Abstract: A highly efficient, scalable, and adaptable framework suitable for modern Big Data processing challenges in cloud-based environments. The framework preferably leverages a scale-up before scale-out paradigm that prioritizes scaling up individual nodes (e.g., with high-core-count processors) before scaling out across multiple nodes. In addition, preferably the framework moves data to compute nodes, e.g., utilizing high-bandwidth cloud storage networks for efficient data transfer. Further, the framework preferably employs specialized primitives optimized for specific Big Data processing tasks, particularly for collations, sorts, and shuffles. Finally, framework utilizes optimized libraries for a small number of file formats.

Abstract: A generative AI process that preferably employs various LLMs to collaborate on a prompt in order to return a desirable response. This process uses prompt engineering in a chain approach to allow different LLMs to contribute to or modify an existing answer until a consensus is reached. By integrating multiple models (or instances of a single model) within the generation pipeline, the process ensures the accuracy and relevance of output, significantly enhancing the reliability of AI-generated content.

Abstract: A computerized system and techniques facilitate the monitoring and management of online behaviorally-targeted advertising. In certain embodiments, electronic notifications related to advertising practices of members of an online advertising ecosystem are presented to users based on the discovery of elements of online content aimed at delivering targeted advertising messages to viewers of the content.

Abstract: Methods and apparatus, including computer program products, for optimization of yield for advertising inventory. A method includes, in a network of interconnected computers, sending a request for a file from a browser residing on a user system to a publisher server, receiving the requested file from the publisher server, the requested file including instructions for the browser to request a site file from a rules server, receiving the site file in the browser, the site file including rules for deciding whether an advertising impression is desired, rules for valuing the advertising impression, and browser executable code that applies and evaluates the rules, executing the browser executable code to evaluate the rules from the site file which determine if one or more signals should be attached to an advertisement request, and selecting an advertisement from a network ad server based on a signal received with the advertisement request from the browser.

Abstract: A computerized system and techniques facilitate the monitoring and management of online behaviorally-targeted advertising. In certain embodiments, electronic notifications related to advertising practices of members of an online advertising ecosystem are presented to users based on the discovery of elements of online content aimed at delivering targeted advertising messages to viewers of the content.

Abstract: A computerized system and techniques facilitate the monitoring and management of online behaviorally-targeted advertising. In certain embodiments, electronic notifications related to advertising practices of members of an online advertising ecosystem are presented to users based on the discovery of elements of online content aimed at delivering targeted advertising messages to viewers of the content.

Abstract: A method includes, in a server residing in a network of interconnected computers, receiving user data, dissecting the received user data into a plurality of key/value pairs, iterating through the plurality of key/value pairs, generating a new data structure in the memory of the server for each key/value pair that do not exist, inserting a UserID into a set associated for a specific key/value pair, storing the key/value sets, and destroying the received user data.

Abstract: A method and system for attributing activity to a user includes sharing information with an analytics server while attributes and a user profile cannot be tracked back to the original user from the analytics server. A temporary ID included in the shared information is destroyed, thus eliminating any trace back.

Abstract: A method includes, in a server residing in a network of interconnected computers, receiving user data, dissecting the received user data into a plurality of key/value pairs, iterating through the plurality of key/value pairs, generating a new data structure in the memory of the server for each key/value pair that do not exist, inserting a UserID into a set associated for a specific key/value pair, storing the key/value sets, and destroying the received user data.

Abstract: A method and system for attributing activity to a user includes sending a first request for content from a browser executing on a consumer device to a first content provider. The first content provider responds to the request by generating a browser identifier and sending the browser identifier along with the requested content to the browser. Next, the user browser sends a second request for content to a second content provider. The user shares personal identification information with the second content provider. The second content provider contacts an attribute server to retrieve attributes associated with the user and generates a temporary ID. The second content provider shares the attributes and the temporary ID with an analytics server. The second content provider also instructs the browser to share the browser ID and the temporary ID with a user profile server.

Abstract: Methods and apparatus, including computer program products, for optimization of yield for advertising inventory. A method includes, in a network of interconnected computers, sending a request for a file from a browser residing on a user system to a publisher server, receiving the requested file from the publisher server, the requested file including instructions for the browser to request a site file from a rules server, receiving the site file in the browser, the site file including rules for deciding whether an advertising impression is desired, rules for valuing the advertising impression, and browser executable code that applies and evaluates the rules, executing the browser executable code to evaluate the rules from the site file which determine if one or more signals should be attached to an advertisement request, and selecting an advertisement from a network ad server based on a signal received with the advertisement request from the browser.

Abstract: A computerized system and techniques facilitate the monitoring and management of online behaviorally-targeted advertising. In certain embodiments, electronic notifications related to advertising practices of members of an online advertising ecosystem are presented to users based on the discovery of elements of online content aimed at delivering targeted advertising messages to viewers of the content.