
Deep neural nets and the purpose of life - nitinpande
https://medium.com/@nitin_pande/deep-neural-nets-and-the-purpose-of-life-d3d60a38d108
======
soyiuz
> We as a unit do not matter. What matters is the emergent behaviour (the
> neural pattern) out of the collective work of everyone who is at this layer
> of the cosmic deep neural net.

This and similar statements are a species of neo-platonic monism: anti-
humanist and system-centric. It is a deeply disturbing and I would argue
reactionary thought. If we do not matter, how does one oppose injustice or
genocide? If "we are just flowing" how does one imagine the possibility of
resistance or dissent?

------
bbctol
You could replace "DNN" in this essay with... anything. Seriously, it just
says that DNNs "can act as both machine and storage," which is true of any
system if you want to define it that way. And pointing out that everything in
the universe is one system is just the beginning of physics. DNNs are
_superficially_ inspired by _parts_ of the brain, but there's nothing magical
about them.

~~~
nitinpande
Fair points. Would love to hear the other 'anythings' that can replace DNNs
(something that optimises and stores knowledge that can be passed down
generations to further build more sophisticated systems).

I thought DNNs are a good framework to contemplate the reason as well as
mechanics of our existence. And using the framework I came to the thought that
we probably do not have any grand purpose.

Also, I think saying that the universe is a DNN system is different from
saying that it is 'a system'.

Agree DNNs are not magical for someone who has been working on them forever
but for a new entry into the ML field, believe me they are pretty magical :)

~~~
bbctol
I might just not be sure what you mean by DNN here. A deep neural network is a
specific architecture, consisting of input and output layers of discrete
nodes, connected through many hidden layers of nodes, with each node able to
perform simple operations on the signals passing through it. So I don't see
any way you could model the universe or a seed as a literal DNN; I interpreted
the main reason for the analogy that they're a system in which storing
knowledge (in an NN, as the weights of activation) is an intrinsic part of the
way the system is active.

From there, you really can interpret most things as systems with embedded
knowledge that both defines their activity and is adjusted by new activity.
The position of each atom in an object is intrinsically both the information
about that object, and the way that it behaves: as changes are made, the atoms
react accordingly, affecting the behavior of the system.

You can view a seed as a "trained model" only insofar as the information on
how to become a tree is encoded in the seed. The specific properties of DNNs
(hidden layers that increase in abstraction) aren't really present, and
anything can encode information: a set of clouds could be considered a trained
model on how to make a hurricane, or a single person could be viewed as
containing a trained model on how to start a company. Seeds are highly
optimized through evolutionary pressure, but that applies to all complex
systems, not just DNNs, and optimization is not just non-unique to DNNs but
not even necessarily present in the architecture.

