What Is Your Take on Stephen Wolfram's "A New Kind of Science"?

I think it's interesting because Wolfram stumbled upon something quite profound that (from my perspective) is under appreciated by the majority of working physicists and mathematicians:

Computation arises from very simple axiomatic systems, in surprising ways, and that in turn has profound implications for quite a number of things.

But people have been playing with constructive mathematics as a foundation for a long time, but Wolfram doesn't seem to acknowledge that.

I think a lot of us who studied computer science forgot some of the magical epiphanies we had when learning about the nature of computation, so it's always fascinating when Physicists re-derive something in the field.

It's probably similar to how they view it when CS folk wade into discussion on QM and reach enlightenment.

Finally though, I give Wolfram a ton of credit not necessarily for his book, but for actually trying to derive modern physics from (his) version of constructive mathematics.

It's not often you see someone really pushing on something like this in public and willing to discuss their progress in real time.

I like it.

It made me realize why structures in biology might arise in very short time spans "fully formed" as opposed to the the relatively slow process of natural selection (which is an important part of the evolutionary process, but strikes me as insufficient given the short time scales at play).

It makes sense if simple rules can create complex structures. Then it would just be a matter of "exploring" this universe of complex structures which would likely produce this wild assortment of distinct organisms, gradually shaped and refined over time.

I don't think it's the full picture, but it adds an interesting perspective I never considered before.

The non-online version is an excellent element in an improvised monitor stand.

It’s not science.

After two decades, zero predictions of any phenomena in nature. Please correct me if I’m mistaken.

Performing a calculation that produces patterns that sort of resemble some natural forms is not a prediction of anything.

The illustrations are gorgeous and thought provoking. The text wildly overstates its own importance and boils down to "simple chaotic systems are cool (and everywhere (and occasionally isomorphic))".

Verdict: good to flip through when you're in an expansive mood.

http://bactra.org/reviews/wolfram/

"As the saying goes, there is much here that is new and true, but what is true is not new, and what is new is not true; and some of it is even old and false, or at least utterly unsupported."

Its an exploration on the fact that not everything has a math equation that can be applied to it.

Most of the book deals with unique aspects of this, but its definitely not new. Anyone who has done CFD in depth already knows this. Computing turbulence is a game of approximation, because if you want results at a certain point, you basically have to start simulating very small areas of air in parallel and their interactions with one another in terms of particle momentum, temperature, density, e.t.c. (which is pretty much how reality works).

The "science" aspect is his claim that researchers should focus on studying this phenomenon as explanation for everything in the universe, missing the fact that a) this already happens and b) in many cases, actual math is much quicker.

The more interesting thing in recent years is this concept is very key to AGI (in the sense of all knowing all powerful AI) being pretty much highly impossible.

When a new technology is discovered, it takes a while for it to be woven into the fabric of everyday life. There are many new connections to the existing ways of doing things that get discovered in due course. Stephen has a head start on the rest of us, but I believe there are plenty of practical uses to the areas of math nearby to physics that he's mapping out for us all.

I think the fundamental idea of "start thinking in graph structures for spacetime instead of rubber sheets" is good and going to eventually pay off. But right now it doesn't offer anything testable and thus is useless for anything but thinking about while high.

Cellular automata bridged math and CS for me and it's beautifully chaotic. It's the same backwards with deep learning. Chaos to structure in classifying numbers or "doing" math.

It's the unexpected that's exciting.

It’s intriguing as a thought experiment that gives insight into how the complex physical structure of the world can emerge due to interactions of pieces according to (some known but many as yet unknown) locally embedded rules.

It seems intuitively correct as an analogy. And maybe obvious and not so new as the name claimed, as others have pointed out.

Beyond that I’m glad for him that he has Wolfram language to play with, because that seems much more practical, more about doing stuff, not just ruminating.

My take: It is poorly written and has low impact

A complete waste of time.

Life-changing demonstration of the power of emergency systems!

Have you seen the stuff he "works on" lately? What a pretentious use of pseudo-scientific jargon that means absolutely nothing. If someone piles on layers upon layers of concepts over many years, but nobody else uses those concepts, this is not science, not even a "new kind" of science.

My gut tells that deep learning works because of a similar underlying mathematics.

I have absolutely no mathematical proof.

But then again there is no cost to trusting my hunch…except maybe a few karma points if someone decides my opinion is worth being upset over.

I mean no matter how wrong I might be, nobody is going to die because of it.

Anyway, I think it is an important book and most of the negativity around it is because people feel threatened by Wolfram. Successful as a scientist, scholar, software developer, startup founder, and business executive.

YMMV.