Post
106
I’ve just published a new article on State16 about a question I think will become increasingly important for robotics, embodied AI, VLAs, and world models.
Physical AI is already moving from research demos into real robots, vehicles, drones, and industrial systems. But as these models begin to produce actions in the physical world, we need to ask a harder question:
What is the runtime guardrail layer that makes these systems auditable, certifiable, and operationally safe?
In the post, I discuss the rise of World Foundation Models, Vision-Language-Action models, closed-loop autonomy stacks, and the missing layer between black-box AI policies and physical actuation.
Would be very interested to hear how this community thinks about runtime evaluation, action authorization, physical consistency checks, and safety layers for embodied AI systems.
Read here:
https://state16.ai/articles/physical-ai-is-already-here
Would love feedback, criticism, and pointers to relevant models, datasets, or evaluation frameworks.
Physical AI is already moving from research demos into real robots, vehicles, drones, and industrial systems. But as these models begin to produce actions in the physical world, we need to ask a harder question:
What is the runtime guardrail layer that makes these systems auditable, certifiable, and operationally safe?
In the post, I discuss the rise of World Foundation Models, Vision-Language-Action models, closed-loop autonomy stacks, and the missing layer between black-box AI policies and physical actuation.
Would be very interested to hear how this community thinks about runtime evaluation, action authorization, physical consistency checks, and safety layers for embodied AI systems.
Read here:
https://state16.ai/articles/physical-ai-is-already-here
Would love feedback, criticism, and pointers to relevant models, datasets, or evaluation frameworks.