How might I combine these two datasets? One is a binary market, the other is a date market. So for any date point, one is a percentage P(turing test before 2030) the other is a cdf across a range of dates P(weakly general AI publicly known before that date).
Here are the two datasets.
Suggestions:
Fit a normal distribution to the turing test market such that the 1% is at the current day and the P(X<2030) matches the probability for that data point
Mirror the second data set but for each data point elevate the probabilities before 2030 such that P(X<2030) matches the probability for the first dataset
Thoughts:
Overall the problem is that one doesn’t know what distribution to fit the second single datapoint to. The second suggestion just uses the distribution of the second data set for the first, but that seems quite complext.
”Why would you want to combine these datasets?”
Well they are two different views when something like AGI will appear. Seems good to combine them.
How might I combine these two datasets? One is a binary market, the other is a date market. So for any date point, one is a percentage P(turing test before 2030) the other is a cdf across a range of dates P(weakly general AI publicly known before that date).
Here are the two datasets.
Suggestions:
Fit a normal distribution to the turing test market such that the 1% is at the current day and the P(X<2030) matches the probability for that data point
Mirror the second data set but for each data point elevate the probabilities before 2030 such that P(X<2030) matches the probability for the first dataset
Thoughts:
Overall the problem is that one doesn’t know what distribution to fit the second single datapoint to. The second suggestion just uses the distribution of the second data set for the first, but that seems quite complext.
”Why would you want to combine these datasets?”
Well they are two different views when something like AGI will appear. Seems good to combine them.