3 ms·

I'm not sure it's so easy to tell whether a given piece of data was in a training run at their scale. It's entirely possible they think the answer is no, but on

I'm not sure it's so easy to tell whether a given piece of data was in a training run at their scale. It's entirely possible they think the answer is no, but on the off-chance that it could be, they'd rather not say no and then later it turns out they did and then they're claimed to be lying. If you were them, unless you could 100% rule it out, you'd hedge and say you can't.

Catloafdev 17d ago
It may not be easy, quick, or simple to figure that out - absolutely fair. But it is knowable. Their entire business is built around training models - they have the ability to know exactly what was in any given training run. I guess time will tell.
- m00x 17d ago
  It would be very difficult to say. It confirms that Tristan's data is likely part of the data the models use, but a lot of filtering, pruning, and transform goes into training. Data has to be determined to be signal and not just noice, then it could go through processes of generating questions/answers from that data, then it RLHF's over this. OpenAI have petabytes of data, all anonymized. It could take months to say for sure it was part of the training, and even more time to determine if it made any difference.
  - Catloafdev 17d ago
    Frankly, I don't buy this difficulty argument. They know which model was used to come up with that particular idea. A text search over the corpus of user data used in the training set can only take so long.
    - vlovich123 17d ago
      I think you may be underestimating how difficult a text search over their data is. They may have to build new mechanisms to do this. And what you really want is also an attribution of how much of a contribution a given corpus made which is a much harder question to answer; a single appearance of a chat probably has very little impact on the inference performance at this time unless it’s been explicitly preferenced somehow
      - Catloafdev 17d ago
        I don't think anyone really cares about 'the measured impact the data had on the exact result' - a question which is fundamentally difficult to answer accurately in the first place - but rather whether the data was used in training at all - which as Tristan described, was extensive, beyond simply a 'single chat.' Can you explain the difficulty in engineering a search apparatus over a corpus of text data? Actually searching through it may not be easy, sure, but it's work that's doable, and creating an index is relatively trivial.
        JoshTriplett 17d ago
        > Can you explain the difficulty in engineering a search apparatus over a corpus of text data? My guess: "If we ever imply that's possible, people might start asking questions about all the other work we've ripped off, so the official answer is that it's impossible".
      - dd8601fn 17d ago
        If they literally can’t audit training data for a given model, they shouldn’t be operating.
        JumpCrisscross 17d ago
        > If they literally can’t audit training data for a given model, they shouldn’t be operating They can operate. They shouldn’t be claiming credit for discovering anything.
    - benmathes 17d ago
      I worked in the tracing and tracking all the thousands of data sets that got tweaked and permuted and changed hands between thousands of researchers and data engineers at a major lab. The data that goes into training runs is permuted so much from the OG data that tracing the lineage is not trivial (dramatic understatement). And the difficulty is harder than just the extreme scale of text searching. but also explodes with organizational difficulty since there are so many people tweaking/shifting data independently upstream of the actual training run, and no they will not all add the telemetry you wish they did. In the ideal, should it be this hard? Well, no, but that's org wrangling for you.
      - ashkankiani 17d ago
        It feels convenient to not spend time on engineering around tooling that could be used to answer a question like “did you violate copyright by training on X?”
        deleted 17d ago
        [deleted]
        benmathes 17d ago
        Don't attribute to malice what is better explained by coordination headwinds in extremely large companies. The engineering around tooling wasn't remotely the issue. It's getting all the (thousands?) data researchers mostly iterating on fine tuning datasets that would get bristly if they couldn't work outside version control in a python notebook iteratively tweaking their dataset that processed and reprocessed a few datasets until a threshold was reached. The only _guaranteed_ chains of custody are down at the compute job and file read level. Which in a massively distributed computing job is... [redacted] nodes reading [redacted] fanouts of "datasets" that is just an abstraction over [redacted] individual files. There's no malice here. Just way way way more complex than you'd first think.
        ashkankiani 15d ago
        The malice would be in not prioritizing the provenance tool at the start as a requirement of the rest of the product. Ethics would tell you that if you can't make the product in an ethical way, then you probably shouldn't make it.
    - mapontosevenths 17d ago
      > A text search over the corpus of user data used in the training set can only take so long. Did you notice the line in the article that says the models had access to an offline copy of THE INTERNET. Like all of it.
scott_weber 17d ago
It should be quite easy: if they don't leak the user session data publicly, and don't commingle it with training data internally, how could it possibly end up in the training data? What surprises me is they're not more boldly/plainly lying about it.
- vlovich123 17d ago
  Unless they know exactly the researcher’s account, they may not know in their end if he had the setting to let them train on his chat logs. They also probably don’t know if he had any correspondence on any forum where he may have discussed this and it got picked up by scrapers. I’m not saying they didn’t do anything unethical. I’m just saying even if they were ethical, there’s plenty of practical reasons at their scale why a flat out denial is logistically difficult to do
- sebzim4500 17d ago
  I think they are pretty clear that they train on some prompts, given they sell the ability to be excluded
- remus 17d ago
  How would they know for sure that some details were not part of some other training data they use? The authors may have discussed some tangential details on a forum for example, in which case you might argue that the model picked up on these details the authors assumed were benign but novel and worked out how to apply them to the problem.
freejazz 17d ago
They are already claimed to be liars
ummonk 17d ago
Especially because the data that gets fed into training is first anonymized, so they’d need to look for navier stokes related stuff in the anonymized training set and then get make some sort of ad hoc process (with Tristan’s permission and sign off from legal) to compare the training data against his chats / Codex sessions to check if anything matches up. And that assumes his chats / sessions are still there, and not deleted to compare against.
- varjag 17d ago
  If the method is indeed found in the training set it's not particularly important to de-anonymize it. You have the proof you need.

Catloafdev 17d ago

It may not be easy, quick, or simple to figure that out - absolutely fair. But it is knowable. Their entire business is built around training models - they have the ability to know exactly what was in any given training run. I guess time will tell.

m00x 17d ago
It would be very difficult to say. It confirms that Tristan's data is likely part of the data the models use, but a lot of filtering, pruning, and transform goes into training. Data has to be determined to be signal and not just noice, then it could go through processes of generating questions/answers from that data, then it RLHF's over this. OpenAI have petabytes of data, all anonymized. It could take months to say for sure it was part of the training, and even more time to determine if it made any difference.
- Catloafdev 17d ago
  Frankly, I don't buy this difficulty argument. They know which model was used to come up with that particular idea. A text search over the corpus of user data used in the training set can only take so long.
  - vlovich123 17d ago
    I think you may be underestimating how difficult a text search over their data is. They may have to build new mechanisms to do this. And what you really want is also an attribution of how much of a contribution a given corpus made which is a much harder question to answer; a single appearance of a chat probably has very little impact on the inference performance at this time unless it’s been explicitly preferenced somehow
    - Catloafdev 17d ago
      I don't think anyone really cares about 'the measured impact the data had on the exact result' - a question which is fundamentally difficult to answer accurately in the first place - but rather whether the data was used in training at all - which as Tristan described, was extensive, beyond simply a 'single chat.' Can you explain the difficulty in engineering a search apparatus over a corpus of text data? Actually searching through it may not be easy, sure, but it's work that's doable, and creating an index is relatively trivial.
      - JoshTriplett 17d ago
        > Can you explain the difficulty in engineering a search apparatus over a corpus of text data? My guess: "If we ever imply that's possible, people might start asking questions about all the other work we've ripped off, so the official answer is that it's impossible".
    - dd8601fn 17d ago
      If they literally can’t audit training data for a given model, they shouldn’t be operating.
      - JumpCrisscross 17d ago
        > If they literally can’t audit training data for a given model, they shouldn’t be operating They can operate. They shouldn’t be claiming credit for discovering anything.
  - benmathes 17d ago
    I worked in the tracing and tracking all the thousands of data sets that got tweaked and permuted and changed hands between thousands of researchers and data engineers at a major lab. The data that goes into training runs is permuted so much from the OG data that tracing the lineage is not trivial (dramatic understatement). And the difficulty is harder than just the extreme scale of text searching. but also explodes with organizational difficulty since there are so many people tweaking/shifting data independently upstream of the actual training run, and no they will not all add the telemetry you wish they did. In the ideal, should it be this hard? Well, no, but that's org wrangling for you.
    - ashkankiani 17d ago
      It feels convenient to not spend time on engineering around tooling that could be used to answer a question like “did you violate copyright by training on X?”
      - deleted 17d ago
        [deleted]
      - benmathes 17d ago
        Don't attribute to malice what is better explained by coordination headwinds in extremely large companies. The engineering around tooling wasn't remotely the issue. It's getting all the (thousands?) data researchers mostly iterating on fine tuning datasets that would get bristly if they couldn't work outside version control in a python notebook iteratively tweaking their dataset that processed and reprocessed a few datasets until a threshold was reached. The only _guaranteed_ chains of custody are down at the compute job and file read level. Which in a massively distributed computing job is... [redacted] nodes reading [redacted] fanouts of "datasets" that is just an abstraction over [redacted] individual files. There's no malice here. Just way way way more complex than you'd first think.
        ashkankiani 15d ago
        The malice would be in not prioritizing the provenance tool at the start as a requirement of the rest of the product. Ethics would tell you that if you can't make the product in an ethical way, then you probably shouldn't make it.
  - mapontosevenths 17d ago
    > A text search over the corpus of user data used in the training set can only take so long. Did you notice the line in the article that says the models had access to an offline copy of THE INTERNET. Like all of it.

scott_weber 17d ago

It should be quite easy: if they don't leak the user session data publicly, and don't commingle it with training data internally, how could it possibly end up in the training data? What surprises me is they're not more boldly/plainly lying about it.

vlovich123 17d ago
Unless they know exactly the researcher’s account, they may not know in their end if he had the setting to let them train on his chat logs. They also probably don’t know if he had any correspondence on any forum where he may have discussed this and it got picked up by scrapers. I’m not saying they didn’t do anything unethical. I’m just saying even if they were ethical, there’s plenty of practical reasons at their scale why a flat out denial is logistically difficult to do
sebzim4500 17d ago
I think they are pretty clear that they train on some prompts, given they sell the ability to be excluded
remus 17d ago
How would they know for sure that some details were not part of some other training data they use? The authors may have discussed some tangential details on a forum for example, in which case you might argue that the model picked up on these details the authors assumed were benign but novel and worked out how to apply them to the problem.

freejazz 17d ago

They are already claimed to be liars

ummonk 17d ago

Especially because the data that gets fed into training is first anonymized, so they’d need to look for navier stokes related stuff in the anonymized training set and then get make some sort of ad hoc process (with Tristan’s permission and sign off from legal) to compare the training data against his chats / Codex sessions to check if anything matches up. And that assumes his chats / sessions are still there, and not deleted to compare against.

varjag 17d ago
If the method is indeed found in the training set it's not particularly important to de-anonymize it. You have the proof you need.