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Thursday, May 30, 2019

Wolfram: Mining the Computational Universe

Intriguing half hour talk.  A response to the broad entry of AI,  or a claim to a new architecture of computation?    Just recently reexamined here the anniversary of Wolfram Alpha.

In the Edge:
Mining the Computational Universe
A Talk By Stephen Wolfram

I've spent several decades creating a computational language that aims to give a precise symbolic representation for computational thinking, suitable for use by both humans and machines. I'm interested in figuring out what can happen when a substantial fraction of humans can communicate in computational language as well as human language. It's clear that the introduction of both human spoken language and human written language had important effects on the development of civilization. What will now happen (for both humans and AI) when computational language spreads?

STEPHEN WOLFRAM is a scientist, inventor, and the founder and CEO of Wolfram Research. He is the creator of the symbolic computation program Mathematica and its programming language, Wolfram Language, as well as the knowledge engine Wolfram|Alpha. He is also the author of A New Kind of Science. 

Mining the Computational Universe

STEPHEN WOLFRAM: I thought I would talk about my current thinking about computation and our interaction with it. The first question is, how common is computation? People have the general view that to make something do computation requires a lot of effort, and you have to build microprocessors and things like this. One of the things that I discovered a long time ago is that it’s very easy to get sophisticated computation.

I’ve studied cellular automata, studied Turing machines and other kinds of things—as soon as you have a system whose behavior is not obviously simple, you end up getting something that is as sophisticated computationally as it can be. This is something that is not an obvious fact. I call it the principle of computational equivalence. At some level, it’s a thing for which one can get progressive evidence. You just start looking at very simple systems, whether they’re cellular automata or Turing machines, and you say, "Does the system do sophisticated computation or not?" The surprising discovery is that as soon as what it’s doing is not something that you can obviously decode, then one can see, in particular cases at least, that it is capable of doing as sophisticated computation as anything. For example, it means it’s a universal computer.  .... " 

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