8 posts tagged AI Safety. ← Back to all posts
Three simultaneous releases ship a complete open-source stack for AI-accountable robotics: rcan-py v0.1.0 on PyPI, @continuonai/rcan-ts v0.1.0 on npm, and OpenCastor v2026.3.6.0 with deep RCAN v1.2 integration.
rcan-py v0.3.0, rcan-ts v0.3.0, OpenCastor v2026.3.8.0, §17 Distributed Registry, and RCAN-Swarm Safety — across four repos and most of the day.
Coordinated releases across four repos, green CI on all of them, a new swarm safety claim for OpenCastor, and the clearest picture yet of what the Robot Registry Foundation actually needs to function.
Every robot incident investigation starts the same way: what did it do, who authorized it, and can you prove it? RCAN is the protocol layer that makes those questions answerable — before the incident happens.
The automotive industry spent decades standardizing autonomy after the technology was already deployed. Robotics is at the same inflection point. RCAN, OpenCastor, and QuantumLink-Sim are a bet on doing it the other way around.
ISO 10218, OPC UA, IEC 62443, ROS2 — the standards that govern industrial robots today were written before AI was making the decisions. Here's what each covers, where they stop, and where RCAN fits.
Thariq Shihipar from Anthropic published a detailed breakdown of how they built Claude Code. Every design decision maps to OpenCastor — but for a different consequence space. And this week, that consequence space got a lot more political.
AI agents make claims. Those claims drive actions. If you can't verify the chain — what was claimed, when, and under what keys — you can't audit anything. Here's how quantum-link-sim's CommitmentEngine solves that.