Hi, I did some stuff, worth showing:

a) Set up a gemini server
(using GCP free tier)

b) Set up a smart phone free of
Google and Apple services.

Read about the phone in my new gemlog on gemini://join.thejoyri.de 😀

Today I set up a new GAFAM free mobile phone using /e/OS and I am very pleased with the result.

Hi, in case you already discovered the small web - find me here:

gemini://join.thejoyri.de/

If you don't know how to get there, here is some info:
en.wikipedia.org/wiki/Gemini_s

Understanding :

Probably a good question ...
What is the correct of (directed) dependencies between mathematical , physical and agential and ?

I remember that it was quite hard to build up a meaningful network on Twitter, so maybe I am just too impatient. But currently I do not see how to discover other users with a specific set of interests, without being able to their content.

I understand that global search and indexing is intentionally kept in check for multiple reasons. Are there any (less comfortable) ways, like external search or whatever to discover stuff outside the local server or the people directly connected?

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How can I discover people in the fediverse interested in niche science content on certain topics, e.g. in the area of ?

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Is there a way to whitelist languages and/or hashtags to get a more customised selection of others’ content?

So this is the chicken egg problem for Mastodon for long tail topics. Obvious stuff like open source works well, but specialized science topics are hard. But I understand that it is an intentional design decision that saves people from the mob and from trolls.

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Mastodon does not offer federated full text search on what people posted, right? Compared to Twitter that makes it much harder to find people on niche topics.

A good background text on algorithmic information theory can be found here:

scholarpedia.org/article/Algor

The key idea is that complexity can be best captured by the length of the most concise description of the regularities of a thing.

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To understand, what Krakauer means with “regularised randomness” and “frozen accidents”, read

WHAT IS COMPLEXITY?

by Murray Gell-Mann, 1995

complexity.martinsewell.com/Ge

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This is the basic mechanism to for complexity to unfold: adversarial arms race.

How parasites expand the computational landscape of life

by Luís Seoane and Ricard Solé

arxiv.org/abs/1910.14339

"host-parasite co-evolution can ignite an explosive race of increasing complexity ..."

How Turing parasites expand the computational landscape of digital life

Why are living systems complex? Why does the biosphere contain living beings with complexity features beyond those of the simplest replicators? What kind of evolutionary pressures result in more complex life forms? These are key questions that pervade the problem of how complexity arises in evolution. One particular way of tackling this is grounded in an algorithmic description of life: living organisms can be seen as systems that extract and process information from their surroundings in order to reduce uncertainty. Here we take this computational approach using a simple bit string model of coevolving agents and their parasites. While agents try to predict their worlds, parasites do the same with their hosts. The result of this process is that, in order to escape their parasites, the host agents expand their computational complexity despite the cost of maintaining it. This, in turn, is followed by increasingly complex parasitic counterparts. Such arms races display several qualitative phases, from monotonous to punctuated evolution or even ecological collapse. Our minimal model illustrates the relevance of parasites in providing an active mechanism for expanding living complexity beyond simple replicators, suggesting that parasitic agents are likely to be a major evolutionary driver for biological complexity.

arxiv.org
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