If all human data were structured in one massive knowledge-graph (a global knowledge graph), we could unlock this potential. Fortunately, Solid is that knowledge graph.

I do expect new social platforms to emerge that focus on privacy and ‘fake-free’ information, or at least they will claim to be so. Proving that to a jaded public will be a challenge. Resisting the temptation to exploit all that data will be extremely hard. And how to pay for it all? If it is subscriber-paid, then only the wealthy will be able to afford it.

two-way links

🌟 Highlight words as they are spoken (karaoke anybody?). 🌟 Navigate video by clicking on words. 🌟 Share snippets of text (with video attached!). 🌟 Repurpose by remixing using the text as a base and reference.

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).

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

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

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

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.

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)

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.

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.

In fact, such small effectively closed scientific communities built on interpersonal relationships already exist to some extent

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.

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.

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]

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

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

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.

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

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.

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.

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

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.

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