Abstract: An artificial intelligence (AI) job recommender system and methods implement neural network machine learning by generating and utilizing actual and synthetic training data to identify, learn, and apply latent job-to-job transition information and trends to improve job recommendations. The AI job recommender system and method represent technological advances that, for example, identify data representations, identify multiple instances of latent information in actual data, develop synthetic training data, create a directed graph from latent, directional information, embed the directed graph into a vector space, and apply machine learning algorithms to technologically advance and transform a machine into a specialized machine that learns and improves job recommendations across the vector space.

Abstract: A multiple platform, multiple creative testing system and method implement and utilize devices and processes for managing and implementing testing of multiple creatives across multiple independent online platforms. The system and method enable a provider of creatives to perform testing of multiple creatives, such as A/B testing, across multiple online platforms with an A test targeting a control group of targeted individuals and an independent B test concurrently targeting a disjoint test group of targeted individuals across multiple online platforms. The system and method accomplish testing through concurrently using two independent targeted tests utilizing separate creatives to disjoint groups of targeted individuals across multiple online platforms.

Abstract: An artificial intelligence (AI) job recommender system and methods implement neural network machine learning by generating and utilizing actual and synthetic training data to identify, learn, and apply latent job-to-job transition information and trends to improve job recommendations. The AI job recommender system and method represent technological advances that, for example, identify data representations, identify multiple instances of latent information in actual data, develop synthetic training data, create a directed graph from latent, directional information, embed the directed graph into a vector space, and apply machine learning algorithms to technologically advance and transform a machine into a specialized machine that learns and improves job recommendations across the vector space.