eli_sennesh comments on Debunking Fallacies in the Theory of AI Motivation - LessWrong

8 Post author: Richard_Loosemore 05 May 2015 02:46AM

You are viewing a comment permalink. View the original post to see all comments and the full post content.

Comments (343)

You are viewing a single comment's thread. Show more comments above.

Comment author: [deleted] 19 May 2015 03:59:17PM -1 points [-]

No, it does not. In sampling-based inference, the necessary computation time grows linearly with the demanded sample size, not exponentially. There may be diminishing returns to increasingly accurate probabilities, but that's a fact about your utility function rather than an exponential increase in necessary computational power.

This precise switch, from an exponential computational cost growth-curve to a linear one, is why sampling-based inference has given us a renaissance in Bayesian statistics.

Comment author: Lumifer 19 May 2015 04:28:40PM 2 points [-]

There may be diminishing returns to increasingly accurate probabilities, but that's a fact about your utility function

This has nothing to do with utility functions.

Sample size is a linear function of the CPU time, but the accuracy of the estimates is NOT a linear function of sample size. In fact, there are huge diminishing returns to large sample sizes.

Comment author: [deleted] 19 May 2015 05:03:19PM 0 points [-]

Ah, ok, fair enough on that one.