Hacker News Reader

Comment by VectorLock | Hacker News Reader

People joked a lot about "injectible source code / machine code" but it is kind of interesting injecting yourself with something that has the source on github.

View on HN

Note that this is a sequencing result, so it will lack a lot of nonstandard RNA tricks that these companies are or might be using, like pseudouridines, or fluorobases. I think those would have to be disclosed in the patent.

Less like original source code, more like a clean room reverse engineering.

We aren’t that different from machines, we just need to know more about the CPU and all the co-processors and how the logic gates interact

But for now we can inject code to trigger protein configuration via the immune system

Does that mean a cytokine storm is the equivalent of a buffer overflow or a DoS?

IDS with ability to launch countermeasures, and no negative feedback loop

A cytokine storm is when you trick the antivirus into thinking all major system files contain a virus.

Cytokine storm would perhaps be like the user deleting random necessary OS executables in an attempt to get rid of malware

> We aren’t that different from machines, we just need to know more about the CPU and all the co-processors and how the logic gates interact

Except it is unfortunately not that simple, because it assumes that distinct components such as CPU, co-processors and even logic gates exist in that context, as is totally reasonable to assume on devices created by humans. Abstracting complex machines into distinct components is a proven strategy to engineer a system, but it's not a necessity for functioning systems to exist.

In the case of natural organism, they "just" need to work. They don't have a blueprint, and they don't need to be organized in a way that allows for easy understanding by looking at individual parts in separation.

Consider also the difference between machine learning through neural networks ("we stuff a lot of training data in there and get what we want eventually, we hardly understand what the model does or why it fails"), and a QR code reader ("we carefully designed the format from the top down, including e.g. framing, error correction, and several invariants like rotation; if a QR code does not get recognized, we can usually tell exactly where and why it failed").

It is actually sort of strange how compartmentalized the living cell is.

I guess there is some type of redundancy that comes from compartmentalization that is evolutionarily beneficial.

No doubt, and separate organs with (sometimes rough, sometimes very clear) separate functions are also a thing, so evolution seems to favor compartmentalization for more complex systems. But that does not mean that there are not complex overarching interactions that make full understanding really hard. The sort of interactions you would stay away from when designing a computer, not because it would not work, but because it would make design, debugging, and iteration upon your system prohibitively hard.

There is a theory "endosymbiotic hypothesis" that mitochondria were wholesale absorbed bacteria into our DNA line. Which I think is pretty wild, and explains how neatly they're compartmentalized.

“Imagine a being like nature, wasteful beyond measure, indifferent beyond measure, without mercy and justice, fertile and desolate and uncertain at the same time; imagine indifference itself as a power, how could you live according to this indifference?"

I am not able to draw the distinction you are trying to make. The more we make machines, especially ones to interact with inputs from our world, the more easy it is to understand our bodies.

Correct, because there is no blueprint then we don't know about how the brains and neurons interact. But if there is a problem with a heart valve we know exactly where and why it failed.

I expect greater convergence in these fields, and as such I can't agree with you.

> But if there is a problem with a heart valve we know exactly where and why it failed.

I highly doubt that. Even for heart valves, which seem less complicated than plenty of other body parts (at first glance, I'm sure they are plenty complicated in detail), because they are comparatively mechanical. For example, Wikipedia says (with citation): "Causes of aortic insufficiency in the majority of cases are unknown, or idiopathic."

Try a kidney or something related to the nervous system next.

> The more we make machines, especially ones to interact with inputs from our world, the more easy it is to understand our bodies.

FWIW I am making machines, and the more I do, the more amazed I am about how intensely complicated our body in general and our nervous system specifically is.

Just because you see the RNA/DNA sequence on Github doesn't mean anything, DNA sequencing has been around since at least the early 70s [0]. Many pharmaceutical drugs already employ such techniques.

[0] https://en.wikipedia.org/wiki/DNA_sequencing#History

Reply on news.ycombinator.com