The FABRK Foundation believes that humanity has only scratched the surface of what is possible when billions of people connect in a common digital ecosystem. See our whitepaper. We believe that this new world is best explored when essential data - such as the network of our personal connections - is liberated from the control of today's social media giants. The world’s 25 million developers are also hungry to remove these giant middlemen, gaining direct access to users.
When users own, and are paid for, their data and attention, they can support developers, user interfaces, and online habits of their own choice. This user freedom is the bedrock that allows developers to build innovative solutions and services, unlocking the full power of our social connections.
Why Distributed Proof of Value (DPoV)?
DPoV gives the power of social networks back to the users. Distributed Proof of Value (DPoV) means that FABRK distributes voting power, thereby leadership over the future of the network, based on the shape of users’ network behavior. As experts have now had more than a decade to study very large datasets on the transmission of content through modern digital networks - particularly the spread of false rumors - it has become clear that popularity does not always indicate a high reputation or value. In fact, sometimes quite the opposite - this is why DPoV is focused on identifying signals in the shape, not the size, of users’ network behavior in order to bestow voting power.
What is Federated AI and how does FABRK use it?
Federated AI Provides Intelligence and Privacy. Massive, centralized stores of personal demographic and behavioral data combined with economic incentives that strongly incorporate value to users are the recipe for the disasters we see playing out on a weekly basis with large, incumbent social data and content platforms and their frequent scandals in North America and Europe. To this end, FABRK is ready for Federated Learning, a machine learning discipline in which data models can be sent to a User Node (with their permission), where it processes private, local data, becoming a bit smarter before the model (but not the data) is returned to the developer.
The greater the number of individually-trained models the developer can synthesize, the more sophisticated and capable the resulting model. Combine this with the FABRK ecosystem’s open market for feeds and suggestion products, and you have a recipe for products that compete to deliver greater user value and intelligence, while protecting user data like never before.
What can developers use to build on the FABRK People Protocol?
Where can I find information about the team behind FABRK?
Check out our team section