Hi Observable Friends,
LalTal is a startup with a bold vision to visualize and map all of human knowledge. Danny Hillis and Esther Dyson are on our advisory board. I am the founder and I am looking for a data visualization expert to hire to help me do some early brainstorming sessions. Please reach out to me if you might be interested: john@LalTal.com (650)966-4538
Regards,
John
Company Overview
Imagine a world in which you have a map that shows everything you’ve ever learned. What if you could compare your map to the maps of others, find areas of complementary knowledge, and connect with those people to learn more? Imagine a map of all human knowledge. What insights could you gain about humanity if you had that map? What paths would you take if you could see all the ways to learn what you wanted to learn? Who are the people you would meet along the way?
LalTal is a people-powered learning platform that transforms human learning by bringing people together for one-to-one learning experiences. Everyone has something they want to learn, and everyone has knowledge they’d love to share. We super-power learning by mapping our users’ knowledge so we can connect the right people at the right time to create enjoyable, engaging, human-to-human learning experiences.
Knowledge Print Problem Statement
For an individual user, LalTal is going to build up data about what they know, and what they don’t know. Imagine that we had these assets:
- A list of core concepts (eg, “Protein Translation”) that could number in the millions
- A graph of how these concepts are connected to each other, with billions of intermediate connections
- A measure of a person’s understanding for each concept (eg, “novice”, “intermediate”, “expert”, “nobel prize winner”)
The problem with just visualizing these concepts is that the human mind cannot understand millions of graphed, depicted data points. We believe we need a different visualization concept to help to make this comprehensible by the human mind. This is a simple Knowledge Graph Visualization problem, but a raw visualization is not usable, eg:
Q: How would we convey such a knowledge graph to an end user, in a way that they would understand their personal understanding of all of human knowledge?