Why don’t you tell us how to think about the AGI problem?
George Pylos

To make significant progress on a hard problem, one has to first understand the approaches that are based on incorrect assumptions.

You should read a lot more of my posts to get an understanding of the approach to AGI. That approach does not include what I believe to be intellectual baggage.

The reason Bayesian statistics should not be used is because it is a subjective and flawed approach. What about probability? Probability is a mathematical tool that has value, however, probability should not be used as the mechanism for AGI. Probability has always been used as a tool to explain systems of many parts. There is nothing wrong with that use.

However, when the approach uses Probability as the mechanism that leads to AGI, then that is incorrect. In this article, you can see that stochasticity found in Deep Learning is not intrinsic. Therefore, one should not assume that Deep Learning uses probability as its mechanism.

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