24 Matching Annotations
  1. Apr 2022
    1. A filing system is indefinitely expandable, rhizomatic (at any point of timeor space, one can always insert a new card); in contradistinction with the sequen-tial irreversibility of the pages of the notebook and of the book, its interiormobility allows for permanent reordering (for, even if there is no narrative conclu-sion of a diary, there is a last page of the notebook on which it is written: its pagesare numbered, like days on a calendar).

      Most writing systems and forms force a beginning and an end, they force a particular structure that is both finite and limiting. The card index (zettelkasten) may have a beginning—there's always a first note or card, but it never has to have an end unless one's ownership is so absolute it ends with the life of its author. There are an ever-increasing number of ways to order a card index, though some try to get around this to create some artificial stability by numbering or specifically ordering their cards. New ideas can be accepted into the index at a multitude of places and are always internally mobile and re-orderable.

      link to Luhmann's works on describing this sort of rhizomatic behavior of his zettelkasten


      Within a network model framing for a zettelkasten, one might define thinking as traversing a graph of idea nodes in a particular order. Alternately it might also include randomly juxtaposing cards and creating links between ones which have similarities. Which of these modes of thinking has a higher order? Which creates more value? Which requires more work?

    1. The latest advances in machine learning — namely transformers and self-supervised learning in natural language processing — will also make it possible to build personalized discovery engines that organize and surface information that is timely, relevant, and impactful

      And possibly summarize it. And connect it to your own knowledge graph.

      Readwise's spaced repetition and integration with Roam/Obsidian is doing some cool stuff with surfacing connections and serendipitous reminders. Here is a Twitter thread I wrote to myself when I started playing with it: https://twitter.com/alexbowe/status/1476817961897783296

  2. Nov 2021
    1. In this proposed system, tags are full-fledged standalone files. They can be published and discussed just like any traditional heavyweight file can.

      Tags are first class

    2. The solution is to create a tag file that points to the original and edited photo, like DerivedWork(original=(some hash), derived=(some hash)).

      Relational tags

  3. Oct 2021
    1. Great teams have a plan to win when -- surprise, surprise -- they learn that a dozen other teams are pursuing their previously-thought-to-be-unique idea. They persevere when others (including us) tell them that ideas are cheap until they are brought to life. They both see themselves as unique and list many companies as their competitors.
    2. We believe more work in the future will look like that of software developers today (automating away tasks and harnessing the flexible power of computers to get work done)
    3. Soon we will see a one-person billion-dollar company, as many of the most talented individuals choose to work for themselves — as founders, in the creator economy, as freelancers, or in some other way.
  4. Aug 2021
    1. In 1963, Ted Nelson coined the terms 'hypertext' and 'hypermedia' as part of a model he developed for creating and using linked content (first published reference 1965).[7] He later worked with Andries van Dam to develop the Hypertext Editing System (text editing) in 1967 at Brown University.
  5. Jan 2021
    1. In fact, such small effectively closed scientific communities built on interpersonal relationships already exist to some extent

      so the weights in the reputation graph are personal knowledge, not citations or whatever.

  6. Nov 2020
    1. Knowledge graphs combine characteristics of several data management paradigms: Database, because the data can be explored via structured queries; Graph, because they can be analyzed as any other network data structure; Knowledge base, because they bear formal semantics, which can be used to interpret the data and infer new facts.

      Characteristics / benefits of a knowledge graph

    1. The ontology data model can be applied to a set of individual facts to create a knowledge graph – a collection of entities, where the types and the relationships between them are expressed by nodes and edges between these nodes, By describing the structure of the knowledge in a domain, the ontology sets the stage for the knowledge graph to capture the data in it.

      How ontologies and knowledge graphs relate.

    1. An ontology is as a formal, explicit specification of a sharedconceptualization that is characterized by high semantic ex-pressiveness required for increased complexity [9]. Ontolog-ical representations allow semantic modeling of knowledge,and are therefore commonly used as knowledge bases in artifi-cial intelligence (AI) applications, for example, in the contextof knowledge-based systems. Application of an ontology asknowledge base facilitates validation of semantic relationshipsand derivation of conclusions from known facts for inference(i.e., reasoning) [9]

      Definition of an ontology

    2. A knowledge graph acquires and integrates infor-mation into an ontology and applies a reasonerto derive new knowledge.

      Definition of a Knowledge Graph

  7. Oct 2020
    1. the name of something and when you press the button to go to the link if it wasn't there it made the card

      This is a phenomenally important UX insight and affordance that has become a foundation of how all modern wiki-linking knowledge graph tools work today. Kudos to Ward for this!

  8. Sep 2019
    1. The problem with the annotation notion is that it's the first time that we consider a piece of data which is not merely a projection of data already present in the message store: it is out-of-band data that needs to be stored somewhere.

      could be same, schemaless datastore?

    2. many of the searches we want to do could be accomplished with a database that was nothing but a glorified set of hash tables

      Hello sql and cloure.set ns! ;P

    3. There are objects, sets of objects, and presentation tools. There is a presentation tool for each kind of object; and one for each kind of object set.

      very clojure-y mood, makes me think of clojure REBL (browser) which in turn is inspired by the smalltalk browser and was taken out of datomic (which is inspired by RDF, mentioned above!)

  9. Aug 2019
    1. After the success of MORE, he went on to develop a scripting language whose syntax (for both code and data) was an outline. Kind of like Lisp with open/close triangles instead of parens! It had one of the most comprehensive implementation of Apple Events client and server support of any Mac application, and was really useful for automating other Mac apps, earlier and in many ways better than AppleScript.

      Yes, lisp!

      This is my thinking as well i.e. if you could (a) keep parentheses but render them differently. But not going over board in basic view so it's still editable like text. AND also have a more graphical view.

    2. After the success of MORE, he went on to develop a scripting language whose syntax (for both code and data) was an outline.

      Lisp! ;P

    3. More was great because it had a well designed user interface and feature set with fluid "fahrvergnügen" that made it really easy to use with the keyboard as well as the mouse. It could also render your outlines as all kinds of nicely formatted and stylized charts and presentations. And it had a lot of powerful features you usually don't see in today's generic outliners.

      fahrvergnügen German for "driving-pleasure. Yes! ALSO This is kind of central, in two ways.

      A. you need to have good story for mouse only and keyboard only B. you need to have multi-modal rendering

    4. Engelbart also showed how to embed lists and outlines in maps:https://www.youtube.com/watch?v=yJDv-zdhzMY&t=15m39s

      Now this is interesting. Instead of normal map here they've had to use this simple sketch/graph. Just arrows etc. BUT There maybe an actual value in that kind of simplicity!

      Question worth asking here is why we have to see all the detail on the map always? Google may have different incentives than just showing you only essential data.

  10. Apr 2019
  11. Feb 2017