* The idea is that you can make an AGI out of a network of humans. The individual humans within the network needn't know how they are contributing to the overall intelligence of the AGI.

* The communication between neighboring humans in the network can happen via sending emails, over hand help radios, yelling or even dockerized containers. The optimization algorithm determines to whom these messages are sent and with what "weight".

* The inputs and outputs need not be trivial, they can be arbitrarily complex, such as numbers, theorems, songs or questions being posed and answered. These inputs and outputs need only be "differentiable" either numerically or even in a "fuzzy" sense in order to allow the communication to be optimized.

* An example could be a neural net of mathematicians who together produce a better mathematician who is able to solve a problem no one single mathematician within the network is able to solve. This neural net of mathematicians could be better than a group of mathematicians discussing amongst themselves. In a group discussion, human dynamics come into play, where one of the mathematicians becomes the leader and needs to act as a centralized consolidator and arbiter of information. Whereas in the neural net the algorithm/weights determines how the mathematicians communicate with each other.

[1] https://news.ycombinator.com/item?id=27738029

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