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Does DNA have the equivalent of IF-statements, WHILE loops, or function calls?

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Re: Does DNA have the equivalent of IF-statements, WHILE loops, or function calls?

#41

Post by gumballindie »

fasterik wrote: post #39
Garlef wrote: post #26

Earlier quoted context omitted.

Before anyone jumps to esoteric conclusions: This is more likely a result of neural networks being very general: General in the sense that they are able to approximate/model a lot of dynamic systems that allow operadic composition.

It's still an interesting fact that evolution seems to have figured out that neural networks are good at approximating arbitrary continuous functions. We could ask whether intelligent alien species are likely to use neural nets. In other words, are neural nets universal in some sense, or are they contingent to how life evolved on Earth?

Yes it was nature that figured out ai neural nets are efficient not humans implementing algorithms that found out that nature makes efficient use of neural nets. Aliens will first have to make contant and dully learn how to use neural nets to develop intelligence. A catch 22.

Re: Does DNA have the equivalent of IF-statements, WHILE loops, or function calls?

#42

Post by yieldcrv »

dawnofdusk wrote: post #3

An interesting question because all of this genetic encoding and expression is probabilistic at its very core (it has to be, otherwise there wouldn't be evolution), whereas it would be very bad if basic operations in a CPU had similar level of error rates. Interesting to me how the top comment has talked about constructing logic gates out of biological circuits. I wonder if anyone has done the opposite, i.e., write a…

LLMs add just enough entropy

Re: Does DNA have the equivalent of IF-statements, WHILE loops, or function calls?

#43

Post by fasterik »

gumballindie wrote: post #41
fasterik wrote: post #39

Earlier quoted context omitted.

It's still an interesting fact that evolution seems to have figured out that neural networks are good at approximating arbitrary continuous functions. We could ask whether intelligent alien species are likely to use neural nets. In other words, are neural nets universal in some sense, or are they contingent to how life evolved on Earth?

Yes it was nature that figured out ai neural nets are efficient not humans implementing algorithms that found out that nature makes efficient use of neural nets. Aliens will first have to make contant and dully learn how to use neural nets to develop intelligence. A catch 22.

What I mean by aliens using neural nets is that we don't know what percent of evolved intelligent species would have neural nets as an integral part of their cognition like we do. And we don't know what alternative paths there are to the evolution of intelligence.

Re: Does DNA have the equivalent of IF-statements, WHILE loops, or function calls?

#44

Post by pyinstallwoes »

akira2501 wrote: post #2

My favorite thing about mtDNA is that two separate genes overlap using separate reading frames. The end of one gene is the same as the start of another, and they are laid out in the circular mitochondrial genome to take advantage of this fact. I've also read that DNA chromosomes can under go conformal changes in response to the environment it's in, making certain reading frames more or less likely to be transcribed,…

That reminds me of how the Vedas Sanskrit flows and also forms error-correction from verse to verse.

The beginning is the end is the beginning.

Re: Does DNA have the equivalent of IF-statements, WHILE loops, or function calls?

#45

Post by Karellen »

dawnofdusk wrote: post #3

An interesting question because all of this genetic encoding and expression is probabilistic at its very core (it has to be, otherwise there wouldn't be evolution), whereas it would be very bad if basic operations in a CPU had similar level of error rates. Interesting to me how the top comment has talked about constructing logic gates out of biological circuits. I wonder if anyone has done the opposite, i.e., write a…

> it would be very bad if basic operations in a CPU had similar level of error rates.

Given how slow evolution is, and how many times DNA is copied and/or transcribed in any one individual, my intuition is that the error rates for genetic processes are actually incredibly low.

Re: Does DNA have the equivalent of IF-statements, WHILE loops, or function calls?

#46

Post by dawnofdusk »

Daub wrote: post #5
dawnofdusk wrote: post #3

An interesting question because all of this genetic encoding and expression is probabilistic at its very core (it has to be, otherwise there wouldn't be evolution), whereas it would be very bad if basic operations in a CPU had similar level of error rates. Interesting to me how the top comment has talked about constructing logic gates out of biological circuits. I wonder if anyone has done the opposite, i.e., write a…

> under the same amount of noise as a cell? Can you share what you mean by this?

I just mean that cells in an organism experience much higher noise rates than a CPU, but we still consider them as capable of sophisticated computations. It's hard to peg a number at exactly how much more, but at least for reference many bacteria have a gene transcriptional error rate of like 10^-4. Apparently fiber optic engineers target 10^-12 error rate, and I assume the error rate of transferring data between CPU registers is even lower. So it's probably a decent estimate to think that biological "computations" occur under at least a million times more noise than a computer.

Re: Does DNA have the equivalent of IF-statements, WHILE loops, or function calls?

#47

Post by dawnofdusk »

nihzm wrote: post #27
dawnofdusk wrote: post #3

An interesting question because all of this genetic encoding and expression is probabilistic at its very core (it has to be, otherwise there wouldn't be evolution), whereas it would be very bad if basic operations in a CPU had similar level of error rates. Interesting to me how the top comment has talked about constructing logic gates out of biological circuits. I wonder if anyone has done the opposite, i.e., write a…

> probabilistic programming language whose operations are under the same amount of noise as a cell The reason for the probabilistic nature is that biological "computations" are eletrochemical reactions and feedback loops, which do not map very well to the concept of "executing code" as in programming languages. I think a closer analogy could be a hardware description language that sythesizes analog circuits for compu…

Analog computing is trendy again, though, especially for AI.

Re: Does DNA have the equivalent of IF-statements, WHILE loops, or function calls?

#48

Post by Alpha3031 »

Carroll is probably one of the better known researchers focusing on the evolution of cis-regulatory elements, non-coding sequences which regulate the expression of nearby genes. I would consider his 2005 book Endless Forms Most Beautiful to be a reasonable introduction. For something more less pop-sci I understand Davidson and Peter's (2015) Genomic Control Process has been fairly well received, as well. Though both are on the older side of things now, and admittedly I'm not too familiar with the current literature, they would probably be my recommendations. There are also non-gene regulatory elements of course.

Re: Does DNA have the equivalent of IF-statements, WHILE loops, or function calls?

#49

Post by guyomes »

fasterik wrote: post #39
Garlef wrote: post #26

Earlier quoted context omitted.

Before anyone jumps to esoteric conclusions: This is more likely a result of neural networks being very general: General in the sense that they are able to approximate/model a lot of dynamic systems that allow operadic composition.

It's still an interesting fact that evolution seems to have figured out that neural networks are good at approximating arbitrary continuous functions. We could ask whether intelligent alien species are likely to use neural nets. In other words, are neural nets universal in some sense, or are they contingent to how life evolved on Earth?

From what I understand, Gene Regulatory Network [1] works very differently from Biological Neural Circuits [2]. Finally, Perceptron used in computers [3] is based on arithmetic operations and is again different from any of those two biological mechanisms. However, perceptron appears to be a good tool to model functions that depends on a large number of parameters.

What we may infer from that is that after a lot of time of evolution, functions depending on a lot of parameters appear. Yet Biological Neural Circuits seem quite bad at approximating simple continuous functions such as the multiplication between two numbers.

Gene Neural Network and Biological Neural Circuit are quite impressive structures considering their size, materials, and energy constraints. However if you allow bigger size, more energy, and faster conducting materials, it should be possible to do have faster modeling tools.

Moreover, to better take into account non-linear functions, my two cents is that Perceptrons could be further enhanced using piecewise polynomial functions instead of piecewise linear functions [4,5].

[1]: https://en.wikipedia.org/wiki/Gene_regulatory_network

[2]: https://en.wikipedia.org/wiki/Neural_circuit

[3]: https://en.wikipedia.org/wiki/Perceptron

[4]: https://doi.org/10.1109/TPAMI.2021.3058891

[5]: https://doi.org/10.1109/TPAMI.2022.3231971

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