OpenAI Codex (which copilot grew out of IIRC), Amazon and Salesforce versions of Copilot exist. Huggingface Bloom was trained on a sizeable amount of public code. Tab9, now behind, was one of the earliest to combine public code repositories with Deep learning for smarter autocomplete. The data requirements for Transformer scaling mean any and all public facing repositories will be assimilated, whether Github, Gitlab, Stackoverflow or so on.
Wish more energy was spent on how to fund pretrained models that will also run efficiently on CPUs, fine-tuneable to one's language and local environment. Removing reliance on cloud services.
Curious about people's opinions on Dall-E 2 or Google Image-gen, which parallel pretty much the same thing with Renders, Illustrations and Paintings, or upcoming models doing the same for voice acting and music. Coders seem more excited about the potential of those tools.