Abstract: Techniques for massively-parallel real-time database-integrated machine learning (ML) inference are described. An ML model is deployed as one or more model serving units behind an endpoint. The ML model can be associated with a virtual table or function, and a query that is received that references the virtual table or function can be processed by issuing inference requests to the endpoint by the query execution engine(s).

Abstract: Techniques for determining image similar are described. For example, a computer-implemented method comprising: receiving a request to determine similarity between a first image and at least one other image; determining similarity between the first image and at least one other image based upon one or more Gram matrix-based style values and one or more vector distance calculation-based content values as determined from one or more outputs of layers of a convolutional neural network; and providing an indication of the similarity of between the first image and the at least one other image is described.