Note that there are several phases of takeoff. We have the current ramp of human efforts into AI which is accelerating results. We have AI potentially self improving, which is already in use in gpt-4. (See the rrbm rubrics where the model grades itself and this is used for RL learning)
And then we have a “pause” where the models have self improved to the limits of either data, compute, or robotics capacity. I expect this to happen before 2030.
But the pause is misleading. If every year the existing robotics fleet is used to add just 10 percent more to itself, or add just 10 percent more high quality scientific data or human interaction data to the existing corpus, or build 10 percent more compute, this is a hard exponential process.
It will not slow down until the solar system is consumed. (The slow down from there being obviously the speed of light)
Note that there are several phases of takeoff. We have the current ramp of human efforts into AI which is accelerating results. We have AI potentially self improving, which is already in use in gpt-4. (See the rrbm rubrics where the model grades itself and this is used for RL learning)
And then we have a “pause” where the models have self improved to the limits of either data, compute, or robotics capacity. I expect this to happen before 2030.
But the pause is misleading. If every year the existing robotics fleet is used to add just 10 percent more to itself, or add just 10 percent more high quality scientific data or human interaction data to the existing corpus, or build 10 percent more compute, this is a hard exponential process.
It will not slow down until the solar system is consumed. (The slow down from there being obviously the speed of light)