n is counting the number of ML systems in the analysis at the point of writing. (We have added more systems in the meantime). An example for such a system is GPT-3, AlphaFold, etc. - basically a row in our dataset.
Right, good point. I’ll add the number of systems for the given time period.
That’s hard to answer. I don’t think OpenAI misinterpreted anything. For the moment, I think it’s probably a mixture of:
the inclusion criteria for the systems on which we base this trend
actual slower doubling times for reasons which we should figure out
Nonetheless, as outlined in Part 1 - Section 2.3, I did not interpret those trends yet but I’m interested in a discussion and trying to write up my thoughts on this in the future.
Thanks, Michael.
nis counting the number of ML systems in the analysis at the point of writing. (We have added more systems in the meantime). An example for such a system is GPT-3, AlphaFold, etc. - basically a row in our dataset.Right, good point. I’ll add the number of systems for the given time period.
That’s hard to answer. I don’t think OpenAI misinterpreted anything. For the moment, I think it’s probably a mixture of:
the inclusion criteria for the systems on which we base this trend
actual slower doubling times for reasons which we should figure out Nonetheless, as outlined in Part 1 - Section 2.3, I did not interpret those trends yet but I’m interested in a discussion and trying to write up my thoughts on this in the future.