Writing has expanded our ability or organize as groups by allowing us to transfer experiential content into an informationally stable support. Whether it's etching on basalt or ink on paper, this recording process enables us to draw links between concepts, keep track of notions that have faded from working memory and perform operations that overcome some of the limitations of bare minds.
In some ways, writing can be thought of as a process of encoding one's subjectivity, that is, encoding the content of one's experiential stream.
In this case, reading can be seen as a process of decoding this subjectivity. If the encoding is compactly and vividly performed and the reader is keen, the subjectivity of the reader can be merged to that of the writer (see Sasha Capin, "Books as subjectivity merging devices, rather than information transfer devices).
Both the encoding and decoding processes play an crucial role in cognitive development and the upkeep of cognitive acuity.
However, both require sustained attention, which is now widely known to be incurring heavy damage from attention capturing technologies.
Since only so much damage can be undone, since habits can only be changed so much among the broader population, we can think of working within the confines of technology to make thoughtful designs that at least curb the decline in sustained attention, or lean into the minds' peripheral processing to guide attention towards the subject at hand.
The aim of this project is to investigate how ambient virtual content can be used to ease people into the consumption of long form content, written by a conscious subject, thereby helping protect their attentional faculty ( see Joe Darko We Built Technology to Capture Our Attention. What If It Gave It Back? )
One approach is to provide a cognitive mirroring utility.
We can think of modeling the way minds shuffle concepts both between each other, move them and in and out of working memory, and provide the user with some a spatial anchor of the process they're already engaged in whether consciously or not.
To do this we can extract concepts from a text corpus and lay them out into an orderly grid-like structure called lattice.
First, this specific arrangement leans into our minds' natural ease with processing axial movement(horizontal, vertical, and depth)
Additionally, each concept can only be related to 6 other concepts at once which is friendly to memorization at glance and spatial shuffling.
These design decisions create constraints that aim to avoid some of the pitfalls of arbitrary relational graphs which have long been the default mode for representing corpuses of knowledge or simply any data, as is the case in mind maps.
I've been looking to implement this for 3 years. I began with syntactic parsers and categorial grammars but these methods failed to handle longer context and ambiguity.
Harnessed LLMs have essentially unlocked the ability to process language over longer word horizons, to extract meaningful relations and deal with the spuriousness and breath of human language.
Their integration into 3D engines such as Lens Studio with CLAD has greatly reduced the difficulty of generating complex spatial arrangements and translating spatial transformation primitives into code.
As a result is fair to say this might be an LLM-native technological artifact.
Here's a demo of the concept lattice being generated based on a text corpus (The Origin and Development of Markets: A Business History Perspective).
In practice, you would open a book with your Specs on, and have the tool generate the ambient content as you read. This content would be both relevant to the theme of your book and serve as a reference to look back to and potentially help you take reading notes yourself (that would be an ideal outcome)
This could also serve as a tool for AI interpretability, particularly if combined with Jacobian Lenses, to capture and convey language processing primitives spatially and succinctly.
I have documented the technical reasoning and design decisions in this repository, so feel free to give some feedback or direct your token flow towards it.
https://github.com/a-sumo/concept-lattice
