109 karma · joined December 25, 2023
Here is a java lib that apply regex to stream of Objects that could be used to achieve this purpose.
https://github.com/search?q=state-machine&type=repositories
This is a very common pattern in Ruby to manage state. It's especially useful to guard entering impossible states with respect to business logic and figuring out what went wrong. Something along the lines of:
Can't transition Command from 'ordered' to 'to-deliver': paid() == false
Not sure whether you talk about the uranium yellow/green color, or the brief hallucination of a light spot (happened to me just a few minutes ago, hadn't had one in a long time).
I don't have such an hyperbolic mental palace, and this doesn't really give me the ability to establish a global map but I relate a lot to what you wrote. Sometimes as I reach the climax of a long deep thought, I'm thinking via vision exclusively to the extent I don't even pay attention to what my outer eye sees and I stumble upon some insight that is sometimes almost impossible to convey in language, not because it lies beyond, but because the intrusion of language causes the idea to collapse: words points to dangling shapes that mean barely anything because the rest of the painting has gone away.
To those that have read this far and can't relate to this way of thinking, this isn't a superpower, those are rather rare experiences of altered states.
Talking about this is a kind of taboo and may cause some smiles, and indeed if there is a deeper truth to these experiences about the computational or geometric nature of the mind, maybe in the same way synaesthesia mirrors spectrograms, it won't help people working in machine learning a lot (even though some like Lecun seem to use their own visual introspective abilities as a source of inspiration).
However they may prove to be crucial in conceiving what kind of use brain chips should be put too. For now it seems we're walking through a thick fog in that direction with envisioned application being confined to interfacing to external computers or increasing cognitive abilities quantitatively, such as perfect memory and so on. If I could sustain such experiences durably, with a high level of control and enhanced geometric/mathematical understanding, I believe this would be akin to a superpower, yes.
Well look at the drawings I posted below: mathematical notions mixed with ad-hoc diagrammatic distinctive elements such as colors and marks. With maybe a theorem that posits that every mixed representation like theses matches a colorless, unannotated, rigorous mathematical object ?
In fact I come from a structural linguistics background, and when I pictured how one could extrude a semiotic square into another one, I felt like I understood the vague intuition behind homotopy type theory: the metaphor goes like this – the extrusion volume must be water tight for the squares to make sense.
Suppose you read Dostoyevsky's short story "Another Man's Wife and a Husband Under the Bed." In that case, you might notice that the protagonist's vertical position, as he eavesdrops on what he believes to be his wife through the wall of another man's apartment while standing alone in a corridor, mirrors the horizontal position he later assumes when hiding under the bed of his wife's presumed lover. This physical positioning reflects his moral descent, particularly as he is not alone this time. Beneath the bed with him is another man, clandestinely involved with yet another man's wife. This leads to help us picture that our protagonist is just as disconnected from his wife as the man lying next to him under the bed or the husband unknowingly sleeping above them—if not more so.
Granted I don't have the detailed vision of this semiotic diagram, but coming up with the skeletal structure is exactly what the job of a semiotician consists in (which I'm not). What matters is that all these equivalence classes the writer lays down, just like in mathematics, allows meaning to flow. His vertical loneliness must match his horizontal promiscuity for the story to operate this crescendo. Clog theses connections, and the inner structure of the object they tie together disappear too. Digging into Saussure and Voeivodsy one can realize they shared a common obsession about identity, for it is precisely when physical objects become indistinguishable that they can be referred to with the same terms and that conceptuality arises (Aerts, 2010s and onward).
"Different names to the same thing" and the "same name to different things": the two directions on the homotopical ladder.
Note: I'm 100% in postmodern mode here, this goes way above my head of course.
>many distinct (euclidian) spaces, whose axis connect to each other through a graph
Imagine having pictures hanged on the walls of your mental palace that act as portals to others rooms and corridors within that palace, and that must exist parallelly to each other, in different "universes" otherwise their volumes would intersect. The kind of geometry the Antichamber video game features.
Or picture this: a representation that relies on its axis to convey meaning, for instance the political compass meme. Walk along an axis long enough and it will connect orthogonally to another axis, for instance, authoritarianism may connect to anger from the emotional compass.
Simplexes: a generalization of triangles to n dimensions. A 2-axis representation (the political compass for example) could connect to spaces with 3 axis (the ascended political compass: https://external-preview.redd.it/UQgZCVQ4OLg_Hz16FGdu9-qxfq9...).
To represent this you could connect one tip of a segment (a 1-simplex) to the tip of a triangle (a 2-simplex), each vertex in these figures representing an axis. This is where my deleuzian metaphore collapses because I'm conflating the notion of axis with the notion of the "left" and "right" part of an axis. And I'd also be tempted to consider that planes should be allowed to connect to axis (to support that portal through a painting I mentioned above).
So this is just a sketchy thought, but this seems legitimate as it's not something I conceptualize but something I perceive (sometimes). But I think there may be something interesting behind these perceptions because it seems they deal with separate concerns through some kind of orthogonal geometry that is structured: putting a concept in a dimension orthogonal to another concept doesn't lead that dimension to be orthogonal to all other dimensions/concepts in your mental palace, as that would be the case if it took the shape of a n-dimensional space. And because the orthogonality is structured, it allows to deal with more than 3 concepts spatially at the same time and embed them within something your eye can picture in 2D or 3D, using diagrammatic annotations (colors, marks, etc). Finally it allows to put a concept C in several orthogonal relationships to distinct concepts, for instance A and B, and to keep these different instantiations of concept C orthogonal to each other.
This is what my mind pictured as I was explaining this ; colors and graduation marks/boxes faithfully representing what I just perceived: https://pasteboard.co/kMecyenyZdzg.png
Note that the two colors, the green of the axis and of red of the sticks could be thought as two individual concepts of their own, orthogonal to each other.
https://pasteboard.co/3VYEyepnVouQ.png
If a mathematician is reading this, please accept my deepest apologies. Here's another paper that seems thematically related to this: https://ieeexplore.ieee.org/abstract/document/10008602
It represents the flow of data between channels/threads as a sequence diagram using PlantUML. Today I implemented core.async/onto-chan! (it spins a thread that will take items from a sequence and put them onto a channel). Here's what it looks like:
https://pasteboard.co/VhvDroREOvOQ.png
It's especially useful in Clojure, as the experience with channels is not as polished as in Go (or so I heard): when a put or a take hangs, your only recourse is to sit and squint at your code. This tool will color them red, so you can immediately spot what's wrong. It also allowed me to spot a channel spaghetti plate I had not anticipated and wouldn't have remarked otherwise.
For now I've taken a "maximalist" approach which includes inspecting buffers, so it incurs a heavy runtime penalty that's only ok at dev-time (+ it keep tracks of the whole trace, so no flight recording in sight for now).
In the future I'd like to give it a proper interface (it's just a svg file with hoverable elements for now), maybe using constraint-based graph layout to lay out the sequence diagram using cola.js/adaptagrams or the sequence diagram from Kiel university Kieler project when it's integrated into the Eclipse Layout Toolkit. Thesis from the developer of this module:
https://web.archive.org/web/20220519080528id_/https://macau....
picture: https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcRx5Xam...
It seems it's used by cognitive models, although I'm not formally trained enough to tell exactly how:
And this is the way. (Machine) learning theory is in some way a meta-science about how to do science from facts in order to construct theories that effectively explain these facts. What you are asking for will never amounts to a short set of equations. There is not elegant theory of how to perceive numbers and this is why symbolic artificial perception, rule engines, spam detection, RDF ontologies, etc never took off. You're idealizing knowledge as a set of representations without ever reifying how these representations come into existence. We're departing a world of representation toward a world driven by "incarnations": you can't make sense of a how a brain works without the help of another brain, and this is why there is so many things being researched at the intersection of deep learning and neuroscience. I'd even go as far as considering this is in fact how brains work: they can be composed and decomposed monoidically.
In short:
>a structural understanding
There is no such thing
>the structures they produced in N-dimensional space [...] this brute force approach
This is a contradiction. I'm not saying there won't be "structural insights along the way" nor that throwing categories into the machine learning mix won't be useful, but the learning-like aspect that you denote by "brute force" is more fundamental, and in some way above the very processus of science.
In less time that it would take me to figure out how dictionary comprehension work in python. But hey, I guess you already know about these use cases.
>Honestly I’ve not encountered an author I resonate with yet
Surely, you'd know how to make it better than a smart 4th grader.
GPT reconstruction:
The dream reaches its peak when you meet the "final boss" of the game: an entity that embodies the ultimate barrier to communication. To overcome this obstacle, you must synthesize everything you've learned about "it" in the dream and present a coherent vision that is true to yourself. As you articulate your final understanding of "it", the maze dissolves around you, leaving you in front of a giant mirror. In this mirror, you see not just your reflection but also all the characters, passions, and ideas you encountered in the dream. You realize that "it" is actually a reflection of yourself and your ability to understand and share your inner world. The dream ends with the title revealed, "Game to Learn to Communicate about It and Its Player", meaning the whole process was a metaphor for learning to know and communicate your own "it" - your personality, thoughts, and emotions - with others, and that you are both the creator and the discoverer of your own communication game.
My note:
The continuation of the dream corresponds to an abrupt change of scene. I find myself in my bed, in the dim light of my room, facing a mysterious silhouette. As I repeatedly inquire about its identity, I stretch my hands towards its face to feel its features as I cannot clearly see them. Then, a struggle begins, during which I panic, giving the dream a nightmarish turn. Noticing that the dark figure mirrors my movements, I realize it's myself. Suddenly under my duvet and as I struggle to get out, I feel jaws and teeth against the sheets. I call out for my mother, whom I seem to hear downstairs, and that's when my vision fades, and I see the dream's source code displayed behind. It consists of ChatGPT prompts shared on the lime green background of an image-board. At the bottom, I then see the dream's title: "Game to learn how to communicate about It and its player."
https://onlinelibrary.wiley.com/doi/abs/10.1002/ejsp.52
>The durability of anchoring effects
>Recent research suggests that judgmental anchoring is mediated by a selective increase in the accessibility of knowledge about the judgmental target. Anchoring thus constitutes one instance of the judgmental effects of increased knowledge accessibility. Such knowledge accessibility effects have repeatedly been demonstrated to be fairly durable, which suggests that the effects of judgmental anchoring may also persist over time. Consistent with this assumption, three experiments demonstrate that judgmental anchors influence judgment even if they were present one week before the critical judgment is made. In fact, the magnitude of anchoring was found to remain undiminished over this period of time.
>AI-Moderated Decision-Making: Capturing and Balancing Anchoring Bias in Sequential Decision Tasks
See:
https://www.cambridge.org/core/journals/judgment-and-decisio...
>A number of studies have shown the robustness of the anchoring effect. Anchors can influence judgment even after weeks or months (Reference MussweilerMussweiler, 2001; Reference Yoon, Fong and DimokaYoon & Fong, 2019). The anchoring effect is present even in experts in the judgmental domain (Reference Englich and MussweilerEnglich & Mussweiler, 2001; Reference Englich, Mussweiler and StrackEnglich et al., 2006). An anchor can influence subsequent judgment even if it is clearly implausible (Reference Strack and MussweilerStrack & Mussweiler, 1997) or when it is compared to a different object (Reference Frederick and MochonFrederick & Mochon, 2012; Reference Mochon and FrederickMochon & Frederick, 2013).
https://www.jcr-admin.org/preprints/chernev-preprint.pdf
>Semantic Anchoring in Sequential Evaluations of Vices and Virtues
>How do people evaluate sequentially presented items? Prior research suggests that sequential evaluations are subject to anchoring biases, such that the values of subsequently evaluated alternatives are assimilated toward the initially considered option. The present research argues, however, that sequential valuations often lead to contrast rather than assimilation effects, whereby values of the subsequently estimated alternatives are distanced from the initially evaluated option. These contrast effects are attributed to semantic anchoring, which stems from evaluating conceptually related options classified into opposing categories (e.g., vices and virtues).
https://en.wikipedia.org/wiki/Anchoring_effect
More specifically, sequential anchoring:
>Consider the following scenario: A reviewer evaluates many unqualified applicants for a university program successively, and the next applicant to be reviewed is an average (borderline admit-reject) applicant. Because the evaluator is influenced, or anchored, by recently made decisions, this borderline applicant might be admitted to the program. On the other hand, when an evaluator is anchored by having reviewed many qualified applicants, the same or a similarly borderline applicant might be rejected (Figure 1). In this scenario, individual fairness, stating that individuals with similar characteristics should be treated similarly [8], is impaired, and wrong or inconsistent decisions can have a consequential impact.
Source: https://dl.acm.org/doi/fullHtml/10.1145/3491102.3517443
> When we found out about the “nogil” fork of Python it took a single person less than half a working day to adjust the codebase to use this fork and the results were astonishing. Now we can focus on data acquisition system development rather than fine-tuning data exchange algorithms.
You need a human eye to figure that out and this is the task nlm-ingestor tackles.
As for the content, semantic contiguity is not always guaranteed. A typical example of this are conversations, where people engage in narrative/argumentative competitions. Topics get nested as the conversation advances, along the lines of "Hey, this remind me of ...". Building up a stack that can be popped once subtopics have been exhausted: "To get back to the topic of ...".
This is explored at length by Kebrat-Orecchioni in:
https://www.cambridge.org/core/journals/language-in-society/...
And an explanation is offered by Dessalles in:
https://twitter.com/parthsarthi03/status/1753199233241674040
processes documents, organizing content and improving readability by handling sections, paragraphs, links, tables, lists, page continuations, and removing redundancies, watermarks, and applying OCR, with additional support for HTML and other formats through Apache Tika:
It's hard
Graphviz-like generic graph-drawing library. More options, more control.
Experiments by the same team responsible for the development of ELK, at Kiel University
https://github.com/kieler/KLighD
Kieler project wiki
https://rtsys.informatik.uni-kiel.de/confluence/display/KIEL...
Constraint-based graph drawing libraries
JS implementation
https://ialab.it.monash.edu/webcola/
Some cool stuff:
HOLA: Human-like Orthogonal Network Layout
https://ialab.it.monash.edu/~dwyer/papers/hola2015.pdf
Confluent Graphs demos: makes edges more readable.
https://www.aviz.fr/~bbach/confluentgraphs/
Stress-Minimizing Orthogonal Layout of Data Flow Diagrams with Ports
https://arxiv.org/pdf/1408.4626.pdf
Improved Optimal and Approximate Power Graph Compression for Clearer Visualisation of Dense Graphs
https://nypost.com/2024/01/08/news/google-co-founder-sergey-...
Sometimes, the repetition of encounters is just as meaningful as the people we meet.
https://en.wikipedia.org/wiki/Small-world_network https://www.quantamagazine.org/new-proof-shows-that-expander... https://telecom-paris.hal.science/hal-03814119/document
As for making things clearer for everyone, well, this is code I work on solo (hobby), but I think providing example inputs as well as debugging macros can help a lot. Consider the following:
(defn parse-it [dependencies]
(pp->> dependencies
str
str/split-lines
(keep (|| re-matches #"- (\d+(?:\.\d+)?) -> \[((?:\d+(?:\.\d+)?(?:, ?)?)+)\]"))
(>>- (map-> (juxt-> second
(->> third (re-seq #"(?:\d+(?:\.\d+)?)")))))))
(parse-it (str "- 4 -> [1, 2, 3]\n"
"- 5 -> [4, 2]\n"
"- 6 -> [1, 2, 5]"))
;; The use of pp->> will lead to this getting printed
;; ->> dependencies : "- 4 -> [1, 2, 3]
;; - 5 -> [4, 2]
;; - 6 -> [1, 2, 5]"
;; str/split-lines : ["- 4 -> [1, 2, 3]"
;; "- 5 -> [4, 2]"
;; "- 6 -> [1, 2, 5]"]
;; (keep (|| re-matches #"- (\d+(?:\.\d+)... : (["- 4 -> [1, 2, 3]" "4" "1, 2, 3"]
;; ["- 5 -> [4, 2]" "5" "4, 2"]
;; ["- 6 -> [1, 2, 5]" "6" "1, 2, 5"])
;; (>>- (map-> (juxt-> second (->> third ... : (("4" ("1" "2" "3"))
;; ("5" ("4" "2"))
;; ("6" ("1" "2" "5")))
(->> [1 2 3 4]
(map (when| odd? inc)))
;; vs
(->> [1 2 3 4]
(map (fn [x]
(if (odd? x)
(inc x)
x))))
;; result (2 2 4 4)
(-> k-or-ks (when-not-> coll? list)
(map-> ...do-something))
;;vs
(let [ks (if (coll? k-or-ks)
k-or-ks
(list k-or-ks))]
(map ...do-something
ks))
(-> 1 (juxtm-> :incd inc :decd dec))
;; vs
(let [n 1]
{:incd (inc n)
:decd (dec n)})
(-> '(1 2)
(•- (conj (-• first dec)))) ;; => (0 1 2)
(-> {:a 1 :b 2}
(•- (-> (>-args (-> (/ (-> :a) (-> :b))))
(->> (assoc (-•) :result))))) ;; => {:a 1, :b 2, :result 1/2}