I haven't heard of that being tried (though I don't read everything.) Someone could do the experiment and write it up, and maybe get it published. The main ML conferences rarely publish anything that's not an improvement on the SOTA, which is why it's so hard to find anything about ideas that don't quite work.
The underlying motivation to my thoughts and comments is investigating if a decentralized but periodically coordinated algorithm for training LLMs exists. We have millions of GPUs distributed across the world which if they could somehow be put to work on training without extreme requirements on data transfer between them could enable training of large LLMs in an open source way even if that training is technically energy suboptimal.
Comments
I haven't heard of that being tried (though I don't read everything.) Someone could do the experiment and write it up, and maybe get it published. The main ML conferences rarely publish anything that's not an improvement on the SOTA, which is why it's so hard to find anything about ideas that don't quite work.
The underlying motivation to my thoughts and comments is investigating if a decentralized but periodically coordinated algorithm for training LLMs exists. We have millions of GPUs distributed across the world which if they could somehow be put to work on training without extreme requirements on data transfer between them could enable training of large LLMs in an open source way even if that training is technically energy suboptimal.