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After a few iterations, I think I understand the point of this piece. It was a bit difficult to hone in on, though.

The article suggests that working out the theory of something like rule production systems, and then figuring out how that theory relates to existing insights from physics, is the best path toward a Fundamental Theory of Physics.

My primary source of skepticism stems from the fact that the theory of rule production systems is not exactly a new area of study. It's been well-developed at various points in time and from various perspectives by the theoretical CS, programming language theory, automated theorem proving, and mathematical logic communities. That theory addresses most of Stephen's "big difficult questions" about the non-physics side of things. For example, his "emulation cones" are a new name for a very old and extremely well-studied idea. The term "rulial space", similarly, is a new name for an idea that's well-developed in programming language theory.

I sympathize with Stephen. In fact, he sounds a bit like I did early in my scientific career. Unfortunately, though, I just don't see how these old well-understood ideas from computer science are going to result in a new fundamental theory of physics.



>For example, his "emulation cones" are a new name for a very old and extremely well-studied idea. The term "rulial space", similarly, is a new name for an idea that's well-developed in programming language theory.

What are the old names for these ideas?


Have ideas from computer science had significant reach inside theoretical physics before? It seems like physics has only recently discovered its love-affair with information theory, but information theory had existed for a long time before quantum information theory became a hot area of study. Maybe what's new here are not the ideas themselves, but bringing them into an area of study that hasn't payed attention to them before.


Maybe. I doubt it, though. There has always been substantial cross-talk between CS/information theory and Physics. Even through the 1990s it was difficult to be a computer scientist without eventually coming into contact with a non-trivial number of physicists. Especially in industrial research labs. Bell Labs, PARC, and IBM Research were full of physicists. Bell Labs and PARC are dead, but AFAIK IBM Research still has a bunch of physicists and the newer kids on the block (Google Research, FAIR, Deepmind, Microsoft Research, Intel, AMD) also have a share of physicists.

Besides, Stephen's approach here is to ignore 15-20 years of research from various CS sub-communities; his best case scenario is spending a decade reinventing that wheel. The problem with cross-talk that isn't "humble on both sides" is that it's either a) a waste of time because one side's ideas aren't that important, or else b) a waste of time because one side has to reinvent the other wise.


I really think that cross-domain concepts are almost the only way to make huge leaps, so that's a precondition in my mind for any advancement. Check.

In terms of "humility on both sides", it's such a common theme that this oft-cited assumption is taken as truth. Some of the greatest minds who had the most impact in our history were also insufferable assholes, who were stubborn and would not yield until people were forced to reckon with their ideas. Is this me defending Wolfram's ideas? No. But it's me defending the idea that "humility and civility" as a prerequisite for scientific advancement seems false, and in fact, in stagnant fields, the need for a disruptive personality who happens to be right may be perhaps the only real way out of the rut.


Sure. The problem here is that exactly the ideas he's proposing to explore have already been explored. I've slightly edited my previous comment to point this out.

The problem, in the very particular case of this blog post, is that the cost for lacking intellectual humility is spending time reinventing other people's wheels. And those wheels won't get him as far as he thinks they will. We know because they've already been built by others.


That makes sense. I can't assess your argument given my lack of understanding. In my own experience though, deriving things from first principles, even if they've been re-invented countless other times, is a good way to build up the intellectual super structures necessary to think new thoughts.

I think we should separate:

- Wolfram acting as though he thought of the ideas first

- Wolfram being underinformed so as to undermine his own progress

People typically get bent out of shape on the former, which is in evidence, and is a problem of politics. The latter, we can't prove or disprove unless you see him drawing significant conclusions that are falsifiable via current understanding. If that is the case, then I'll yield. But I suspect Wolfram may be more well read than he lets on, but for whatever reason, has a dysfunctional personality trait where he sees his own wrangling with ideas already put forth as a form of authorship, when he incorporates it into his long chain of analysis that he's been doing for decades. A potential analogy is one of "re-branding" - but in this case it's re-branding as part of an internal narrative, one where in the final chapter, Wolfram sees himself as the grand author of the unified theory. In that mental model, each idea he draws from is not one he cobbles together into a unified form, but instead, ideas he incorporates and reinterprets in his own bespoke system and methods, leading him to forget that the core ideas are not his own. (I'm definitely reaching here, but trying to to highlight how the two things above could be in fact very materially divergent and consistent with the evidence.)


You say:

> Wolfram [is] acting as though he thought of the ideas first.

This is called plagiarism. Independent reinvention is no defense if you keep on acting as though you had the idea first. He has already been informed many times that parts of his work are not original, and his behavior doesn't change.

And he knows it, on some level. He made the decision to communicate his "discoveries" in press releases and self-published books. He knows he's not subjecting himself to peer review. He may know, on some level, that his work couldn't pass it. He sued one of his employees to prevent him (the employee) from publishing a proof that Wolfram claimed he had discovered in his book. https://en.wikipedia.org/wiki/Rule_110

I understand what you're up to in trying to invent a psychology that explains his bad behavior, but at some point you have to withdraw empathy and think pragmatically about consequences. Wolfram's actions are already more than sufficient to disgrace an ordinary academic. He's damaged at least one career that we know of. He tries to pass himself off as a visionary scientist only he never delivers. If he wasn't independently wealthy no one would be listening to him at all. But non-experts do listen, which is precisely why speaking up against pseudoscience is part of every real scientist's professional responsibilities. Rather than spin these theories, it would be a better use of your time to send Stephen some email urging him to stick to working on Mathematica.


> He sued one of his employees to prevent him (the employee) from publishing a proof that Wolfram claimed he had discovered in his book.

The wikipedia article claims that Wolfram conjectured rule 110 in 1985 many years before Cook. Out of curiosity, do you have any info that disputes this?


I've read Wolfram's Wikipedia page. It doesn't contain a single word about the controversy that surrounds him and that is in evidence in this discussion thread. On the page for his book, A New Kind of Science, all the allegations of academic dishonesty, which to working scientists is probably more important than the contents of his work -- assigning credit for discoveries is how they get paid, after all -- has been compressed down to a single paragraph at the very end. And that paragraph contradicts itself on a sentence-by-sentence basis, first blaming Wolfram, then excusing him, then blaming him again and so on. So it seems that someone has been pretty successful -- more successful than not -- at erasing criticism of Wolfram from his Wikipedia presence. Therefore, I think Wikipedia's claim that he invented rule 110 in 1985 is highly suspect.

That doesn't matter much, though. Academics have a lot of ways to deal with priority disputes. Sometimes they author a paper together. Sometimes they each publish separately in the same issue of one journal. That's what happened when Darwin and Wallis simultaneously developed the theory of evolution. Sometimes, if the first discoverer was much earlier than the second, the second author might publish the work, and make a public statement in the paper saying the first author was first. This is what happened when Claude Shannon invented information theory only to learn that Norbert Wiener had done the same thing twenty years before. If Wolfram had documentation of his claim, some compromise could probably have been worked out.

Instead, it's a matter of public record that he sued Cook, alleging that the knowledge that Cook had done the work was a trade secret of Wolfram Research. I said before that scientists get paid by correctly being assigned credit for their discoveries. Suing to prevent a scientist from taking credit for their research is like armed robbery. There had been some grumbling before, but this was the moment when scientists recognized that Stephen Wolfram was Not A Real Scientist Anymore.


What if sometimes reinventing the wheel is in fact the efficient procedure and "humility" has nothing to do with it? Simultaneous discoveries and rediscoveries are something rather common. Rather than getting familiarized with some literature and, consequently, getting also tangled with the problems peculiar to how the literature has developed, maybe a fresh start from a different approach is sometimes preferable.

What specific literature are you referring to?


Yes, for example, it took Lagrange reinventing classical mechanics using the principle of least action to put physics in a spot where quantum mechanics and general relativity could be seen.


To be fair, both quantum mechanics and general relativity were first "seen" without the aid of the Lagrangian. (Not to dismiss its role in later developments.)


The name that springs to mind is https://en.wikipedia.org/wiki/Edward_Fredkin

> Everything in physics and physical reality must have a digital informational representation.


> For example, his "emulation cones" are a new name for a very old and extremely well-studied idea. The term "rulial space", similarly, is a new name for an idea that's well-developed in programming language theory.

Can you go into a little more detail about the other versions of these ideas? What are they called in other theories?



> For example, his "emulation cones" are a new name for a very old and extremely well-studied idea. The term "rulial space", similarly, is a new name for an idea that's well-developed in programming language theory.

What are the names for these old, well-studied things in programming language theory, so we can look them up?


Oy, I've been dreading having to answer this question since I pressed "post" :)

I've decided that I do not have the time or interest in writing the Related Work section for a paper-length blog post touching on an enormous number of fields, some of which I know well and some of which I haven't thought about in a decade. (As an aside, one real and substantive problem with trying to build a research program without taking the time to share a survey and comparison with related work is that you'll have difficulty communicating with others. It will then take extra effort on others' part to build up a knowledge base. Surveying and comparing to related work is hard and thankless but important work. It's not about credit, it's about building up a shared knowledge base.)

However, I can spare an hour or two and take the time to flesh out one or two in order to demonstrate what I mean.

So, I'll make the following offer: is there any particular excerpt from Stephen's blog post to which you would like the CS/PL/info theory analogue? Or, would you prefer me to pick a particular sentence and identify the body of work that explores that question and the major results of that body of work? (I will take this opportunity to emphasize the "about the non-physics side of things" portion of my original post.)

I'm going to link to this thread in other places where people have asked this question instead of monitoring 3 or 4 different threads going forward. I'll do my best to occasionally monitor this thread for requests and do my best to reply. FYI, I probably won't get around to answering more than one reply until the weekend.


Earlier you wrote 'For example, his "emulation cones" are a new name for a very old and extremely well-studied idea. The term "rulial space", similarly, is a new name for an idea that's well-developed in programming language theory.'

I don't understand how things could be extremely well studied and developed, but also not exist in some fashion where you could just name and link to it in a matter of minutes rather than hours. Example "emulation cones are called X here".

I've listened to Wolfram and skimmed one of his books before deciding he's beyond my ability to evaluate as genius or crackpot. I'd love to be able to nail down a specific thing where I could read about some existing topic and then read about Wolfram claiming to reinvent it or something, because that could help me learn towards one conclusion over the other in the genius versus crackpot consideration.

One frustrating thing that I often find is that much of Wolfram criticism is non-specific and as it's impossible for me to bucket Wolfram I can't bucket his critics either because they tend not to provide enough detail or clarity.


The question you're asking requires non-trivial effort to answer precisely because "emulation cone" and "rulial space" are never quite all the way defined, and the question being asked in terms of these definitions is also left a big vague.

Emulation cones go by various names, but perhaps the most common is the (bounded) reflexive and transitive closure of a reduction rules of a system. Another common name is the (bounded) reachable set.

Rulial spaces, by which I mean the particular ones Stephen seems interested in toward the end, are higher order term rewriting systems or higher order syntax. But actually, rulial space is used throughout the text in a much more general sense. I'd consider even very canonical results from PL theory, e.g. confluence of rewriting, to be non-trivial observations about a particular rulial space.

The reason for giving (or at least very vaguely hinting at) a definition for rulial spaces and emulation cones is to talk about foliations and then expressiveness. There's some connection between foliation and bisimulation that's difficult to exactly nail down, because nailing it down requires a lot more precision about the exact sort of (emulation cones we are interested in and for which) spaces. The connection between expressiveness and complexity hierarchies is immediately obvious, I think, right?

> One frustrating thing that I often find is that much of Wolfram criticism is non-specific and as it's impossible for me to bucket Wolfram I can't bucket his critics either because they tend not to provide enough detail or clarity.

Oy, no good deed goes unpunished :)

Look, I get why it's frustrating.

But, really, there's a reason that rule #0 of technical writing is to define terms before using them. The reader can only do so much.


I would like the PL theory analogue of "emulation cones" and "rulial space" please :)

If these concepts don't have a single name that you can just rattle off, and that we can Google - if describing them in terms of existing theory would take serious effort - then surely identifying and naming them is a major contribution?


PL theory is a bit of a hobby of mine, but I don't really see an exact equivalent to what Wolfram seems to be describing. His rules are like rules in a term rewriting system, but the rules of rulial space are permitted to change so they may be more expressive, perhaps like a higher-order rewrite system.


I'm interested in research direction of using code-data dual algothms that modify each other and form natural selection process to formally abstract notion of evolutional open-endedness (like Turing completeness is an abstraction of algorithms notion). More details: https://www.reddit.com/r/DigitalPhilosophy/comments/dzghec/o...

Maybe you could advise some developed language or model for this task? The interesting part is to have code-data duality and enough rich language to kick start natural selection that would produce competing algorithms that would gradually become more and more complex (and gradually become closer to sentience).

Though the language might not even be Truring complete as it is. As natural assumption would be that the model should be finite in resources and it can get access to infinite time or memory only in time limit (assuming that the individual algorithms would survive for this to happen).


Specifically just looking for a brief explanation of this line:

>For example, his "emulation cones" are a new name for a very old and extremely well-studied idea. The term "rulial space", similarly, is a new name for an idea that's well-developed in programming language theory.'

What's the old well-studied idea, and the well-developed programming theory idea? A one sentence reply is fine.


The idea of defining a set of transition rules and then analyzing the properties of some closure (e.g., think reflexive and transitive) of those rules. For transition rules of various orders, expressiveness, etc. And then stepping back and realizing that's what you're studying and generalizing it by thinking rigorously about the relationships between those systems and so on. That's really pretty much then entire modus operandi of a huge chunk of PL research, and there's a ton of mathematical and actual technology built up for doing so. The algorithms that are core components of Stephen's "standard library" for this project scratch the surface.


Scott Aaronson said basically this ending his review of NKS:

"However, were the book more cautious in its claims and more willing to acknowledge previous work, it would likely be easier for readers to assess what it does offer: a cellular-automaton-based perspective on existing ideas in science"


I don’t understand how this model can ever be predictive. It seems like a good way perhaps to create an approximation engine but I’m not sure what sort of predictive insights you can gain from this approach.

In order to be useful, this model should either create a new testable prediction or speed up computations in existing models while retaining accuracy. It seems to be in the latter camp. I would like to understand more about why this model is more computationally efficient.

Perhaps there’s more work to be done on the process of generating rules or limiting the types of rules. Arbitrarily choosing rules to create properties that look similar to observed physical properties doesn’t seem to point to a fundamental theory.


I think Wolfram makes the point himself that the model may not directly be predictive in the way that states "encrypt" their predecessors. I guess the best bet is to show that there is a direct connection between his model and higher models, because then you can start to look for physical manifestations of things his lower-level model predicts that don't exist in higher-level models. Kind of like how GR keeps getting reinforced by verifying its predictions with phenomena that hadn't been considered before its advent.




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