Welcome to Core dump, the one stop for techies, in this episode, we have Dr bheemaiah talk about provable ML.
Gecko: so all NP complete problems are Z Complete, and hence tensorizable, based on the machine dreaming, so essentially ML problems are provable in tensorization, and complexity.
Supervised and unsupervised learning is encapsulated in neural architectures, tensorized to formally define the complexity, trainable and transfer learnt to solve all NP complete problems.
Have we found any exceptions, any unsolvable problem that is not Z Complete?
None so far.