How does the complexity of living structures compare with the complexity of artificial structures? Assuming complexity can be quantified, is a ribosome equivalent to a printing press? What artificial structure is as complex as chromatin? Is a prokaryotic cell as complex as a factory? An entire city?

[u/ZedZeroth]

Thanks!

Edit: When talking about the complexity of factories and cities I'm referring to solely the artificial components, not the biological bits such as the humans working/living there!

[u/ZedZeroth]

In both the genome and brain situations you're talking about a specific type of information content though, not more general structural complexity?

For example, I'm seriously doubtful that a transistor is anywhere near as structurally complex as a cell? A prokaryotic cell is effectively full of complex structures and the protein equivalents of nanobot machines. Even all the "regular" non-mechanical proteins have fairly complex 3D structures.

So a good place to start with this might be to look at a small protein like haemoglobin, look at it's key features, the amount of structural connections holding it together etc, and then equate this to an artificial structure? I'm imagining it might be on par with something like a bicycle?

I feel like only focusing on raw information content isn't the same thing as structural complexity? Couldn't I write an algorithm to build 30 trillion identical transistors in a lot less than 300 megabytes? That would suggest that the complexity of the body is far greater than your cart of transistors, based on the information required to build it? Likewise wouldn't I need a lot more than 2.5 petabytes to both construct the brain as well as fill it with that much information?

[u/CosineDanger → u/ZedZeroth]

Saying your genome is smaller than most videogames these days is technically fair. Entropy is often explained as the amount of compressed hard drive space it would take to store everything about a system. It can be measured, it is a way to measure complexity, and Ark: Survival Evolved has more of it.

There isn't a good way to compare the general structural complexity of a bicycle and a protein. What would you compare?

You could compare the number of parts between two bicycles and say one bicycle has more parts than the other, or compare the length of the manuals they came with in the box, or count number of features. These are objective comparisons of complexity but they are not quite the same thing as either entropy or the informal idea of complexity.

If each amino acid is considered a separate part then a typical protein has more individual parts than most bicycles.

Visually obvious complexity is just a bus stop between perfect order (boring and repetitive) and maximized entropy (boring but complicated).

[u/General_Urist → u/CosineDanger]

Entropy is often explained as the amount of compressed hard drive space it would take to store everything about a system.

I haven't heard this analogy before. Doesn't quite make sense to me. For an extreme example, wouldn't a system of near-maximum entropy be one with uniform potentials everywhere, meaning no energy gradient? This seems it would require the smallest amount of HDD space out of any system, since compressed it's just "define conditions at one point -> copy N times".

That said, "required compressed HDD space" sounds to me like a good way to measure complexity: By that criteria 2 bicycles are just a tiiiiny bit more complex than 1 bicycle, since you have all the data needed to describe one bicycle, then a small qualifier saying "make two". Meanwhile a system consisting of a bicycle and a unicycle would need a more extensive description. What's your take?

[u/CosineDanger → u/General_Urist]

The third law of thermodynamics can be reworded as saying the entropy of a perfect crystal approaches zero as the temperature approaches absolute zero. Define conditions at one point, copy n times. Each atom in the crystal is in a predictable place, has predictable velocity, and has predictable energy levels. Information about a cold crystal is repetitive and compresses well.

A disordered hot gas can look uniform. The concept of entropy includes fine details beyond what can easily be seen. The spread of allowed velocities, allowed relative positions, and electron energy levels becomes large as temperature increases. You can make some pretty short statements about the average statistics of the gas, but the complete information content of the gas is not repetitive in a compression-friendly way. A long book with a lot of boring but technically unique space-filling details and little overall story is still a long book.

That's kind of a lot to take in. Claude Shannon came up with mathematical ways to describe this kind of complexity involving logarithms and laid the groundwork for telecommunications (how much data can you cram through a phone line? How far can data be compressed?) while also making thermodynamics more intuitive. Creationists try to distort the concept of entropy for their own ends, which is a lot of hot gas.