Privacy and latency are the two biggest barriers to AI adoption in manufacturing. Factories don't want to send sensitive production data to the cloud, and they can't afford the round-trip time of an API call.
The Hardware Revolution
We are seeing an explosion of specialized hardware. NVIDIA's Jetson Orin, Hailo-8 AI accelerators, and even NPUs integrated into standard Intel and AMD CPUs are making it possible to run meaningful inference workloads locally.
TinyLLMs
Models like Llama 3 (8B) and Mistral 7B, when quantized to 4-bit, can run comfortably on consumer-grade GPUs or even high-end standard RAM. This enables "Chat with your Documentation" features for maintenance technicians that work completely offline.
The Impact
This decoupling from the cloud democratizes AI. A small SME can deploy an intelligent monitoring system without a massive Azure or AWS contract. It puts the power back into the hands of the OT engineers.
About the Author
Nay Linn Aung is a Senior Technical Product Owner specializing in the convergence of OT and IT.