Sounds like your solution to alignment is “if it’s not aligned, switch to a random different model instead”. Which would make sense if we could expect that a nontrivial fraction of models turns out to be magically aligned, so it’s just a question of sufficient shopping until we find one of them.
If the model is instead that by nature almost all models are misaligned, and we need to work hard to align them, then this only means throwing the existing work away and starting from anew, only with increasingly more powerful models.
It’s not magically aligned, it’s pointed in a random direction, and if you have choices, as long as you’re not too picky, you can find one that’s pointed in roughly the right direction along the few axes you care about on any particular task, instead of being forced to use the few that are adversarially crafted by the closed model producers at great expense to be opposed to you on every relevant axis.
Sounds like your solution to alignment is “if it’s not aligned, switch to a random different model instead”. Which would make sense if we could expect that a nontrivial fraction of models turns out to be magically aligned, so it’s just a question of sufficient shopping until we find one of them.
If the model is instead that by nature almost all models are misaligned, and we need to work hard to align them, then this only means throwing the existing work away and starting from anew, only with increasingly more powerful models.
It’s not magically aligned, it’s pointed in a random direction, and if you have choices, as long as you’re not too picky, you can find one that’s pointed in roughly the right direction along the few axes you care about on any particular task, instead of being forced to use the few that are adversarially crafted by the closed model producers at great expense to be opposed to you on every relevant axis.