Real-time personalized recommendations by an ultrafast, lightweight, highly performant system

A system comprising:

• at least one processor;
• and
• one or more computer storage media storing computer-readable instructions thereon that when executed by the at least one processor cause the at least one processor to perform operations comprising:
• accessing, from a shared memory, a dataset comprising a binary matrix of user identifiers, item identifiers, and indications identifying whether users corresponding to the user identifiers have interacted with items corresponding to the item identifiers;
• and
• training a model by parallel processing, using a plurality of central processing units (CPUs) with access to the shared memory, each column of a design matrix determined from the binary matrix, each CPU processing one or more threads by performing a least squares analysis for each column of the design matrix within each thread, the trained model configured to provide an item recommendation from an input item interaction based on the training.