Abstract: Methods and apparatuses that apply a hierarchical-decomposition reinforcement learning technique to train one or more AI objects as concept nodes composed in a hierarchical graph incorporated into an AI model. The individual sub-tasks of a decomposed task may correspond to its own concept node in the hierarchical graph and are initially trained on how to complete their individual sub-task and then trained on how the all of the individual sub-tasks need to interact with each other in the complex task in order to deliver an end solution to the complex task. Next, during the training, using reward functions focused for solving each individual sub-task and then a separate one or more reward functions focused for solving the end solution of the complex task. In addition, where reasonably possible, conducting the training of the AI objects corresponding to the individual sub-tasks in the complex task, in parallel at the same time.

Abstract: An AI database hosted on cloud platform is configured to cooperate with a search engine and an AI engine. The AI database stores and indexes trained AI objects and its class of AI objects have searchable criteria. The AI database cooperates with the search engine to utilize search criteria supplied from a user, from either or both 1) via scripted software code and 2) via data put into defined fields of a user interface. The search engine utilizes the search criteria in order for the search engine to retrieve one or more AI data objects that have already been trained as query results. The AI database is coupled to an AI engine to allow any of reuse, reconfigure ability, and recomposition of the one or more trained AI data objects from the AI database into a new trained AI model.

Abstract: An AI database hosted on cloud platform is configured to cooperate with a search engine and an AI engine. The AI database stores and indexes trained AI objects and its class of AI objects have searchable criteria. The AI database cooperates with the search engine to utilize search criteria supplied from a user, from either or both 1) via scripted software code and 2) via data put into defined fields of a user interface. The search engine utilizes the search criteria in order for the search engine to retrieve one or more AI data objects that have already been trained as query results. The AI database is coupled to an AI engine to allow any of reuse, reconfigure ability, and recomposition of the one or more trained AI data objects from the AI database into a new trained AI model.

Abstract: Methods and apparatuses that apply a hierarchical-decomposition reinforcement learning technique to train one or more AI objects as concept nodes composed in a hierarchical graph incorporated into an AI model. The individual sub-tasks of a decomposed task may correspond to its own concept node in the hierarchical graph and are initially trained on how to complete their individual sub-task and then trained on how the all of the individual sub-tasks need to interact with each other in the complex task in order to deliver an end solution to the complex task. Next, during the training, using reward functions focused for solving each individual sub-task and then a separate one or more reward functions focused for solving the end solution of the complex task. In addition, where reasonably possible, conducting the training of the AI objects corresponding to the individual sub-tasks in the complex task, in parallel at the same time.

Abstract: An AI database hosted on cloud platform is configured to cooperate with a search engine and an AI engine. The AI database stores and indexes trained AI objects and its class of AI objects have searchable criteria. The AI database cooperates with the search engine to utilize search criteria supplied from a user, from either or both 1) via scripted software code and 2) via data put into defined fields of a user interface. The search engine utilizes the search criteria in order for the search engine to retrieve one or more AI data objects that have already been trained as query results. The AI database is coupled to an AI engine to allow any of reuse, reconfigure ability, and recomposition of the one or more trained AI data objects from the AI database into a new trained AI model.

Abstract: Modular die or mold assemblies comprise a platform, and at least one die or mold unit which is releaseably connected to the platform. The invention permits rapid changing of molds or dies, especially in the manufacture of detergent bars, such as soap bars. Surface ornamentation such as logos can be imparted to the detergent bars either directly from the stamping surface of the dies, from the stamping surface of the dies through an elastomeric lining, or from the surface of the elastomeric lining; in the latter case the indicia is imparted by a mold used to prepare the lining. The modular molds may be used where it is desired to coat the dies with elastomer, particularly where logos are imparted to the elastomeric layer, and where it may be desirable to change the logos, e.g., by changing the modular mold units.

Abstract: A device for stamping a detergent bar, i.e. a bar comprising soap, a synthetic detergent active or a mixture thereof, includes a die. The die has at least one bar stamping surface provided with at least one elastomeric coating which includes a conductive filler such as stainless steel powder. Good release of the detergent bars from the die is possible particularly when the dies are chilled. Use of the conductive filler facilitates chilling of the dies.

Abstract: A device for stamping a detergent bar, i.e. a bar comprising soap, a synthetic detergent active or a mixture thereof, includes a die. The die has at least one bar stamping surface provided with at least one elastomeric coating which includes a conductive filler such as stainless steel powder. Good release of the detergent bars from the die is possible particularly when the dies are chilled. Use of the conductive filler facilitates chilling of the dies.

Abstract: A device for stamping a detergent bar, i.e. a bar comprising soap, a synthetic detergent active or a mixture thereof, includes a die. The die has at least one bar stamping surface provided with at least one elastomeric coating and includes an edge for delaying tearing of the elastomeric coating. Good release of the detergent bars from the die is possible without chilling of the dies. Use of the edge increases the useful life of the coating.

Abstract: A device for stamping a detergent bar, i.e. a bar comprising soap, a synthetic detergent active or a mixture thereof, includes a die half and a release fluid reservoir. The die is porous so that at least one bar stamping surface has pores through which a release fluid may be to facilitate clean release of the detergent bar cleanly after stamping. Good release of the detergent bars from the die is expected without or with reduced chilling of the dies.

Abstract: A stamping die includes a substrate stamping surface comprising a base matrix of open structure having a coating of elastomeric material applied thereon. The resulting surface is a composite comprising predominantly elastomer having matrix protruding through the elastomer in places.

Abstract: A device for controlling fluid or liquid flow which comprises: a.) a metallic fill tube which is tapered at one end and has an opening at said end and has an internal profile and an outer profile; b.) a metallic tip and elastomeric assembly within said metallic fill tube; and which forms a seal with the internal profile of said fill tube upon contact with said internal profile; c.) a nozzle which at one end is attached to said metallic tip; and wherein the opening of said metallic fill tube has approximately the same radius as the metallic tip and elastomeric assembly, is described.