4 ms·

The argument then becomes how to interpret "Open", not that you both agree. If they keep publishing their research, then OpenAI seems like a fine name to me.

OnlineGladiator 4y ago
And Russia never invaded Ukraine. You can stretch the meaning of a word all you want, it doesn't change the fact that the people misrepresenting the word are acting in bad faith.
- throwaway29812 4y ago
  What?
  - OnlineGladiator 4y ago
    According to Russia, they never invaded Ukraine. Russia is acting in bad faith. The point is you can misconstrue a word all you want, but you're only damaging your own credibility. OpenAI is likewise acting in bad faith. It's the same story with Google, and Facebook, and Tesla, and on and on and on. When the leaders are unethical you shouldn't expect anything else.
cardine 4y ago
They've largely stopped publishing.
- thesunkid 4y ago
  To be fair, they still published papers casually and published a ton of useful OOS recently. Whisper, Tiktoken, Point-E, you named it.
  - bayindirh 4y ago
    Are these papers reproducible, or do they have source attached to them, if applicable?
    - teruakohatu 4y ago
      Very few DL papers are 100% fully reproducible, in that you can get identical results and generate identical checkpoints, even when source is attached and benchmark datasets are used. I would say the vast majority published are not even close to be able to be reproduced. Full size LLMs are not able to be reproduced because the datasets are copyright and not distributable and you need millions of dollars worth of compute to fully train them. If a company is publishing enough detail about SoTA architectures for researchers to ballpark reproduce, that is a win in my book.
      - bayindirh 4y ago
        I'm not actually expecting them to be 100% reproducible. I'm more than familiar with the work required to do that. What I'm expecting is not holding back the secret sauce, as seen in some (or many) publications. My gripe is not limited to DL/ML/AI scope either. When I try to compare my results with the papers I cite, I generally can't find the formulae or the detailed method to reproduce the numerical method the paper claims, and this leaves us at the dark. All I can do is saying "Paper23 cites these results, and we surpass them at this, we are even at that, and they are better at the other thing", which I'm not comfortable doing. Not because they are not telling the truth, but I want to test my method against other methods on an even ground.
        teruakohatu 4y ago
        > My gripe is not limited to DL/ML/AI scope either. When I try to compare my results with the papers I cite, I generally can't find the formulae or the detailed method to reproduce the numerical method the paper claims, and this leaves us at the dark. I agree. So many don't even both including hyperparams, even when they publish the code. The Github Issues for their code are littered with questions asking about hyperparams. > All I can do is saying "Paper23 cites these results, and we surpass them at this, we are even at that, and they are better at the other thing", which I'm not comfortable doing. If you are achieving better results, on the same dataset, and you are not cheating in anyway, and others can reproduce your results, then I don't know what is wrong with saying you got a better result. Issues somewhat arise when you are using better hardware with more parameters or larger batch sizes than the original authors could have attempted. I think this accounts for the results in many papers.
DrBenCarson 4y ago
It’s not even open source lol I get the need to make money but at least contribute OSS to the community they’re building a product on….
koheripbal 4y ago
Semantic debates are largely irrelevant. It is what it is.

OnlineGladiator 4y ago

And Russia never invaded Ukraine. You can stretch the meaning of a word all you want, it doesn't change the fact that the people misrepresenting the word are acting in bad faith.

throwaway29812 4y ago
What?
- OnlineGladiator 4y ago
  According to Russia, they never invaded Ukraine. Russia is acting in bad faith. The point is you can misconstrue a word all you want, but you're only damaging your own credibility. OpenAI is likewise acting in bad faith. It's the same story with Google, and Facebook, and Tesla, and on and on and on. When the leaders are unethical you shouldn't expect anything else.

cardine 4y ago

They've largely stopped publishing.

thesunkid 4y ago
To be fair, they still published papers casually and published a ton of useful OOS recently. Whisper, Tiktoken, Point-E, you named it.
- bayindirh 4y ago
  Are these papers reproducible, or do they have source attached to them, if applicable?
  - teruakohatu 4y ago
    Very few DL papers are 100% fully reproducible, in that you can get identical results and generate identical checkpoints, even when source is attached and benchmark datasets are used. I would say the vast majority published are not even close to be able to be reproduced. Full size LLMs are not able to be reproduced because the datasets are copyright and not distributable and you need millions of dollars worth of compute to fully train them. If a company is publishing enough detail about SoTA architectures for researchers to ballpark reproduce, that is a win in my book.
    - bayindirh 4y ago
      I'm not actually expecting them to be 100% reproducible. I'm more than familiar with the work required to do that. What I'm expecting is not holding back the secret sauce, as seen in some (or many) publications. My gripe is not limited to DL/ML/AI scope either. When I try to compare my results with the papers I cite, I generally can't find the formulae or the detailed method to reproduce the numerical method the paper claims, and this leaves us at the dark. All I can do is saying "Paper23 cites these results, and we surpass them at this, we are even at that, and they are better at the other thing", which I'm not comfortable doing. Not because they are not telling the truth, but I want to test my method against other methods on an even ground.
      - teruakohatu 4y ago
        > My gripe is not limited to DL/ML/AI scope either. When I try to compare my results with the papers I cite, I generally can't find the formulae or the detailed method to reproduce the numerical method the paper claims, and this leaves us at the dark. I agree. So many don't even both including hyperparams, even when they publish the code. The Github Issues for their code are littered with questions asking about hyperparams. > All I can do is saying "Paper23 cites these results, and we surpass them at this, we are even at that, and they are better at the other thing", which I'm not comfortable doing. If you are achieving better results, on the same dataset, and you are not cheating in anyway, and others can reproduce your results, then I don't know what is wrong with saying you got a better result. Issues somewhat arise when you are using better hardware with more parameters or larger batch sizes than the original authors could have attempted. I think this accounts for the results in many papers.

DrBenCarson 4y ago

It’s not even open source lol I get the need to make money but at least contribute OSS to the community they’re building a product on….

koheripbal 4y ago

Semantic debates are largely irrelevant. It is what it is.