Abstract: A system for providing a travel recommendation to a user device includes a memory having instructions therein and at least one processor in communication with the memory. The at least one processor is configured to execute the instructions to receive communications of event data from the user device and generate an event schedule based at least in part on the event data. The at least one processor is also configured to execute the instructions to receive communications of travel context data and generate, using a cascaded machine learning model, a predicted optimal travel itinerary based at least in part on the event schedule and the travel context data. The at least one processor is also configured to execute the instructions to communicate the predicted optimal travel itinerary for reception by the user device.

Abstract: A computer-implemented method implemented by an AI onboarding system for performing trading partner onboarding. The method performs artificial intelligence (AI) training to learn onboarding information requirements. The method submits a transaction proposal to a blockchain business network (BBN) for obtaining a new business trading partner that requires trading partner onboarding. The method sends a business trading partner survey to the new business trading partner. The method monitors for queries regarding the business trading partner survey from the new business trading partner. The method provides responses to the queries based on the AI training. The method verifies using the AI training that the business trading partner survey is completed correctly by the new business trading partner.

Abstract: A computer-implemented method for presenting a companion shopper with one or more additional items to cross-sell and/or up-sell based on selected items of a first user and a predicted checkout time for the first user. The computer-implemented method includes detecting one or more items for purchase associated with the first user, and recognizing a second user paired with the first user. The computer-implemented method further includes determining one or more additional items to present to the second user, based on one or more of the following: the detected one or more items already selected by the first user, one or more item requirements of the second user, and current pricing and available promotions. The computer-implemented method further includes presenting the determined one or more additional items to the second user.

Abstract: A method can include obtaining personal data of a user and generating, based at least in part on the personal data of the user, a taste profile of the user. The taste profile can include a set of food characteristics that corresponds to one or more food preferences of the user. The method can include obtaining contextual data that corresponds to a location of the user. The method can include generating, based at least in part on the taste profile and the contextual data, a food recommendation. The food recommendation can include a predicted food preference of the user. The method can include transmitting the food recommendation to the user.

Abstract: Systems, methods and/or software where a separate image repository server (IRS) is created and maintained in each and every network and/or subnet segment that includes a destination server associated with the managed pool. Also, when a given virtual image is provisioned to a given destination server then the present invention preferably ensures that the IRS used as a source of the given virtual image is an IRS located in the same subnet and same network as the given destination server.