Research area / Agents & evaluation
Distributed Inference & Reasoning Evaluation
Nuera RDL studies how AI systems can reason, coordinate, and make decisions across many agents and machines, and how to check that those decisions are correct, traceable, and good for the people they affect.
Distributed inference
When many AI agents share work, results need to stay fast, consistent, and traceable. This research connects to two of our programs:
- Project Forkling: an open-source framework for distributed decision-making and multi-agent coordination.
- Project Quicksilver: an operating system for autonomous companies, in which AI agents propose actions and a deterministic kernel checks authority and risk before anything happens.
Reasoning and outcome evaluation
We treat evaluation as an engineering discipline. Systems are tested against explicit tasks, observable intermediate steps, edge cases, and repeatable success criteria, not only final answers. Two early-stage efforts sit here:
- Aura models what the people behind an automated system actually want, and keeps every change to that record visible.
- WAES is a set of evaluation suites for checking whether AI outcomes are good for the people they affect.
Contact
Jeremy Beebe, Founder
jeremy.beebe@nueraresearch.com
(719) 849-8965
linkedin.com/in/jeremybeebe