My response was only in regard to the speed in which something like IoT devices can operate.

You’re right that goals/directions of LLMs can be persisted anywhere, but a swarm or fleet of AI running on IoT devices will be severly hampered by compute (based on current models). Which was the main point I was making, in that there is only so much you can do to distribute their processing. Meaning you can parallelize the number of models, but can’t speed them up beyond a certain limit. This is based on the fact that some form of a layer and it’s weights must exist within the memory of a single device.

The downside to this limitation is that it is temporary, eventually IoT devices will probably be powerful enough, or the worms could just attack phones/laptops and easily get the compute they need. I think the real risk of IoT devices is low security mixed with low “supervision” (no one would easily notice their IoT device is doing extra processing).