You can include multimodal data like images. There’s something strange about including images when going back to Roman times or 1700 because while they had texts, they didn’t have digital images. However, this is acceptable for some purposes. You’d want to avoid leaking information that could only be known in the present. You could include things people at the time could see and experience themselves. For example, there may be no anatomically accurate painting in Roman times of a bee or an egg cracking, but you can include such images because people could see such things, even if they weren’t part of their recorded media. You could also have pictures of buildings and artifacts that we still have from the past.
RadialB says he was able to start making this content because of the "huge jump" in the quality and availability of AI tools. It "hugely lowers the barrier for entry" for anyone who wants to make "fake stuff", he says.
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If executed well, Delaunay-based tetrahedral dithering can outperform the N-convex method and produce results that rival Knoll’s algorithm. The devil is in the detail however, as actually implementing a robust Delaunay triangulator is a non-trivial task, especially where numerical stability is concerned. The additional memory overhead required by the triangulation structure may also be a concern.