Besearch cycles & DML

A besearch cycle is an agentic cycle to apply a new form of science peer to peer and core to that process is the ability to use DML, decentralized machine learning.

DML has to have foundations and those start with a challenge of proof of work between peers. Two peers can produce technical data standards between each other or two unknown peers start to build trust in another peers data and vice versa. Once we have trust in the data, agreement on the computation or machine learning algorithm is verified and each peer perform its solution or weights or parameters in a prediction equation or simulation. The next task is to aggregate those values peer to peer. How peers decide to 'add' up those machine learning is a challenge and how do we know when the model is complete or ready for use?