AMP AI DO NOT EXPERIMENT

Brand Owner Address Description
AMP.AI: DON'T EXPERIMENT, JUST OPTIMIZE. Scaled Inference, Inc. 375 Forest Ave. Palo Alto CA 94301 AMP.AI: DO NOT EXPERIMENT, JUST OPTIMIZE.;Software as a service (SaaS) services featuring artificial intelligence and machine learning software for use in the optimization of key product, marketing, and business metrics; software as a service (SaaS) services featuring software for use in data analytics, artificial intelligence and machine learning, specifically for use in web site optimization, mobile application optimization, and software optimization; software as a service (SaaS) services featuring software for data analytics, anomaly detection, and recommendation and decision support based on data analytics and compilation, data mining, knowledge management and research, business process and data optimization, automation of predictive analytic processes, optimization of predictive analytic business decisions, business intelligence information gathering and analysis, forecasting and reporting of possible predictive outcomes, application of company and market data and data analytics, accounting and financial reporting and analysis, budgeting, enterprise management, data extraction, data monitoring, statistical compilation of market data, economic forecasting, market analysis, personalization and contextualization of user experiences and other elements of a company website, application or other software or platform, and optimization of company key performance indicators and business metrics; providing information, advice and consultancy in the fields of artificial intelligence and machine learning;
 

Where the owner name is not linked, that owner no longer owns the brand

    
Technical Examples
  1. Methods and apparatus, including computer program products implement techniques for processing experimental data according. An input specifies a set of variable definitions according to a variable definition template for defining a set of variables of a plurality of variable types usable in experiments of a pre-defined experiment class. Data from an experiment of an experiment type is received. A first representation of the data is stored in a format defined according to the plurality of variable types. A second representation of the data, derived from the first representation, is presented in a format defined according to the set of variable definitions. The variable definition template is referenced in the pre-defined experiment class. The data includes a plurality of values corresponding to variables defined in the set of variable definitions.