Abstract: A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.

Abstract: Systems, methods, and devices for human-machine interfaces for improving machine understanding and fulfillment of utterance-based requests provided via the interfaces. Multiple candidate understandings from multiple stages of a natural language processing flow are preserved for arbitration and choosing by an arbitrator that applies arbitration rules to the plurality of candidates and chooses a single candidate for initiation of a corresponding service. In an embodiment, the arbitrator uses a media content taste profile to choose a candidate understanding for initiation of a corresponding service.

Abstract: Systems, methods, and devices for human-machine interfaces for improving machine understanding and fulfillment of utterance-based requests provided via the interfaces. Multiple candidate understandings from multiple stages of a natural language processing flow are preserved for arbitration and choosing by an arbitrator that applies arbitration rules to the plurality of candidates and chooses a single candidate for initiation of a corresponding service. In an embodiment, the arbitrator uses a media content taste profile to choose a candidate understanding for initiation of a corresponding service.

Abstract: Systems, methods, and devices for human-machine interfaces for improving machine understanding and fulfillment of utterance-based requests provided via the interfaces. Multiple candidate understandings from multiple stages of a natural language processing flow are preserved for arbitration and choosing by an arbitrator that applies arbitration rules to the plurality of candidates and chooses a single candidate for initiation of a corresponding service. In an embodiment, the arbitrator uses a media content taste profile to choose a candidate understanding for initiation of a corresponding service.

Abstract: Methods of making an artificial leather substrate from leather waste (e.g., shavings, such as wet blue, and/or pulverized trim scrap) and products formed using the artificial leather substrate are disclosed. In one example, the artificial leather substrate comprises a composite web comprising leather waste mixed with a lightweight web, a lightweight web atop the composite web, and another lightweight web atop the first lightweight web. A method of making the artificial leather substrate includes the steps of mixing one or more fiber components, leather shavings, and/or pulverized leather trim scrap to form the composite web; needle punching the composite web; and bonding the composite web.

Abstract: Methods of making an artificial leather substrate from leather waste (e.g., shavings, such as wet blue, and/or pulverized trim scrap) and products formed using the artificial leather substrate are disclosed. In one example, the artificial leather substrate comprises a composite web comprising leather waste mixed with a lightweight web, a lightweight web atop the composite web, and another lightweight web atop the first lightweight web. A method of making the artificial leather substrate includes the steps of mixing one or more fiber components, leather shavings, and/or pulverized leather trim scrap to form the composite web; needle punching the composite web; and bonding the composite web.