The paper is an impressive testimony to the engineering sweat and tears they had to put in to get their model to generalize as well as it did. Like, just seeing a parameter set equal to 0.997 makes you think “huh, so did they try every value from 0.995 to 0.999?”—to say nothing of all the functional degrees of freedom. The end result is simpler than MCTS on the surface, but it doesn’t seem obvious whether it was any less effort by the researchers. Still plenty cool to read about though.
And also, yes, of course, it’s 2023 and shouldn’t someone have heard the fire alarm already? Even though this research is not directly about building an AI that can navigate the real world, it’s still pushing towards it, in a way that I sure wish orgs like DeepMind would put on a back burner relative to research on how to get an AI to do good things and not bad things if it’s navigating the real world.
The paper is an impressive testimony to the engineering sweat and tears they had to put in to get their model to generalize as well as it did. Like, just seeing a parameter set equal to 0.997 makes you think “huh, so did they try every value from 0.995 to 0.999?”—to say nothing of all the functional degrees of freedom. The end result is simpler than MCTS on the surface, but it doesn’t seem obvious whether it was any less effort by the researchers. Still plenty cool to read about though.
And also, yes, of course, it’s 2023 and shouldn’t someone have heard the fire alarm already? Even though this research is not directly about building an AI that can navigate the real world, it’s still pushing towards it, in a way that I sure wish orgs like DeepMind would put on a back burner relative to research on how to get an AI to do good things and not bad things if it’s navigating the real world.