Reflection AI demonstrates Beam building a live-updating map of the NYC subway from publicly available MTA data.
Beam checked authentication requirements, located subway and map geometries, and built the frontend and backend so the server keeps pulling live MTA updates.
Reflection says the demo shows Beam's reinforcement learning training produced reasoning that generalizes across domains such as ML workflows.
In this demo, Beam was prompted to create a live updating map of the NYC subway. Beam used the publicly available NYC MTA data, checked authentication requirements, and found subway and map geometries. Beam also built the right front and backend so the server keeps pulling live MTA updates.
This shows Beam’s RL training developed reasoning capabilities that allows it to generalize across domains like ML workflows.
Source: Reflection · x.comPublished · added here
