[summary: Arbital is an online, collaborative platform for explaining everything math ([Arbital_scope for now]). To see what the platform can do, check out Arbital's guide to Bayes's Rule.]
Arbital is an online, collaborative platform for explaining everything math ([Arbital_scope for now]). We're still in beta but we've got a bunch of cool features and some great content todo: link to great content.
Our vision is to combine Wiki-style collaborative editing with a StackOverflow-style trust system to empower people who have demonstrable expertise to build a comprehensive structured network of knowledge and explanations. If this sounds awesome to you too, we'd like to [Arbital_contributing have you on board].
TODO: some connecting bit here, maybe a header
Explaining things is difficult. Every reader comes in with a different level of background knowledge and needs a different explanation. However the author pitches the explanation, most readers will not get the version which would best suit them. Websites like Wikipedia face difficult tradeoffs and end up with many long, technical pages that try to cover everything a person might want to know about a given subject.
We solve this collection of problems by having highly modular content, in particular encouraging different versions of the same page at different levels of technicality and for people with different backgrounds (e.g. x for Computer Scientists). We track what requisites you know and guide you towards versions of pages which are most useful to you, allowing you to rapidly learn without having to search around for background information or trawl through things you already know.
TODO: Have a page for future plans which we want to point people at, and link to it. Currently there are a few parts of pages, but none contain all the right things. This is important for people who want the big picture.
[comment: Imagine being able to find explanations which are suited to your background and preferred level of guidance.
Have you tried to learn online? Even been frustrated by explanations being poorly targeted?]