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How many proper open-source LLMs are there?
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this post was submitted on 01 Sep 2026
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I recall OpenAI saying to a courtroom judge that modern AI requires training off copyrighted material. And obviously the AI labs cannot just release those.
Distlled models (aka models that train themselves off the responses from other AI models) could probably release all the AI responses they used for training, since afaik AI generated content is not copyrightable..
However I suspect that most modern models are built from previous models. For example Claude Fable is probably based on Claude Sonnet or something. And for a downstream model to be fully "open source" and reproducible, you would need to reproduce the upstream model too. So even if a downstream model didn't use copyrighted data (eg it only used distills), one of the upstream models likely did.
They could still release a manifest of hashed contents and metadata.
What would be an application for this? More transparency for court cases? Or enable people to search for an alternative source for the data, like a torrent?
It would allow users to audit the dataset for ethical concerns, to interrogate the set to understand what a model does and does not "know", to identify weaknesses and biases, and to ensure that nothing has been inserted specifically to engineer prompt responses. Just examples off the top of my head.
Knowledge should be relatively impossible, though, if you just get the names and hashsums of the files? I mean I guess you could look up if a specific file you already have is in it. Might have some application. It needs to be very detailed, though. If they just call it GitHub-dump-timestamp or Wikipedia-dump-2026 with some overall hash, that doesn't tell us anything.
Most resources have a URI, Universal Resource Identifier. Related to a URL, except that it doesn't necessarily tell you how to locate the resource it identifies, URIs have dozens of schemas (eg isbn: for books) that can identify virtually any kind of media. Ideally they would tell us the URI, all metadata, source/provenance/licensing information, and the hash of the resource. If they truly are training on anonymous unattributed blobs that they just mysteriously found in their dataset, well that would be interesting to learn.