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Comment by aj7 | Hacker News Reader

I’ve had more downvotes sharing my opinions about cellular automata on HN than on any other topic, so I won’t make any here. Rather, I’d like to point out that I personally have not seen a single theory, not a single piece of a theory, known to be productive in explaining experimental data, recast with underlying cellular automata theory. If I am simply showing my ignorance, please enlighten me. Meanwhile, the clock is ticking.

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I think it's a good thing to have a small percentage of scientists working on whacky theories, one of them might turn out to be true.

Plus it's not like Wolfram is taking resources away from other scientists as he is funded from his company. If Wolfram wasn't doing this he'd be CEO'ing his company, there's no cost to the public for Wolfram exploring this and potentially huge gains - though unlikely.

There could be an opportunity costs, researchers working on this could be working on a different problem. Unlikely, but not impossible.

I'm fairly sure Wolfram's researchers are working on it because they are interested, and want to do it.

Money is not the only resource. Scientist time is another resource, and probably a lot more important when it comes to Physics. Any private venture such as this necessarily (a) takes up scientist time, (b) provides training to scientists that can be applied to other problems later on, (c) as a second order effect, molds the public's perception of science in a certain way.

(a), (b) or (c) could individually be positive or negative to society. And their net could be positive or negative.

I don't know what these values are for Wolfram's work, but we can definitely make this sort of nuanced analysis.

There’s no such thing as a limited supply of scientists, whose precious time is to be carefully allocated. For all I know, Wolfram might be creating new scientists from people who otherwise might not choose to pursue corrupt academia route.

He is taking resources by not properly attributing work, actually. One of the big criticisms of NKS was the lack of a real bibliography and there was the whole Wolfram v. Cook debacle on top. As I recall, the book still doesn't credit cook for the proof.

That was true about the Wolfram Physics Project. But now, the Wolfram Institute will compete for research funding, as he explains in the blog post. In fact, this is the whole point of creating the Institute: WPP couldn't scale up as it was eating too much of his own money, and he believes he needs to scale this up to actually bring the work to fruition.

> So far we’ve basically been incubating the Wolfram Institute within our existing organization, with me effectively footing the bill. But as we launch the full Wolfram Institute we need a larger scale of support, and we’re counting on having a network of people and organizations to provide that.

mRNA reporting for duty

Kirov reporting

Scientists, yes.

Note that at various times, Feynman and Ed Fredkin became enchanted with cellular automata. We’ve had some significant tries apart from Wolfram.

We should also note when high credibility scientists work on something for a while and then drop it altogether.

Hey, I do really weird math for unspecified reasons.

https://pdfs.semanticscholar.org/28da/6507acf40f892b95ee61a7...

Cellular Automata are, in essence, a type of mathematical function called a “Chaos Map”, aside from the cool name it’s also a WYSIWYG name, a chaos map is a mapping of how a fractal expands or changes across space time.

A great example very germane to this site is the Hacker Glider from Conway’s game of life. https://en.m.wikipedia.org/wiki/Glider_(Conway%27s_Life) The Glider is a pattern which we can observe within the game, and we can see that it represents a function related to the overall chaotic map of the game itself. In English, Doc! All the patterns the game can make are the chaos map. Studying the individual patterns shows both how they are created and interact with other patterns. Here’s an overlapping example: https://www.sciencedaily.com/releases/2020/03/200318143635.h...

Within the Chaotic map of slime mold evolution, it’s the loner pattern which informs the other parts of the map.

Let’s bring it all together now. By studying cellular automata, we can observe patterns which correspond to a chaotic map of those patterns. By looking at that, we are able to make deeper inferences about the overall total pattern by knowing that what we observe in a small scale will also exist at n+1 scale. Meaning, when we see the loner slime mold evolve the other parts, it’s reasonable to infer through scale that loner humans may also contribute evolutionary information. We can test that theory, and then either continue to investigate from a positive or negative delta.

The benefit of learning about and using CA isn’t that it’s abstract but rather it creates meaning from the raw chaos of life which we deal with every day.

Practically it can lead to better encryption like I linked above, superior understanding and prediction of weather, and for those who are able to view the patterns of the small as a whole: it can reveal truths which I would call mathematically spiritual.

Thanks for reading I hope I changed your mind!

>a chaos map is a mapping of how a fractal expands or changes across space time.

My jaw actually dropped in real life when I read this line. It fits so well. Thank you so much for this explanation.

From your first link:

> The digital images can be converted to binary data and encrypted with Advanced Encryption Standard (AES). However, the high correlation between adjacent pixels may still be kept after encrypting a digital image without considering the property of digital images.

What do you mean by this? It sounds like it’s suggesting that, e.g., the AES-CBC ciphertext of an image has detectable internal correlations. In other words, AES is completely broken as a cipher. Surely I’m misinterpreting the claim here.

I guess they’re referring to AES-ECB, which is notoriously weak at encrypting images (it’s weak in general of course, just most obviously with respect to images): https://words.filippo.io/the-ecb-penguin/.

But I don’t think the same is true of the other AES cipher modes.

Yeah, this paper is a good representation of the whole "chaos cryptography" theme — snake oil cryptography invented by authors who don't even attempt to study cryptography before producing their bullshit and publishing it in sketchy or generalist, unrelated to cryptography, journals.

In this particular paper:

1. The motivation for "image encryption" is completely wrong, as you pointed out.

2. There is no secret key. The "key" is produced by hashing the image with SHA-256.

3. Claim: "No any useful information can be acquired from encrypted images". Actually: since this is convergent encryption (https://en.wikipedia.org/wiki/Convergent_encryption, "key" derived from SHA-256 of data), encrypting any two equal images will produce the same ciphertext, globally.

4. Finally, the actual "key" can't be more than 64 bits, since SHA-256(image) is then split into two groups of 32-bit words, which are xored together to produce two key values. Thus, this whole "encryption" scheme is limited to 64-bit security (probably even less than that). We don't even have to analyze the whole "chaos" system they invented to conclude that it's insecure.

> Practically it can lead to better encryption like I linked above, superior understanding and prediction of weather

This is the problem. Maybe it will, but as of yet nobody has figured out a practical application beyond "helping us appreciate nature" (replace nature with any chaotic system).

We are pretty good with weather prediction and getting better all the time. The fundamental problem is the chaotic nature. CA does practically help us in anyway there.

Fractals on the other hand has so many practical applications. Just the other day I was applying factual theory to the prediction of criminal activity.

Maybe all CA needs to do is help us appreciate nature and simple machines.

> This is the problem. Maybe it will, but as of yet nobody has figured out a practical application beyond "helping us appreciate nature" (replace nature with any chaotic system).

Why is this a problem? Doing maths purely for its own sake is as valid and useful as painting a picture, or cooking a delicious meal instead of just eating dry bread.

If that's not good enough for you, there are plenty of examples of maths that was considered useless at the time but ended up finding a use years, decades, or centuries later.

> Why is this a problem? Doing maths purely for its own sake is as valid and useful as painting a picture, or cooking a delicious meal instead of just eating dry bread.

Nothing is wrong with this at all. I never wrote nor even implied there was anything wrong with this.

If you had read to the end of my comment you would have seen I wrote:

> Maybe all CA needs to do is help us appreciate nature and simple machines.

So looks like we are in agreement in appreciating the beauty of maths.

It's a problem when someone is claiming that a technique Solves the Big Problems when it clearly doesn't.

Maybe it will one day, and no one is saying it's not an interesting avenue to explore.

But making grandiose claims is not doing science. Making novel falsifiable concrete predictions is science, and Wolfram hasn't made enough of those to justify the extreme self-regard.

I strongly agree with the spirit of what you're saying, but:

> making grandiose claims is not doing science. Making novel falsifiable concrete predictions is science

It seems to me that making grandiose claims is absolutely essential to science every now and then. A good example is when Einstein made the grandiose (and unfalsifiable) claim that the mathematical theory of relativity already worked out by Lorentz and Poincare and whoever was best seen as the denial of the existence of simultaneity etc., a claim which obviously turned out to be very fruitful since it lead to General Relativity.

However (and this is one reason I so strongly argee with the spirit of what you're saying), (a) there isn't room for very much of this stuff, (b) Einstein was much better at it than Wolfram is, and (c) Einstein was listened to because at the same time (ha ha) as he was making grandiose claims he was making unarguably gobsmacking breakthroughs in atomic theory and quantum mechanics.

I think it is fair to assert that if maybe one day it will solve big problems, that it should have solved a little problem already.

Quantum mechanics rapidly gained credibility because once its formalism became established, it was easy to show how classical mechanics came out of it in a limit.

> Why is this a problem? Doing maths purely for its own sake is as valid and useful as painting a picture, or cooking a delicious meal instead of just eating dry bread.

It's a problem because Wolfram named his book A New Kind of Science, not A New Kind of Doing Maths Purely for Its Own Sake.

If Wolfram just went around saying "hey, cellular automata are fun and interesting for their own sake` he wouldn't get the hate he does.

You are certainly right. But what I was referring to was CA being linked to physics, but without any tangible link.

So then is it less of a proof mechanism and more of a simulation one?

> "Let’s bring it all together now. By studying cellular automata, we can observe patterns which correspond to a chaotic map of those patterns. By looking at that, we are able to make deeper inferences about the overall total pattern by knowing that what we observe in a small scale will also exist at n+1 scale."

Okay, this follows themes of fractal self-similarity, very interesting stuff. However, the next leap sounds completely unsupported. One reason is that physics often doesn't scale like this (see gravity and why we don't have elephant-sized ants):

> "Meaning, when we see the loner slime mold evolve the other parts, it’s reasonable to infer through scale that loner humans may also contribute evolutionary information."

The cellular automata stuff sounds valid mathematically, though I'm no expert, but the leap to other areas of science? Even the jump to slime mold evolution... I mean, where is the valuable addition? Slime mold evolution doesn't seem to require any cellular automata theory to understand. It's an interesting biological system that has aspects of both independent microbial cellular life as well as multicellular cooperation under stress conditions.

Plus the tedious self-promotion, I've know academics like that, the type who march into every room tooting their own horn and banging their drum. Working for people like that is a big mistake for many reasons. For example, if your results disagree with theirs they'll go overboard trying to sabotage you. Your only possible roles in that situation will be those of loyal sycophant, or, if you don't follow along, excommunicated heretic.

I work on weather prediction, both with traditional simulation methods and machine learning. I have not seen any examples of cellular automata used for useful predictions in this space.

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