The <@biological anchors approach@>(@Draft report on AI timelines@) to forecasting AI timelines estimates the compute needed for transformative AI based on the compute used by animals. One important parameter of the framework is needed to “bridge” between the two: if we find that an animal can do a specific task using X amount of compute, then what should we estimate as the amount of compute needed for an ML model to do the same task? This post aims to better estimate this parameter, by comparing few-shot image classification in bees to the same task in ML models. I won’t go through the details here, but the upshot is that (after various approximations and judgment calls) ML models can reach the same performance as bees on few-shot image classification using 1,000 times less compute.
If we plug this parameter into the biological anchors framework (without changing any of the other parameters), the median year for transformative AI according to the model changes from 2050 to 2035, though the author advises only updating to (say) 2045 since the results of the investigation are so uncertain. The author also sees this as generally validating the biological anchors approach to forecasting timelines.
Planned opinion:
I really liked this post: the problem is important, the approach to tackle it makes sense, and most importantly it’s very easy to follow the reasoning. I don’t think that directly substituting in the 1,000 number into the timelines calculation is the right approach; I think there are a few reasons (explained [here](https://www.alignmentforum.org/posts/yW3Tct2iyBMzYhTw7/how-does-bee-learning-compare-with-machine-learning?commentId=rcJuytMfdQNMb82rR), some of which were mentioned in the post) to think that the comparison was biased in favor of the ML models. I would instead wildly guess that this comparison suggests that a transformative model would use 20x less compute than a human, which still shortens timelines, probably to 2045 or so. (This is before incorporating uncertainty about the conclusions of the report as a whole.)
Planned summary for the Alignment Newsletter:
Planned opinion: