saurkt

Yes, these things keep us up at night as well :-).

If you want access, please send an email to [turing_ AT _microsoft _DOT_ com]. Remove underscores and spaces.

We don't have an exact date, but, we plan to share more details in a later submission. If you want access, please send an email to [turing_ AT _microsoft _DOT_ com]. Remove underscores and spaces.

Thanks for your kind words. Yes, we would like to next train a language representation model. And our hunch is that probably something which is a mixture of language representation and language generation would be able to get the best of both worlds.

(Similar to the response for another question.) BERT is a language representation model while Turing-NLG is a language generation model (similar to GPT). They are not directly comparable (they can potentially be massaged to mimic the other, but, not something that we have done yet.)

SQUAD and GLUE are tasks for language representation models -- aka BERT-like. This is a language generation model -- GPT-like. Hence, SQUAD/GLUE test sets are not really applicable. We are reporting on the wikitext and lambada sets that openAI also uses for similar models (numbers are in the blogpost).

Not yet. We will try to run against those benchmarks soon.

One of the team members from Project Turing. Happy to answer any questions.