From a customer's perspective, "serverless" means consumption-based pricing as opposed to reservation-based, regardless of the actual technology being used.
Not that but maybe someone can explain if the technology is "AI" why it still takes tens of thousands of hours to implement a project? Shouldn't we call it AI when the frameworks can be implemented with relative ease? My point is that the level of customization required to achieve AI, in my opinion, doesn't make it very intelligent.
One of the primary methods to join multiple learned models is a decision tree (or combination of decision trees making a decision forest), which can be simplified as a series of if statements/conditionals. So if you join a 'is it a shirt' model with a 'is it striped' model you get two sets of things, and with how big data approaches this it is something you can do quickly. As other people have pointed out the issue here is that the NLP of the actual search is not creating a negation of two sets, it is returning the intersect of sets 'is it a shirt', 'is it striped' and shrugging its shoulders and either intersecting it with 'things with the text without', or throwing up its hands entirely based on the context because it wasn't programmed to do something smarter.
