These methods may be too aggressive. Before we have ASARA, less capable AI systems may still accelerate software progress by a more moderate amount, plucking the low-hanging fruit. As a result, ASARA has less impact than we might naively have anticipated.
I’m confused.
My default assumption is that prior to ASARA, less-capable AIs will have accelerated software progress a lot — so I’m interested in working that into the model.
It looks like your “gradual boost” section is for people like me; you simulate the gradual emergence of the ASARA boost over a period of five years. But in the gradual boost section, you conclude that using this model results in a higher chance of >10yrs being compressed into one year. (I’m not currently following the logic there, just treating it as a black box.)
Why is the sentence “As a result, ASARA has less impact than we might naively have anticipated” then true? It seems this consideration actually ends up meaning it has more impact.
Yep, the ‘gradual boost’ section is the one for this. Also my historical work on the compute-centric model (see link in post) models gradual automation in detail.
So if you’ve fully ignored the fact that pre-ASARA systems have sped things up, then accounting for that will make takeoff less fast bc by the time ASARA comes around you’ll have already plucked much of the low-hanging fruit of software progress.
But I didn’t fully ignore that, even outside of the gradual boost section. I somewhat adjusted my estimate of r and of “distance to effective limits” to account for intermediate software progress. Then, in the gradual boost section, i got rid of these adjustments as they weren’t needed. Turned out that takeoff was then faster. My interpretation (as i say in the gradual boost section): dropping those adjustments had a bigger effect than changing the modelling.
To put it anothr way: if you run the gradual boost section but literally leave all the parameters unchanged, you’ll get a slower takeoff.
I’m confused.
My default assumption is that prior to ASARA, less-capable AIs will have accelerated software progress a lot — so I’m interested in working that into the model.
It looks like your “gradual boost” section is for people like me; you simulate the gradual emergence of the ASARA boost over a period of five years. But in the gradual boost section, you conclude that using this model results in a higher chance of >10yrs being compressed into one year. (I’m not currently following the logic there, just treating it as a black box.)
Why is the sentence “As a result, ASARA has less impact than we might naively have anticipated” then true? It seems this consideration actually ends up meaning it has more impact.
Yep, the ‘gradual boost’ section is the one for this. Also my historical work on the compute-centric model (see link in post) models gradual automation in detail.
So if you’ve fully ignored the fact that pre-ASARA systems have sped things up, then accounting for that will make takeoff less fast bc by the time ASARA comes around you’ll have already plucked much of the low-hanging fruit of software progress.
But I didn’t fully ignore that, even outside of the gradual boost section. I somewhat adjusted my estimate of r and of “distance to effective limits” to account for intermediate software progress. Then, in the gradual boost section, i got rid of these adjustments as they weren’t needed. Turned out that takeoff was then faster. My interpretation (as i say in the gradual boost section): dropping those adjustments had a bigger effect than changing the modelling.
To put it anothr way: if you run the gradual boost section but literally leave all the parameters unchanged, you’ll get a slower takeoff.