![]() Check out ai_curio on Twitter for an endless stream of examples.Ĭopyright © 2021 IDG Communications, Inc. ![]() And these notebooks, themselves free to use under an MIT license, have spread across the internet like fanzines of decades past, being remixed, altered, translated, and used to produce astonishing works of art. To fill that gap, Ryan Murdoch and Katherine Crowson developed Colab notebooks that combined CLIP with other open source models, such as BigGAN and VQGAN, to make prompt-based generative artworks. While CLIP was fully open sourced, OpenAI’s generative neural network, DALL-E, was not. From solo designers to employees, promising new open source alternatives are everywhere. So many times, it’s even available on all major operating systems. Open source software tends to be more platform agnostic. First up, there’s OpenAI’s CLIP (Contrastive Language-Image Pre-training) model, a multimodal model for generating text and image vector embeddings. The best part is that open source design programs often work great as stand-alone tools, or alongside existing design stack. ![]() However, I think the open source components that have ignited this year’s explosion in generative art also deserve some recognition. The winners of the Bossies have traditionally been libraries, frameworks, platforms, and operating systems - the backbone of open source.
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