The entire field of Service Reliability is dedicated to finding the exact boundaries of acceptable errors, and defining the response function when those boundar

The entire field of Service Reliability is dedicated to finding the exact boundaries of acceptable errors, and defining the response function when those boundaries are crossed. I would assume this actually gels very nicely with neural nets since its constantly optimizing for fitness. Hell in theory you could bake in your SLA/SLIs into the models to self correct? Give the model direct feedback that its unfit?