That is interesting. I was aware of the growth of Monte Carlo sampling due to its use in Go AI, and I have an interest in the philosophical aspects of statistical inference though I haven’t follwed up on it quite to the extent that I would like. One of the things I’m currently picking at is An Introduction to Kolmogorov Complexity by Li and Vitanyi. I started looking into it after seeing the discussions about complexity and Solomonoff induction on this site.
However, I am still unclear as to why this is more lucrative than other areas related to AGI.
Ah, now I see what angle you are coming at this from. Yes, data mining techniques would certainly be invaluable to an AGI (which needs to be able to organize its input data into useful information) as well as lucrative to any number of companies. I saw a talk by John Hopcroft a while back that made it seem very appealing.
That is interesting. I was aware of the growth of Monte Carlo sampling due to its use in Go AI, and I have an interest in the philosophical aspects of statistical inference though I haven’t follwed up on it quite to the extent that I would like. One of the things I’m currently picking at is An Introduction to Kolmogorov Complexity by Li and Vitanyi. I started looking into it after seeing the discussions about complexity and Solomonoff induction on this site.
However, I am still unclear as to why this is more lucrative than other areas related to AGI.
See http://www.sciencemag.org/site/special/data/
Ah, now I see what angle you are coming at this from. Yes, data mining techniques would certainly be invaluable to an AGI (which needs to be able to organize its input data into useful information) as well as lucrative to any number of companies. I saw a talk by John Hopcroft a while back that made it seem very appealing.