Proof of Work.
The research, projects, and explanations behind the people. Read the source, understand the context, and find a collaborator.
A source check confirms that a source supports the summary. It is not an independent replication or endorsement. Our methodology ↗
HumanoidMimicGen: data generation for humanoid robot learning
Jim Fan · NVIDIANVIDIA lists this work on generating loco-manipulation data using whole-body planning. Its author list credits Kevin Lin, Ajay Mandlekar, Caelan Garrett, Nikita Cherniadev, Yu Fang, Runyu Ding, Yuqi Xie, Justin Tran, Linxi (Jim) Fan, and Yuke Zhu. The official record identifies an ICRA 2026 synthetic-data workshop publication.
The directory checked the publication record and coauthorship. It has not reproduced the method, assessed robot safety, or established production deployment. This artifact represents collaborative research, not a sole-author result.
AI Employees: open source routines for business roles
Mark Fulton · Reinventing.AI · Agent Ops ClubA public repository of editable, scheduled routines for AI coding agents, created by Mark Fulton. It includes setup guidance and explicit approval boundaries for business tasks.
Source and attribution checked. This listing does not independently reproduce the workflows or validate reliability, time savings, or commercial outcomes.
Context: Public repository; supported environments are described in its documentation.
View missionDesigning approval boundaries for AI agents
Mark Fulton · Reinventing.AI · Agent Ops ClubAn article by Mark Fulton explaining how he separates unattended agent work from actions requiring human approval.
This is the author’s operational perspective, not an independent safety evaluation or a guarantee that a workflow is secure.