Perhaps, but another possibility is that the more advanced models all end up being polyglots. The state of the art in machine translation already uses a single

Perhaps, but another possibility is that the more advanced models all end up being polyglots. The state of the art in machine translation already uses a single model trained on multiple languages[1], which results in better translations between languages it doesn't have a lot of examples for. If the same principle applies to other types of models, then training them on every possible dataset available regardless of language might yield better results. That could result in models that are fluent in hundreds of languages. (I'd be curious as to whether DALL-E understands prompts in languages other than English, has anyone tried?) [1]: https://ai.googleblog.com/2019/10/exploring-massively-multilingual.html https://ai.googleblog.com/2019/10/exploring-massively-multil...