Meta is accused of "bullying" the open-source community
Meta faces accusations of "bullying" the open-source community while trying to establish its AI models as the standard, creating a divide between purists and users attracted to its offerings.
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Meta is facing accusations of "bullying" the open-source community as it seeks to establish its artificial intelligence models as the standard in the field. The situation is likened to a scenario where a large corporation takes over a long-standing communal space, imposing new norms that clash with the existing culture. Open-source purists are expressing their concerns over Meta's approach, which they perceive as undermining the foundational principles of open-source collaboration. Despite the objections from these purists, many users are still drawn to Meta's offerings, indicating a divide within the community. The implications of Meta's actions could significantly impact the future of open-source AI development and the dynamics between large corporations and independent developers.
- Meta is accused of undermining the open-source community's principles.
- The company's efforts aim to set a new standard for AI models.
- There is a growing divide between open-source purists and users attracted to Meta's offerings.
- The situation reflects broader tensions between large corporations and independent developers in the tech space.
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11 commentsThe perfect is the enemy of the good, as usual.
All of this needs to stop.
The OSI's definition is still new. In fact it's still in draft form so this debate is a bit premature. I suspect that companies will begin releasing the code to train the model once it is finalized (they will never tell you the training data due to legal reasons and forcing them to is a losing battle).
This last sentence gave me a headache. He does not need to publish a bunch of possibly proprietary data owned by Meta, so no he won't bare it all. Data isn't free.
The model architecture and infrastructure are open source. That is what matters.
The fact that you get really good weights that result from millions of dollars of GPU time on extremely expensive-to-procure proprietary datasets is amazing, but even that shouldn't be a requirement to call this open source. That is literally just an output of the open source model trained on non-open source inputs.
I find it absurd that if I create a model architecture, publish my source code, and slap an open source license on it, I can call that open source…but the moment I publish some weights that are the result of running the program on some proprietary dataset, all of a sudden I can’t call it open source anymore.
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