Very very wrong.

Here is the relevant portion of Wei Dai's post:

These considerations lead to the following design for the decision algorithm S. S is coded with a vector <P1, P2, P3, ...> of programs that it cares about, and a utility function on vectors of the form <E1, E2, E3, …> that defines its preferences on how those programs should run. When it receives an input X, it looks inside the programs P1, P2, P3, ..., and uses its "mathematical intuition" to form a probability distribution P_Y over the set of vectors <E1, E2, E3, …> for each choice of output string Y. Finally, it outputs a string Y* that maximizes the expected utility Sum P_Y(<E1, E2, E3, …>) U(<E1, E2, E3, …>). (This specifically assumes that expected utility maximization is the right way to deal with mathematical uncertainty. Consider it a temporary placeholder until that problem is solved. Also, I'm describing the algorithm as a brute force search for simplicity. In reality, you'd probably want it to do something cleverer to find the optimal Y* more quickly.)

If I am reading him correctly, he uses the letter "P" in two different ways. In one use, he writes Pi, where i is an integer, to denote a program. In the other use, he writes P_Y, where Y is an output vector, to denote a probability distribution.

I was referring to the second use.