Arbital: Google Maps for knowledge
While Arbital can do many things, currently it’s most geared towards providing the reader with a tailored explanation on any given subject. Arbital can find out what you know by asking a few questions, and then dynamically generate a tailored sequence of pages for you to read. Take a look at Bayes’ rule: Guide to see how that works.
Advantages of Arbital’s algorithm:
Arbital can cut out whole chunks of explanation if the reader already knows it, saving them lots of time.
Arbital helps you learn piecemeal. Most pages are pretty short and teach you one or two things, and each page brings you a step closer to learning what you are after.
If there are multiple pages explaining the same concept Arbital can pick the best one using a multitude of signals: page complexity, popularity, and author specified metadata.
Arbital dynamically modifies each page to tailor it to the reader’s current knowledge and preferences. For example, if you don’t read logic, the algorithm can replace the math formulas with text.
There is a single URL to learn a subject that works for everyone, even people with vastly different levels of prior knowledge.
A few examples:
If you want to learn Bayes’s Theorem, Arbital can find a tailored explanation for you based on how good you are at math.
If you are learning a new programming language, it will leverage your existing knowledge programming in general and instead of teaching you functions from scratch, it’ll skip directly to teaching you function syntax for the particular language.
If you want to understand a certain historical or modern event, it can figure out what previous and related events and figures you need to know about, so you have the full context.
Everything you see on any Arbital page was created by its author(s) using Arbital’s markdown syntax. There is no page-specific code anywhere. The magic ingredients are Arbital’s network of requisites and the relationships that the authors create. Each author can leverage all the existing pages in the Arbital system and their existing requisite connections. For example, if you create a blog post about “Social media graph analysis”, you can set “Graph theory” as a prerequisite. A reader who wants to understand your blog post can easily go through the sequence teaching them “Graph theory” after which they’ll be ready to read your post.