for - example - importance of multiscale hierarchical intelligence and control - Michael Levin - high level instruction is issued and the multiscale structure ensures that all the lower level details are executed - like a software function call

new plexmark - person assigned to each comment in multiplayer conversational environment - have a way to - detect then - discriminate and finally - tag - each sequentially different conversant' s comments in the conversation - This will help with Indyweb provenance by attributing the person with each sentence

for - quote - consciousness vs cellular level intelligence - Michael Levin - key insight - high level governance (consciousness) vs low level intelligence adjacency hierarchical control - high level consciousness - low level micro intelligence quote - consciousness vs cellular level intelligence - Michael Levin - all intelligence is collective intelligence in the sense that - every agent is made of parts, all of us. - And what you want is for the (high level) agent to have a causal power that is not the same as simply tracking the microstates, the particles.

key insight - high level governance (consciousness) vs low level intelligence - This is a very important observation - It says that a multi-cellular being such as a human being can have consciousness that has agency for the entire organism and governs at that high level, and it must have this beyond just the cognition and intelligence at the lower cellular and subcellular level

Really interesting and innovative method for using multiview perspective data to learn human pose and pedestrian detection.

Seems like from a historical perspective hierarchical databases were more prevalent in the 1960s and relational databases didn't exist until the 1970s. (check references for this historically)

Of course one must consider that within a card index or zettelkasten the ideas of both could have co-existed in essence even if they weren't named as such. Some of the business use cases as early as 1903 (earlier?) would have shown the idea of multiple storage and relational database usage. Beatrice Webb's usage of her notes in a database-like way may have indicated this as well.

https://github.com/CondeNast/atjson

They're using annotations in this context more like CSS, but instead of adding the markup into the content as is done in HTML and processing it, they've physically separated the text and the markup entirely and are using location within the text to indicate where the formatting should take place.

t Laurie Voss's crowdsourced set of examples of things that have structure & control in the form of the following: - centralized - hierarchical - federated - distributed - decentralized

Picture below: Link to tweet: https://twitter.com/seldo/status/1486563446099300359?s=20&t=C6z9xUF_YBkOFmfcjfjpUA

Maarten van Smeden. (2021, March 25). 🚨🚨NEW EVIDENCE PYRAMID🚨🚨 https://t.co/RnGfl337tD [Tweet]. @MaartenvSmeden. https://twitter.com/MaartenvSmeden/status/1375008127737851904

Good explanation about semantic fields.

I assume the same or an even stronger statement can be made about semantic classes (which to me are like more clear-cut, distinct semantic fields), then? 

Databases and filesystems are both systems which mediate the interaction between user and stable storage.

Often, the implicit aim of a database is to capture as much as they can about the structure of the data they store. The database is the all-knowing and exclusive arbiter of access to data.

If a user wants direct access to the data, a database isn't the right choice, but interacting directly with stable storage is too involved.

A Filesystem is a lightweight (container) abstraction in between a database and raw storage. Filesystems are opaque to the system (i.e. visible only to the user) and allow for a simple, hierarchical organizational structure of directories.

Peel, L., & Schaub, M. T. (2020). Detectability of hierarchical communities in networks. ArXiv:2009.07525 [Physics, Stat]. http://arxiv.org/abs/2009.07525

Ortiz, E., García-Pérez, G., & Serrano, M. Á. (2020). Geometric detection of hierarchical backbones in real networks. ArXiv:2006.03207 [Physics]. http://arxiv.org/abs/2006.03207

Peixoto, T. P. (2020). Revealing consensus and dissensus between network partitions. ArXiv:2005.13977 [Physics, Stat]. http://arxiv.org/abs/2005.13977

Ciranka, S. K., & van den Bos, W. (2020). A Bayesian Model of Social Influence under Risk and Uncertainty [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/mujek

Multilevel correlations: A new method for common problems. (2020 April 13). R-bloggers. https://www.r-bloggers.com/multilevel-correlations-a-new-method-for-common-problems/

With the advent of Google Docs we're finally moving away from the archaic indexing mentioned here. The filesystem metaphor was simple and dominated how everyone manages their data-- which extended into how we developed web content, as well.

The declaration that Hierarchical File Systems are Dead has led to better systems of tagging and search, but we're still far from where we need to be since there is still a heavy focus on the document as a whole instead of also the content within the document.

The linearity of printed books is even more treacherously entrenched in our minds than the classification systems used by libraries to store those books.

One day maybe we'll liberate every piece of content from every layer of its concentric cages: artificial systems of indexing, books, web pages, paragraphs, even sentences and words themselves. Only then will we be able to re-dress those thoughts automatically into those familiar and comforting forms that keep our thoughts caged.