| ▲ | tristanj 4 hours ago |
| The models are trained on the conversations of hundreds of millions of people. ChatGPT has several billion conversations every day. I estimate that the model that solved Navier–Stokes was trained on data from nearly a trillion conversations. It's unknowable and not possible to prove if any one specific conversation was the key to solving Navier–Stokes. |
|
| ▲ | Pulcinella 3 hours ago | parent | next [-] |
| Do you not log the training data? Seems like you should be able to just check what was in the training data. To not keep track is just sloppy work and certainly unprofessional science. |
| |
| ▲ | tristanj 3 hours ago | parent [-] | | The burden of proof is on Buckmaster and Alpöge to reveal if they had the "Improve the model for everyone" setting enabled or disabled. OpenAI shouldn't be expected to reveal private user configuration data. You're asking them to perform a user privacy violation. | | |
| ▲ | whimsicalism 3 hours ago | parent [-] | | If the reason that OpenAI is unable to state whether they trained on this data is because they (as policy) do not reveal whether a given member has turned on/off the "Improve the model for everyone" setting, they can at least say so. FWIW, publicly facing OAI docs are very unclear about whether this setting even applies to Codex conversations. |
|
|
|
| ▲ | whimsicalism 3 hours ago | parent | prev | next [-] |
| I agree that it is not possible to prove if any one specific conversation (or derived RL tasks) was key to solving Navier-Stokes (at least without massive resource expenditure). I don't really understand how the quantity of training data/rollouts used in training is relevant to the question of whether or not it was trained on these conversations. I also don't really believe that whether or not this model was trained on these conversations is unknowable information. |
| |
|
| ▲ | DetroitThrow 4 hours ago | parent | prev | next [-] |
| >It's unknowable and not possible to prove if any one specific conversation was the key to solving Navier–Stokes. If the conversation was in the training set, there's a high likelihood that the small set of conversations related to solving Navier-Stokes was used by the model. I get Astra to still quote some of my friends' books or blogposts nearly verbatim on certain niche issues. Much more importantly, we _can_ determine whether a conversation was used in the training data. And if it was, it gives us a great idea whether that logic was captured in reasoning for a novel problem never yet solved. Given that you don't see any of this as below the belt according to your other comments, maybe your contribution here is more for yourself than a fair conversation about attribution. |
| |
| ▲ | tristanj 3 hours ago | parent [-] | | The flaw with this line of reasoning is that Buckmaster and Alpöge only had a partially completed proof of a weaker version of the Navier-Stokes problem. OpenAI's internal model solved the full, harder problem. This means the key information needed to bridge the gap was not present in Buckmaster and Alpöge's chat history. You might retort that ChatGPT used the training data to copy their approach, but the approach Buckmaster and Alpöge chose was already published by Luis and Diego in 2023 and in every frontier model's training set. | | |
| ▲ | whimsicalism 3 hours ago | parent | next [-] | | This argument proves too much. By this standard, it wouldn't have counted as copying their approach if the researchers had just fed in Levent & Buckmaster's paper verbatim as a prompt into the swarm. | | |
| ▲ | DetroitThrow 3 hours ago | parent [-] | | I don't think the person describing the paper by Buckmaster as the same as the 2023 paper by Córdoba and Martínez-Zoroa is really discussing this in good faith fwiw. There are some massive advancements within it and if the person was participating wasn't just regurgitating something to "win the argument" in their eyes, they wouldn't describe it that way. |
| |
| ▲ | tomcorrigan 2 hours ago | parent | prev | next [-] | | I’m pretty sure you think you are doing a good job of defending your employer and you probably believe “Open”AI are the good guys here. I also acknowledge that they butter your bread so your financial future currently depends on their success. However the way you are conducting yourself in public, while announcing yourself as an OpenAI employee is doing enormous harm to the greater and magnanimous aim of your organisation. Take a step back and read the temperature of the room. Being the smartest guy in the room will never protect you from alienating the rest of the room into a baying mob. Right now you are Icarus flying straight into the sun. | | |
| ▲ | senordevnyc 2 hours ago | parent | next [-] | | You’re confusing usernames, which is pretty ironic given your nasty comment. | |
| ▲ | tristanj 2 hours ago | parent | prev [-] | | I'm not an OAI employee and never pretended to be one are you high? |
| |
| ▲ | hellohello2 2 hours ago | parent | prev [-] | | I don't believe people are denying that the model is impressive. The problem is that learning someone else is making progress on a topic using method X and then rushing to scoop them borders on academic misconduct. If, on top of this, their private conversations about X were used in the proof, I really don't see how its defensible... | | |
| ▲ | tristanj 2 hours ago | parent [-] | | The rumor going around X was that Anthropic had solved a Millennium Prize problem weeks ago and was sitting on the solution, waiting to release it right before their IPO to maximize hype. If I were at OpenAI, I'd naturally want to snipe that from them. I am completely unsurprised they formed a crack team to steal Anthropic's glory, and do so in just five days. | | |
| ▲ | hellohello2 2 hours ago | parent [-] | | Between companies, direct malevolent competition is OK.
Between academics, there are other rules to the game.
When you go into a boxing match, you agree to get punched in the face. All this to say, trust is important, and grounded in social convention.
So I do agree with you, but also disagree. Whenever this is OK or not really depends on how the breakthrough is contextualized, and how there people at play, here, agree to contextualize it. In my view, in the blog post, there is much discussion about who will be publishing the paper. If instead it was just a blog post that said "oops, we beat you to it, our model is the best", it would have been different. |
|
|
|
|
|
| ▲ | hellohello2 2 hours ago | parent | prev | next [-] |
| Sorry but this is a misconception: these models are both capable of complete novelty and of plagiarism. For a concrete example, image diffusion models have been shown to reproduce many existing images nearly 100% exactly, yet clearly, they can also create new ones. A model being trained on lots of irrelevant information does not mean relevant information was not used. |
|
| ▲ | fwip 3 hours ago | parent | prev [-] |
| The IP laundering machine strikes again. |
