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Signal.
Technical writing on physical AI safety, edge inference, industrial automation, and the engineering decisions that determine whether safety systems actually work.
VOL.01
EST.2026
BRISBANE, AU
#03TechnicalICLAI SafetyResearch8 min read
Inverse Constraint Learning: What It Is, Why It Is Different, and Why It Matters for Physical AI
Most AI safety systems tell machines what to do. Averiom's ICL approach learns what not to do from expert operator behaviour — a distinction that turns out to matter enormously in physical environments.
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#02Industrial SafetyMiningManufacturingPhilosophy6 min read
The Cage Problem: Why Industrial Safety Has Been Trading Productivity for the Illusion of Control
For 40 years, the dominant paradigm in industrial safety has been exclusion zones and hard stops. This has kept workers safe by keeping them away from the work. It is time for something better.
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#01EngineeringEdge ComputingSafety Architecture7 min read
Why 5ms Is the Line Between a Safety System and a Logging System
The physics of intervention latency — why cloud-based safety architectures are fundamentally incapable of protecting humans at the point of action, and what the numbers actually mean.
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