Comment on The Irony of 'You Wouldn't Download a Car' Making a Comeback in AI Debates

• WalnutLum@lemmy.ml ⁨2⁩ ⁨months⁩ ago

  Whisper’s code and model weights are released under the MIT License. See LICENSE for further details. So that definitely meets the Open Source Definition on your first link.

  Model weights by themselves do not qualify as “open source”, as the OSAID qualifies. Weights are not source.

  Additional WER/CER metrics corresponding to the other models and datasets can be found in Appendix D.1, D.2, and D.4 of the paper, as well as the BLEU (Bilingual Evaluation Understudy) scores for translation in Appendix D.3.

  This is not training data. These are testing metrics.

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  • QuadratureSurfer@lemmy.world ⁨2⁩ ⁨months⁩ ago

    I don’t understand. What’s missing from the code, model, and weights provided to make this “open source” by the definition of your first link? it seems to meet all of those requirements.

    As for the OSAID, the exact training dataset is not required, per your quote, they just need to provide enough information that someone else could train the model using a “similar dataset”.

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    • WalnutLum@lemmy.ml ⁨2⁩ ⁨months⁩ ago

      Oh and for the OSAID part, the only issue stopping Whisper from being considered open source as per the OSAID is that the information on the training data is published through arxiv, so using the data as written could present licensing issues.

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      • QuadratureSurfer@lemmy.world ⁨2⁩ ⁨months⁩ ago

        Ok, but the most important part of that research paper is published on the github repository, which explains how to provide audio data and text data to recreate any STT model in the same way that they have done.

        See the “Approach” section of the github repository: github.com/openai/whisper?tab=readme-ov-file#appr…

        And the Traning Data section of their github: github.com/openai/whisper/blob/…/model-card.md#tr…

        With this you don’t really need to use the paper hosted on arxiv, you have enough information on how to train/modify the model.

        There are guides on how to Finetune the model yourself: huggingface.co/blog/fine-tune-whisper

        Which, from what I understand on the link to the OSAID, is exactly what they are asking for. The ability to retrain/finetune a model fits this definition very well:

        The preferred form of making modifications to a machine-learning system is:

        • Data information […]
        • Code […]
        • Weights […]

        All 3 of those have been provided.

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    • WalnutLum@lemmy.ml ⁨2⁩ ⁨months⁩ ago

      The problem with just shipping AI model weights is that they run up against the issue of point 2 of the OSD:

      The program must include source code, and must allow distribution in source code as well as compiled form. Where some form of a product is not distributed with source code, there must be a well-publicized means of obtaining the source code for no more than a reasonable reproduction cost, preferably downloading via the Internet without charge. The source code must be the preferred form in which a programmer would modify the program. Deliberately obfuscated source code is not allowed. Intermediate forms such as the output of a preprocessor or translator are not allowed.

      AI models can’t be distributed purely as source because they are pre-trained. It’s the same as distributing pre-compiled binaries.

      It’s the entire reason the OSAID exists:

      1. The OSD doesn’t fit because it requires you distribute the source code in a non-preprocessed manner.
      2. AIs can’t necessarily distribute the training data alongside the code that trains the model, so in order to help bridge the gap the OSI made the OSAID - as long as you fully document the way you trained the model so that somebody that has access to the training data you used can make a mostly similar set of weights, you fall within the OSAID

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