Let the algorithm that represents the brain of a typical new-born baby be denoted as B1.
Now surely we can agree that the brain of a new-born baby does not have sophisticated Bayesian machinary built into it? Yes, there must be *some* intrinsic built-in reasoning structure, but everything we know suggests that the intrinsic reasoning mechanisms of the human brain must be quite weak and simple. Let the algorithm which represents the brain of the baby B1 which grew up into a 20-year old with a PhD in Bayesian math be denoted as B2. Now somehow, the algorithm B1 was able to 'optimze' its original reasoning mechanisms by a smooth transformation into B2. (assume there was 'brain surgery', no 'hand coding'). The environment! you may shout. The baby got all its information from human culture (Reading math books, learning from math professors), you might try to argue, that's how B1 (baby) was able to transform into B2 (PhD in Bayes) But this cant be correct. Since, humans existed long before Bayesian math was developed. Every single Bayesian technique had to be developed by a human in the past, without being told. So in theory, B1 could have grown into B2 entirely on its own, without being told anything by anyone about Bayesian math. The conclusion: *There exists a very simple algorithm which is only a very weak approximation to PhD Bayesian reasoning, which is perfectly capable of recursive self-improvement to the PhD level! No hand coding of advanced Bayesian math is needed. Or to simply rephrase: Humans could reason before they discovered Bayes. --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Everything List" group. To post to this group, send email to [EMAIL PROTECTED] To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/everything-list?hl=en -~----------~----~----~----~------~----~------~--~---