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Comment by jfk13 | Hacker News Reader

I wonder. A quick google suggests that a typical cell might contain 10^14 atoms, and that the number of transistors in a current supercomputer is of a similar order of magnitude. Is the cell really "more complicated" than the supercomputer? The nature of the complexity is so different that I'm not sure the comparison is all that meaningful.

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> Is the cell really "more complicated" than the supercomputer?

Let us ask a different question that may suggest a possible answer.

How many different dynamic manufacturing processes occur inside a supercomputer as compared to the number of different manufacturing, transportation and communication processes that control those manufacturing and transportation processes occurring within any single living biological cell?

Cells have a rather limited set of manufacturing processes.

Mycoplasma mycoides only has 525 genes and we can cut tha down to 473 and end up with something that self replicates. https://www.nationalgeographic.com/science/phenomena/2016/04.... (I find it amusing how breathless they talk about the fact their where some unknowns in that list rather amusing.)

Let me ask some more questions and see what insights we can obtain from them.

Within each manufacturing process, how many different kinds of steps are there and how "complicated" is each step (the required processing that is required to do that step)?

What kind of dynamic manufacturing infrastructures are created and then taken down within the cell for each of these processes?

That’s an ambiguous question. If you want to accurately simulate matter, the larger the block of matter the more processing power it takes. We think of DNA as more complex than a crystalline structure becase crystals have more order, but that’s abstracting away a lot of the details. Which means manufacturing a super computer is vastly more complex in terms of matter.

In some ways we better understand how super computers are made, but we can also far more easily replicate cells than a supercomputer. So, again supper computers are more complex.

In terms of the minimum amount of information to turn raw matter into a simple cell, again super computers take more information.

I suspect you want some sort of third definion where cells are more complex, but that’s more begging the question than how things actually are.

When you get the chance have a listen to some of the discussions about organic chemical processes occurring in cells by Dr James Tour. From an engineering and manufacturing point of view, the processes that occur in a cell are far beyond what we are able to achieve in any of our engineering and manufacturing processes.

It is not about simulating processes, it is about doing those processes.

We can manufacture DNA from 'scratch'. That means as long as we have the sequence we can largely use those same processes. Sure, we don't necessarily understand what's going on, but neither did our ancestors you first manufactured steel etc etc.

Protean folding is very complex to simulate. But, so is even a hydrogen atom starting from quantum mechanic equations. Saying we can abstract away that hydrogen atom does not mean the complexity disappears. Further from a QM standpoint protean folding is really slow, it's a complex dance like plate tectonics even if it's blindingly fast from our viewpoint.

By nature, we understand the "what' and "why' of each supercomputer component, as they have been built by us from the bottom up. We are orders of magnitude from understanding each component of the cell. When you get into the weeds, the methods used to dissect these processes are generally slow, indirectly and subject to relatively subjective interpretation and poor reproducablility (vs chemistry or physics). Don't get me wrong, I love this stuff and was drawn to a molecular biology career by curiosity around the wide grey line that separates what is living and what is a bag of molecules, but having spend many years at the bench still think that the Biology part of Synthetic Biology will be the bottleneck rather than the bioinformatics/synthetic methods, tho improvements in this stuff will greatly help.

Exactly. Look at the computational power we have thrown into figuring out just how a protein folds for example. I worked in a lab where we used a lot of inference in the 2D structure of RNA over a decade ago after the 23s and 16s ribosomes tertiary structures were resolved. I was simply working with 70-120 base-pair tRNAs and that alone was computationally complex using a known model to compare against! We have still but scratched the surface.

Building a core cell always intrigued me as an undergraduate and I was often interested in the bare minimum (DNA-wise) lab manufactured bacterial strains that were used in experiments.

How many types of atoms are there vs types of transistors? How many combinations and permutations can the atoms rearrange themselves into vs transistors? How many other atoms can an atom interact with in a given time period vs transistors? How dynamic is the state of a cell vs a supercomputer, and how diverse are the state changes?

I don't know the answers to any of these but I think that a comparison of complexity should take more than one metric into account

I'm working (as a consultant) for a company that does state-of-the-art chip design. The complexity is mind-boggling. The number of different types of core components isn't very high; at root it's all transistors and (nominally) rectangular pieces of metal. But these simple building blocks interact with each other in ridiculously complicated ways. Just processing the files that contain the timing information for the current generation of chip fabrication technology takes over an hour on a fully-tricked-out server. Checking a design to see if it meets a timing spec takes many hours using dozens of servers. And then you have to deal with power, thermal constraints, geometric design rule checks (the list of rules you have to follow is a PDF document hundreds of pages long), clock distribution... Frankly, it amazes me that state-of-the-art chips work at all.

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