Matt, Yours is a remarkable posting - with SO much crammed into just two paragraphs. Several disciplines would benefit if you were to write this in more bite-sized pieces spread over several pages, with explanations mixed in. Or, perhaps, I have simply missed a VERY important article?
Steve On 10:29AM, Fri, Jun 15, 2018 Matt Mahoney via AGI <agi@agi.topicbox.com> wrote: > On Thu, Jun 14, 2018 at 10:40 PM Steve Richfield via AGI > <agi@agi.topicbox.com> wrote: > > > > In the space of real world "problems", I suspect the distribution of > difficulty follows the Zipf function, like pretty much everything else does. > > A Zipf distribution is a power law distribution. The reason that power > law distributions are so common over different domains (for example, > wealth distribution or population of cities) is the same reason that > Gaussian normal distributions are common. When you add a large set of > small random variables, the result is Gaussian by the central limit > theorem. When you multiply instead of add, you get a power law > distribution, which is the exponential of a Gaussian. It happens > whenever small random variations are in proportion to the magnitude of > the variable. > > So yes, the distribution of problem difficulty over broad domains is > Zipf or power law. It is why intelligence (as measured by problem > solving ability) is proportional to the log of computing power. The > value of intelligent systems grows linearly while their power grows > exponentially by Moore's law. > > -- > -- Matt Mahoney, mattmahone...@gmail.com ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T5ada390c367596a4-Mc9b631b2083c956f6cd6d8bf Delivery options: https://agi.topicbox.com/groups
