This is probably only going to become important once model-generated data is used for pre-training (or fine-tuning that’s functionally the same thing as continuing a pre-training run), and this process is iterated for many epochs, like with the MCTS things that play chess and Go. And you can probably just alpaca any pre-trained model you can get your hands on to start the ball rolling.
The amplifications in the papers are more ambitious this year than the last, but probably still not quite on that level. One way this could change quickly is if the plugins become a programming language, but regardless I dread visible progress by the end of the year. And once the amplification-distillation cycle gets closed, autonomous training of advanced skillsbecomes possible.
This is probably only going to become important once model-generated data is used for pre-training (or fine-tuning that’s functionally the same thing as continuing a pre-training run), and this process is iterated for many epochs, like with the MCTS things that play chess and Go. And you can probably just alpaca any pre-trained model you can get your hands on to start the ball rolling.
The amplifications in the papers are more ambitious this year than the last, but probably still not quite on that level. One way this could change quickly is if the plugins become a programming language, but regardless I dread visible progress by the end of the year. And once the amplification-distillation cycle gets closed, autonomous training of advanced skills becomes possible.