
Deep Molecular Programming - groar
https://arxiv.org/abs/2003.13720
======
cs702
A warning shot.

I'm bracing for what I think will be rapid acceleration in joint organic-
machine experimentation going forward.

Over the next decade, I surmise it's likely we will see everything ranging
from constructing and training large-scale organic/molecular deep neural
networks with stochastic gradient descent (which is what these guys have done
at a small scale) to integrating artificial networks with organic ones (which
is what startups like Neuralink are doing) to who knows what else.

We live in interesting times.

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zingermc
This paper mentions CRN++, a compiler that translates an imperative language
into Chemical Reaction Networks. I had no idea this field existed. This stuff
is mind bogglingly cool!

[https://arxiv.org/abs/1809.07430](https://arxiv.org/abs/1809.07430)

~~~
amelius
I skimmed the paper but I still wonder how a (practical) memory would be
implemented, and how many bits it could contain.

I think these computations all happen in a "soup", and this means that the
memory can only exist as a superposition of concentrations, which I suppose
has its limits.

~~~
akimball
Nucleic acids store bits pretty well.

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fsloth
Programmable matter. Now we are getting closer to the future we were promised.

~~~
youareostriches
Well, what do you think life is? It’s a product of chemical computation.

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aledalgrande
Until when do I have to wait for an Organic Raspberry Pi to play with?

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canjobear
How can a binary-valued network be differentiable?

~~~
GregarianChild
The loss function needs to be differentiable. The paper uses _square hinge
loss_ which is differentiable.

~~~
canjobear
Thanks, and for those who are wondering how squared hinge loss is
differentiable, I found:

[https://www.quora.com/Why-is-squared-hinge-loss-
differentiab...](https://www.quora.com/Why-is-squared-hinge-loss-
differentiable)

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_ZeD_
future virus and worms will be scary...

