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Someone in the Tweet reply [1] says it is due to a reddit user called "davidjl123", because of his posting history in /r/counting (?). So what is /r/counting,

Someone in the Tweet reply [1] says it is due to a reddit user called "davidjl123", because of his posting history in /r/counting (?). So what is /r/counting, and why its "top" user's name is a glitch token in GPT? [1] https://twitter.com/SoC_trilogy/status/1666714127438434304 https://twitter.com/SoC_trilogy/status/1666714127438434304

GaggiX 3y ago
It's a subreddit where people count. There are a lot of comments, and unfortunately the tokenizer was trained on this subreddit, which is why these weird tokens.
- georgeg23 3y ago
  My hunch is the token “ davidjl” is repetitively used in the data that determines the tokenization scheme but is nearly (or completely) absent from the actual pre-train data. -Riley Goodside
  - GaggiX 3y ago
    Yeah this is true with every glitch token, the distribution of the tokenizer and the GPT model is very different.
  - mike_hearn 3y ago
    That was investigated here: https://www.lesswrong.com/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation?commentId=MYLFfeNfQsxjBJwkF https://www.lesswrong.com/posts/aPeJE8bSo6rAFoLqg/solidgoldm... The idea that tokens found closest to the centroid are those that have moved the least from their initialisations during their training (because whatever it was that caused them to be tokens was curated out of their training corpus) was originally suggested to us by Stuart Armstrong. He suggested we might be seeing something analogous to "divide-by-zero" errors with these glitches. However, we've ruled that out. The counting Reddit usernames are clearly a major source of glitch tokens, there's something about that sub that screws up the model, maybe the unusually predictable/repetitive nature of what goes on there or the sheer obsessiveness of the posters. The fact that the only non-counting Reddit usernames are both people at the center of massive Bitcoin psychodramas is suggestive however, especially given the associations with the petertodd token. My guess is that these names appear much more frequently in other people's posts than is normal for forum usernames (especially if it read bitcointalk.org and twitter too), and that maybe this has some effect. To get an idea of just how frequently this token will crop up in the reddit corpus, just do a search for it: https://www.reddit.com/search/?q=%22petertodd%22&sort=comments https://www.reddit.com/search/?q=%22petertodd%22&sort=commen... I'm not sure how many posts match but you can keep scrolling a long time. Having been more exposed than normal to what happened back then I wasn't hugely surprised by what concepts clustered there, and sadly don't think it's actually random or unexplainable. Flick through discussions pre-2015 (when the Bitcoin forums started to be heavily censored) and you'll see a lot of very similar words as what GPT spits out being used in connection. It was all very nasty.
    - samstave 3y ago
      [flagged]
      - mike_hearn 3y ago
        Here's my non expert explanation, take it for what it's worth. Tokens solve the following problem: the first layers of the neural net(s) are a big array of numbers, where the size is a hyperparameter (a parameter that can be used to change the size or behavior of the network). A typical size for a big model like the GPTs is larger than 50,000. You have to somehow encode language as a sequence of assignments to this array of numbers. How do you do it? The first and most obvious idea is characters. You could assign each unicode code point to one of the slots in the input array, and then use what they call a one-hot encoding where every number is zero except the character. You can do this, but it's not very efficient because virtually all the training text is written in Latin languages and so almost all the slots will be unused. A better way is to start with a big pile of text that you're going to use, and then iteratively assign the slots to sequences of characters based on how common they are. This makes it easier for the network to learn and reason. These sequences are tokens. For example "and" is very common, and so would "ing" (from the suffix), so those should get their own tokens. SuperGoldMagiCarp isn't so that really shouldn't - it should be represented as a sequence of tokens instead. There are algorithms that figure out the most efficient assignment of tokens to character sequences, which you can think of as the model's vocabulary, and then to convert text into a sequence of these token numbers. OpenAI's software is called Tiktoken and is written in Rust for speed. The output of the network is likewise also tokens, and so you run the process in reverse at the end to get text back out of the array of floats that the network produces. Or more accurately, the network produces a set of probabilities for each token in its vocabulary, and then you can pick the most probable (oversimplification - in reality the way you select the token is more complicated than that as otherwise you get bad results). The problems here are to do with bugs in the training process, but are no less interesting for that. Some character sequences that are very rare and should really be represented by many different tokens in a row have somehow ended up being considered important enough to be given their own whole token. The most common cause of this seems to be cases where the token vocabulary was computed on text that contained garbage highly repetitive text like debug logs from video games, hence the prevalence of obscure game characters like Leilan, and Reddit threads are clearly over-represented. But then GPT struggles to work out what these tokens actually mean because they hardly appears in the training set, and so these tokens seem to float together in space and get easily conflated inside the model, also they end up representing very vague or abstract concepts.
  - neonate 3y ago
    That is a quote from https://twitter.com/goodside/status/1666609934635606017 https://twitter.com/goodside/status/1666609934635606017.
- countmora 3y ago
  > unfortunately the tokenizer was trained on this subreddit Do you have a source for that or was it just an assumption?
  - gl-prod 3y ago
    There was a video[0] on Computerphile about this topic [0] https://www.youtube.com/watch?v=WO2X3oZEJOA https://www.youtube.com/watch?v=WO2X3oZEJOA
  - mike_hearn 3y ago
    It's pretty much guaranteed. Where else on the internet would this sequence of characters appear so frequently that it gets selected as one of the internet's top ~50,000 words? Also, that Reddit is frequently used to train LLMs is widely known. It's an unusually clean source of conversational text because you can slice threads (i.e. pick a root comment, then pick a child, then a child of the child etc and then concatenate the results), and you'll get a coherent conversation. There are relatively few places on the internet where that is true. For example most phpBB forums conflate many different conversations into single threads, with ad-hoc quoting being used to disambiguate which post is replying to which. That makes it a lot harder to generate sample conversations from.
    - dontupvoteme 3y ago
      >There are relatively few places on the internet where that is true Imageboards. DailyMail. Slashdot. Even a somethingawful dump would have been superior.
      - mike_hearn 3y ago
        Slashdot doesn't have the volume. Don't know about image boards but are they threaded and do they cover as many topics? The Daily Mail (the newspaper) has been used for training LLMs in the past, yes. I don't know if it still is.
        3y ago
- perfmode 3y ago
  is this why reddit is charging for its API? to try to capture value from the entities training LLMs on reddit data?
  - asddubs 3y ago
    that ship has probably sailed, since pushshift hosts a copy of all of reddit, including removed content. it's really weird to me that they even allowed that level of access for that long (FWIW I don't agree with the recent changes, but I see little legitimate reason to give someone a way to scan and copy all recently made posts across all subreddits).
    - pjc50 3y ago
      Archiving. https://news.ycombinator.com/item?id=36254172 https://news.ycombinator.com/item?id=36254172 It's very much "he who has the power to destroy a thing controls that thing"; so long as there's only one canonical copy of a post and it's on Reddit's servers, that's vulnerable to actions by the subreddit mods or Reddit themselves.
- deleted 3y ago
  [deleted]
jallen_dot_dev 3y ago
> ETIQUETTE: > 1. If you're counting, upvote your fellow counting comrades. Looks like a voting ring for farming karma. Not sure why reddit allows it.
- hn_throwaway_99 3y ago
  That's not what it is. It's really just kind of a wacky subreddit for bored and/or OCD people.
  - Freedom2 3y ago
    I disagree, and agree with jallen. If nothing else, this is fraud! A voting ring like this has to be dismantled immediately, or else there will be significant ramifications, which im sure GP and expand on.
    - jallen_dot_dev 3y ago
      I know they're just Internet points but they are supposed to serve as a social signal that somebody has contributed (meaningful) content. Also some subreddits require a certain amount of karma to post. And finally, this activity is just useless spam. I never implied it was such a big deal as to warrant your snark.
      - LegionMammal978 3y ago
        > And finally, this activity is just useless spam. It's far from spam: it's a social activity. When "running" with someone, you post a comment with a count, watch your inbox patiently for the other person to post the next count, reply with the count after that, and repeat. In the process, you collaboratively climb the infinite ladder together. Hence the words of congratulations and thanks every time a milestone (a "get") is reached. Counters can and do hold side discussions along the way; pretty much no one comes to the subreddit to act like a perfect robot. Indeed, the other person's humanity is plainly observable in the variation in their response times. Also, the main visible karma on Reddit is post karma, and r/counting is the exact opposite of where you'd go to farm post karma, given that a new post on a given chain is only made every ~1000 counts.

GaggiX 3y ago

It's a subreddit where people count. There are a lot of comments, and unfortunately the tokenizer was trained on this subreddit, which is why these weird tokens.

georgeg23 3y ago
My hunch is the token “ davidjl” is repetitively used in the data that determines the tokenization scheme but is nearly (or completely) absent from the actual pre-train data. -Riley Goodside
- GaggiX 3y ago
  Yeah this is true with every glitch token, the distribution of the tokenizer and the GPT model is very different.
- mike_hearn 3y ago
  That was investigated here: https://www.lesswrong.com/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation?commentId=MYLFfeNfQsxjBJwkF https://www.lesswrong.com/posts/aPeJE8bSo6rAFoLqg/solidgoldm... The idea that tokens found closest to the centroid are those that have moved the least from their initialisations during their training (because whatever it was that caused them to be tokens was curated out of their training corpus) was originally suggested to us by Stuart Armstrong. He suggested we might be seeing something analogous to "divide-by-zero" errors with these glitches. However, we've ruled that out. The counting Reddit usernames are clearly a major source of glitch tokens, there's something about that sub that screws up the model, maybe the unusually predictable/repetitive nature of what goes on there or the sheer obsessiveness of the posters. The fact that the only non-counting Reddit usernames are both people at the center of massive Bitcoin psychodramas is suggestive however, especially given the associations with the petertodd token. My guess is that these names appear much more frequently in other people's posts than is normal for forum usernames (especially if it read bitcointalk.org and twitter too), and that maybe this has some effect. To get an idea of just how frequently this token will crop up in the reddit corpus, just do a search for it: https://www.reddit.com/search/?q=%22petertodd%22&sort=comments https://www.reddit.com/search/?q=%22petertodd%22&sort=commen... I'm not sure how many posts match but you can keep scrolling a long time. Having been more exposed than normal to what happened back then I wasn't hugely surprised by what concepts clustered there, and sadly don't think it's actually random or unexplainable. Flick through discussions pre-2015 (when the Bitcoin forums started to be heavily censored) and you'll see a lot of very similar words as what GPT spits out being used in connection. It was all very nasty.
  - samstave 3y ago
    [flagged]
    - mike_hearn 3y ago
      Here's my non expert explanation, take it for what it's worth. Tokens solve the following problem: the first layers of the neural net(s) are a big array of numbers, where the size is a hyperparameter (a parameter that can be used to change the size or behavior of the network). A typical size for a big model like the GPTs is larger than 50,000. You have to somehow encode language as a sequence of assignments to this array of numbers. How do you do it? The first and most obvious idea is characters. You could assign each unicode code point to one of the slots in the input array, and then use what they call a one-hot encoding where every number is zero except the character. You can do this, but it's not very efficient because virtually all the training text is written in Latin languages and so almost all the slots will be unused. A better way is to start with a big pile of text that you're going to use, and then iteratively assign the slots to sequences of characters based on how common they are. This makes it easier for the network to learn and reason. These sequences are tokens. For example "and" is very common, and so would "ing" (from the suffix), so those should get their own tokens. SuperGoldMagiCarp isn't so that really shouldn't - it should be represented as a sequence of tokens instead. There are algorithms that figure out the most efficient assignment of tokens to character sequences, which you can think of as the model's vocabulary, and then to convert text into a sequence of these token numbers. OpenAI's software is called Tiktoken and is written in Rust for speed. The output of the network is likewise also tokens, and so you run the process in reverse at the end to get text back out of the array of floats that the network produces. Or more accurately, the network produces a set of probabilities for each token in its vocabulary, and then you can pick the most probable (oversimplification - in reality the way you select the token is more complicated than that as otherwise you get bad results). The problems here are to do with bugs in the training process, but are no less interesting for that. Some character sequences that are very rare and should really be represented by many different tokens in a row have somehow ended up being considered important enough to be given their own whole token. The most common cause of this seems to be cases where the token vocabulary was computed on text that contained garbage highly repetitive text like debug logs from video games, hence the prevalence of obscure game characters like Leilan, and Reddit threads are clearly over-represented. But then GPT struggles to work out what these tokens actually mean because they hardly appears in the training set, and so these tokens seem to float together in space and get easily conflated inside the model, also they end up representing very vague or abstract concepts.
- neonate 3y ago
  That is a quote from https://twitter.com/goodside/status/1666609934635606017 https://twitter.com/goodside/status/1666609934635606017.
countmora 3y ago
> unfortunately the tokenizer was trained on this subreddit Do you have a source for that or was it just an assumption?
- gl-prod 3y ago
  There was a video[0] on Computerphile about this topic [0] https://www.youtube.com/watch?v=WO2X3oZEJOA https://www.youtube.com/watch?v=WO2X3oZEJOA
- mike_hearn 3y ago
  It's pretty much guaranteed. Where else on the internet would this sequence of characters appear so frequently that it gets selected as one of the internet's top ~50,000 words? Also, that Reddit is frequently used to train LLMs is widely known. It's an unusually clean source of conversational text because you can slice threads (i.e. pick a root comment, then pick a child, then a child of the child etc and then concatenate the results), and you'll get a coherent conversation. There are relatively few places on the internet where that is true. For example most phpBB forums conflate many different conversations into single threads, with ad-hoc quoting being used to disambiguate which post is replying to which. That makes it a lot harder to generate sample conversations from.
  - dontupvoteme 3y ago
    >There are relatively few places on the internet where that is true Imageboards. DailyMail. Slashdot. Even a somethingawful dump would have been superior.
    - mike_hearn 3y ago
      Slashdot doesn't have the volume. Don't know about image boards but are they threaded and do they cover as many topics? The Daily Mail (the newspaper) has been used for training LLMs in the past, yes. I don't know if it still is.
      - 3y ago
perfmode 3y ago
is this why reddit is charging for its API? to try to capture value from the entities training LLMs on reddit data?
- asddubs 3y ago
  that ship has probably sailed, since pushshift hosts a copy of all of reddit, including removed content. it's really weird to me that they even allowed that level of access for that long (FWIW I don't agree with the recent changes, but I see little legitimate reason to give someone a way to scan and copy all recently made posts across all subreddits).
  - pjc50 3y ago
    Archiving. https://news.ycombinator.com/item?id=36254172 https://news.ycombinator.com/item?id=36254172 It's very much "he who has the power to destroy a thing controls that thing"; so long as there's only one canonical copy of a post and it's on Reddit's servers, that's vulnerable to actions by the subreddit mods or Reddit themselves.
deleted 3y ago
[deleted]

jallen_dot_dev 3y ago

> ETIQUETTE: > 1. If you're counting, upvote your fellow counting comrades. Looks like a voting ring for farming karma. Not sure why reddit allows it.

hn_throwaway_99 3y ago
That's not what it is. It's really just kind of a wacky subreddit for bored and/or OCD people.
- Freedom2 3y ago
  I disagree, and agree with jallen. If nothing else, this is fraud! A voting ring like this has to be dismantled immediately, or else there will be significant ramifications, which im sure GP and expand on.
  - jallen_dot_dev 3y ago
    I know they're just Internet points but they are supposed to serve as a social signal that somebody has contributed (meaningful) content. Also some subreddits require a certain amount of karma to post. And finally, this activity is just useless spam. I never implied it was such a big deal as to warrant your snark.
    - LegionMammal978 3y ago
      > And finally, this activity is just useless spam. It's far from spam: it's a social activity. When "running" with someone, you post a comment with a count, watch your inbox patiently for the other person to post the next count, reply with the count after that, and repeat. In the process, you collaboratively climb the infinite ladder together. Hence the words of congratulations and thanks every time a milestone (a "get") is reached. Counters can and do hold side discussions along the way; pretty much no one comes to the subreddit to act like a perfect robot. Indeed, the other person's humanity is plainly observable in the variation in their response times. Also, the main visible karma on Reddit is post karma, and r/counting is the exact opposite of where you'd go to farm post karma, given that a new post on a given chain is only made every ~1000 counts.