• TheGrandNagus@lemmy.world
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    2 days ago

    Unless the dataset, weighting, and every aspect is open source, it’s not truly open source, as the OSI defines it.

    • Buffalox@lemmy.world
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      1 day ago

      The dataset is massive and impractical to share, and a dataset may include bias and conditions for use, and the dataset is a completely separate thing from the code. You would always want to use a dataset that fit your needs. From known sources. It’s easy to collect data. Programming a good AI algorithm not so much.
      Saying a model isn’t open source because collected data isn’t included is like saying a music player isn’t open source, because it doesn’t include any music.

      EDIT!!!

      TheGrandNagus is however right about the source code missing, investigating further, the actual source code is not available. and the point about OSI (Open Source Initiative) is valid, because OSI originally coined the term and defined the meaning of Open Source, so their description is per definition the only correct one.

      https://en.wikipedia.org/wiki/Open_source

      Open source as a term emerged in the late 1990s by a group of people in the free software movement who were critical of the political agenda and moral philosophy implied in the term “free software” and sought to reframe the discourse to reflect a more commercially minded position.[14] In addition, the ambiguity of the term “free software” was seen as discouraging business adoption.[15][16] However, the ambiguity of the word “free” exists primarily in English as it can refer to cost. The group included Christine Peterson, Todd Anderson, Larry Augustin, Jon Hall, Sam Ockman, Michael Tiemann and Eric S. Raymond. Peterson suggested “open source” at a meeting[17] held at Palo Alto, California, in reaction to Netscape’s announcement in January 1998 of a source code release for Navigator.[18] Linus Torvalds gave his support the following day