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Why not adapt and fine-tune from an existing base model, as their training is open ended and does not yet include the assistant role? If you are to train from scratch, what do the synthetic data, or the model's environment look like? Is this "embodiment" for the model grounded in a video game, a random narrative, or something else? Is there to be any components to the "experience" besides word/token input/output? What do you see as the benefit of this project, if it's successful?

the benefits would allow true async communication without tooling , i have come across a new perspective of transformers and it seems like just finetuning might work as well , it would be a random narrative just like how we as human beings  have a narrative behind every stimulus we receieve 

I have to push back on the randomness a little bit -- I'd say a human being's narrative is almost the opposite of random, we live in highly coherent, directed stories