam to get trained on. That's going to change very quickly.

Any non-trival LLM that works by scraping the internet is already sufficiently advanced to be able to classify blogspam.

The issue Google has with blogspam is they don't want to filter it because it inevitably uses Google's advertising. So Google gets to self-deal traffic to blogspam which makes them money. They're not incentivized to actually eliminate blogspam.

LLMs aren't automatically disincentivized from training on blogspam so they're not going to avoid it either.

It's funny that you mention recipes at the end because that's exactly what I like to use ChatGPT for. Every single recipe site has been so corrupted by SEO that you need to scroll past 12 paragraphs of nonsense to get to the actual recipe, and more often than not once you actually get to the recipe part you'll be bombarded with popups about newsletters and cookies or some late-loading ad will cause the view to shift past the step you're trying to look at.

ChatGPT is great for distilling that experience down to just a simple recipe for whatever it is I'm looking for.

Tangentially: props to AnyList for their amazing plugin that scrapes recipes off of sites like this and stores them in an easy-to-use format.

I think it's pretty safe to say if any of these AI-based models gain dominance, they will eventually add junk to their output if that junk makes money.

My prediction: By 2025, you'll be able to purchase sponsored sentences and sponsored paragraphs in ChatGPT's (or whoever's on top) output.

I just used ChatGPT4 this past weekend to come up with smoothie recipes and then a shopping list to take to Whole Foods. Can also give it ingredients you already have and ask for recipes. It’s a killer application for me ha

The appeal is that AI answers your question. Maybe a wrong answer. Maybe from questionable sources.

Search, on the other hand, doesn't answer your question.

Simple: get the search results, have LLM read and evaluate them.

It's devilishly difficult to get citations in there, you're not going to do it with langchain, but its possible (c.f. Bing).

Python x langchain x LLMs makes it very easy to create demos so there's been an initial influx of meh stuff, I'm very excited for 6 months from now.

A niche provider that doesn't do generative AI very well but does "AI powered search with citations" is perplexity.ai

I've used for rather obscure queries and liked the summary the AI wrote as well as the links to dive deeper. I imagine that's what AI search will look like across all providers before long.

That site looks incredibly good.

I threw in a question Wikipedia does kinda answer but leaves a lot of details off, and it enumerated a set of possible answers, with my favored option linking into a forum where it looks like less than a dozen people post, but with people that tried all variations of it and know all of the details.

DDG and Google would never show me that site (yeah, I've tried).

Just to add, that forum has better answers than the ones GPT created directly on the search engine. If it was a "consult the Oracle" interface instead of a search engine, it wouldn't be useful at all.

> I genuinely don't understand the appeal of AI for search

If you're good at googling the flow is: Ask the question > Clock which result isnt spam and click it > Figure out how to dismiss the cookies gate without accepting the cookies > Dismiss the google login box > Dismiss the popover pushing you to install an app > Scroll the page or ctrl+F to find the answer

With ChatGPT it's just type your question and your answer is appearing right away.

Of course I understand ChatGPT shouldn't be used for this because it will lie to you and make things up. But I am saying that's why you'll see people who don't know that preferring it over Google.

painful how accurate that is

Aaand this is basically the story of silicon valley over and over again.

Build a product that's more convenient, and people will use it. Google is so full of shit now, and even answer boxes are below 4 ads, it's just way more comfortable and efficient to ask chatgpt.

This morning I wanted to know how many calories there are in a breaded chicken breast. Chatgpt told me in 3 seconds after asking. Google would have been way more time. (sidenote: I also hate google, so I'd much rather use chatgpt anyway)

Also Google (and distressingly, DDG as of late) sanitizes the hell out of the SERPs to only present you with “approved viewpoints”.

And I’m not talking about fringe Q Anon type stuff: the other day I was looking up the specifics of China’s “Blue Sky Initiative” climate change policies and the only thing Goog/DDG would show me (despite several attempts at rephrasing the query) was Western industry think tanks bellyaching about how the policies effect profits. It took me a good ten minutes of refining my search before I got an English translation of the actual policy bullet points.

I can’t imagine this being such a PITA on 2013 era Google.

out of curiosity, how did you verify the information?

I didn’t, but it sounded right. I know it might be incorrect.

However, I’ve seen plenty of bad information in google answer boxes too. And finding it in actual search results is going to be way more time. It’s not a life and death question.

My googling flow: Ask the question > Clock which result isnt spam and click it > uBLock Origin blocks everything > ctrl+F to find the answer

It lies like crazy on surprising things. Database parameters for an enterprise provider, for example, I've seen hallucination in 5% of cases. That's _bad_ when its taken as authoritative.

I like that you can get results quickly and it solves the "I don't know what I'm looking for" problem.

I'm learning typescript and ran into a weird typescript construct the other day, I threw it into chatgpt and asked "what is this" and it explained it to me. I'm not entirely sure if pasting in a bunch of braces and parentheses into google would find me the same result.

Don't get me wrong, thats a great use case!

None of the results are surprising if you simply read what OpenAI writes about their own machine. It's an autocomplete engine.

An autocomplete engine with "sparks of AGI", because gotta get that sweet sweet VC money and market it as the Next Big Thing.

Well, if you make up the answer from nowhere yourself, you save the work of creating a question and typing it on the ChatGPT prompt.

I mean the internet lies and makes stuff up too, being first on Google results has nothing to do with truthfulness.

That's the glory of a search engine. You have multiple sources available to review, compare and - with enough experience - learn which sources you can more readily trust than others.

AI offers none of the above. Ask the same question twice in a row, maybe you'll get a different answer, maybe you won't. You won't know which of the two answers are hallucinations, which are true factoids it trained on, and which are bogus things it had been trained on. There's literally no providence for the results- no trail, no references, nothing, because it's really a sophisticated game of "Whose Line" where everything's made up and nothing matters.

I suspect this is due to a fundamental misunderstanding of what tools like ChatGPT actually are, what their capabilities are, etc. I think there is a large population of people who think they're simply more sophisticated versions of Siri. In fact, I'd go so far as to say that the vast majority of people don't even realize they're powered by different things, but instead just see the "marketing term currently known as AI" as a singular monolithic entity, and all related technology just gets lumped into the same category. That's miles away from understanding how "use a language model to interpret what I'm asking you to search for, and then plug that into a normal search engine, and read me back the most relevant result", is fundamentally different from "use a language model to predict the stastically most likely next sequence of tokens based on the ones you gave me."

I don't mean this as a way of thumbing my nose at people who don't know this stuff, but rather, to point out what a massive failure the completely nonexistent consumer education surrounding ML products has been.

This is the logical endgame for the search engine form factor. Remember watching mom ask google questions using complete sentences and punctuation with a “please and thank you”?

The appeal of a conversational response was too great to wait for a solution to the problem of training data quality.

When you're not sure what to Google (such as when working in an unfamiliar domain), asking ChatGPT for help and then researching it's answer with normal searches is very effective.

ChatGPT like AI is the natural next step in the arms race of SEO vs Search. Right now is a mechanism to fight SEO. It will continue to work for a few years.

> I genuinely don't understand the appeal of AI for search. The provenance of information is just as important as the resulting information for pretty much anything I search for.

Search requires work on the part of the user to distinguish between good links and bad. AI is an oracle just tells you what you're looking for.

Now you and I might think this is a terrible way to evaluate the veracity of information. But think about the new generation of mobile-native users who were raised on simplistic discourse in tweet-length messages, and would rather watch a 1-min video on a topic than scan search results for 30 seconds.

For this group, searching for information where more than 2 clicks is required is going to be a "too complicated", anda "bad user experience".

> AI is an oracle just tells you what you're looking for.

LLMs are oracles that arrange words in a probabilistic order that are grammatically correct and may be factually correct. Unfortunately there's no way to evaluate the probability of confabulation with any of the LLM chat bots. The distribution of occurrences confabulation is also not regular or predictable nor is it fixed. So you can't ever say "ChatGPT is bad at X" because it can be bad today, good tomorrow, then bad the next day.

It sounds like we are dooming an entire generation by catering to a maladaption of technology-addiction induced ADD.

Idiocracy and The Machine Stops ... All At Once.

LLMs are the worst method for information retrial, except for every other method we tried.

You are absolutely right minority or not. I actively avoid reddit because the majority of users there. The fact we're seeing government agencies start treading into using GPT models is frightening. We could find ourselves in a tragic comedy where all of the massive institutions and enterprises around us are addressing their serious issues via redditors by proxy.

depends of where you go on reddit. i've learned a lot of things for my hobbies. for example r/espresso and r/roasting are a source of good information. there are also places like r/askhistorians and many many otheres. reddit is not just r/funny.

niches and hobbies are dominated by beginners and ideas that can't be challenged (theres a word for this, I cant remember what it is). people aren't just talking about their experience on major subs though.

the opinions i run into real life can be very different then with people in the real world. the communities online are made up of the kinds of people who spend their time online, and the content you see on reddit is generally from the people who spend enough time on reddit that they want to browse new. these arent average people. only a minority professionals are actually engaged in reddit. even those ive seen run off because they don't agree with the acceptable opinions

> there's a word for this

Hegemony, perhaps.

>the opinions i run into real life can be very different then with people in the real world.

I think you messed that sentence up, but I get what you're trying to say....

And I think it's this. The opinions you get from people 'IRL' are not apt to be as strong as the ones online, and or will run into the regency bias.

For example, it's very unlikely you'll actually meet someone that has used 10 different coffee makers because they wanted to see which one was best. Online on some subreddit, you're very likely to meet someone who has done exactly that. Of course those people with strong opinions are the ones that are apt to post most online.

So who's option is wrong? Neither. That's why they are opinions.

>And I think it's this. The opinions you get from people 'IRL' are not apt to be as strong as the ones online, and or will run into the regency bias.

No, I've noticed what he's talking about, and it's not the strength of the opinion, it's what the opinion is. Reddit has a moral system that's completely misaligned with real world morality, where having a child or being autistic makes you a bad person, even if you didn't do anything wrong. You can find some really weird takes on r/AITA, which ironically points out that the subreddit has a fucked up sense of morality in its highest rated post.

>having a child

Not sure if you've noticed but younger generations that go out and do things are big into having children. Now, some groups on reddit are more extreme on that, but the general trend of Americans at least is to tell the act of having kids to screw off.

---

But to answer your question, it's not Reddit that has this moral system, it's social media in general that has a moral system that does not match reality (kinda). The loudest idiots tend to get voted up, moderates disappear in the bulk of posts. Binary voting systems on sites tend to amplify this. Content suggestion systems tend to lift up contentious posts for engagement. Welcome to the internet.

But coming back to (kinda). This is becoming reality. Behavior IRL affects behavior online. Online behavior affects IRL behavior. People don't talk to their neighbors these days in most places. Communities are spread all over the earth.

>We could find ourselves in a tragic comedy where all of the massive institutions and enterprises around us are addressing their serious issues via redditors by proxy.

not with a bang, but with a "this. take my upvote my good sir"

horrific

I think what the article tries to say is that OpenAI have already scraped Reddit for training data and with the recent API changes and subreddits going dark, new competitors in the AI space won't have it as easy to get the same training set.

Honestly this sounds like a shower-thought post. With even basic research, Internet Archive and The Eye have Reddit historical data freely available. My desktop PC has all comments and posts from 2007-early 2023, in a convenient jsonl zst. It's only 3TB.

The point isn't really to discover the opinions of redditors, it is to ingest the 'common sense' things that you would never find out from reading scientific papers or even books.

You’re not alone in thinking that. The value in using Reddit as training data would be the question response format of threaded comments. The downside is that the vast majority of comments on Reddit are very low quality and repetitive. You’d have to do a lot of filtering to make it usable and what you’d be left with would be a much smaller pile of training data.

repetitive is good tho, it presents validation. I'm sure programming a good AI means adding a grading system for repetitive facts, in reddit's case, it may even accommodate likes. The problem would be when we have run-away sarcasm/irony/memes which the llamas can't handle.

Repetition is not good, because too much of it leads to overfitting.

I don't think you're the minority. I want to actually read the thread and see what random individuals thought about a thing (with their different views intact), rather than getting an aggregate summary. Often the overlooked, 1 point comment (because he answered the question a month after the question was raised), is the one you're looking for.

One of the big values of reddit is that it serves as an easy index for non-garbage websites on the internet. This is exactly how it was used in the T5 paper: they threw away all the websites from their crawl that were not linked to from Reddit.

And by garbage I mean literally data/illegible/etc. that would ruin the pretraining of the model.

In my opinion, it comes back to search engines not giving you a the best answer. If you're looking for the best headset with whatever feature, you'll find mostly sponsored reviews, or at the very least hard to trust reviews.

On the other hand, some random people's opinions in a Reddit community with -apparently- no further agenda seem somewhat more honest.

Not that the answer is better but it gives you new data points in your search.

Basically, it's not one or the other, you can use both tools and that's probably why it makes sense to include Reddit in AI models (which do this job for you automatically)

Seriously hope OpenAI is stripping all the canned meme replies that go on for hundreds of sub threads and end up as the top comments in threads before they train their models. How would you even do that reliably?

Label data and build a meme classifier? Does not have to be perfect to be useful. But yeah, data curation is probably a huge endeavor at the companies making Language model that are fit for production. Like in practically all applications of Machine Learning.

But the Reinforcement Learning from Human Feedback (RLHF) is also one of the key tools to getting useful outputs.

They don't. That's why some tokens from /r/counting mess up their models: SolidGoldMagikarp and " davidj12" or something like that

I'm sure that the non technical public would be interested in a chatbot fed on reddit data, which is more interesting than how valid the AI models predictions are for the people making money off of it.

Reddits community is passive aggressive, thinks it’s really smart, loves memes. I certainly hope OpenAI doesn’t view it at as some kind of a source of truth

You just described the C-suite at most SV companies.

No, they view it as a language model. You can tell lies with the same language that you can tell truth with.

If you want truth, you don't want language, you want references to reviewed work. You also want things like 'show your work' chains of though. These are really different things.

If I tell GPT "make up a story" I don't want it coming back and saying, sorry I can only tell the truth.

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