Abstract: Based on user work product and underlying source data information, automatic generation of artificial intelligence (AI) topology defining operations for future AI generations each mimicking the approach and format of the user work product. Hosting services supports user interaction to gather work product examples and source data information, and also supports automatic identification of: (i) frames or elements of user work product; (ii) primary AI and support processing nodes to service content generation for each frame (or element); (iii) cross frame topology influence linkages; (iv) pattern data associated with each frame; and (v) AI and support processing based topologies for each frame. AI and support processing nodes being selected from a plurality of available nodes provided by the hosting service. Insufficient performance of such available nodes drives custom, automatic training of AI nodes and/or creation of support processing nodes with and without auto programming assist.

Abstract: Based on user work product and underlying source data information, automatic generation of artificial intelligence (AI) topology defining operations for future AI generations each mimicking the approach and format of the user work product. Hosting services supports user interaction to gather work product examples and source data information, and also supports automatic identification of: (i) frames or elements of user work product; (ii) primary AI and support processing nodes to service content generation for each frame (or element); (iii) cross frame topology influence linkages; (iv) pattern data associated with each frame; and (v) AI and support processing based topologies for each frame. AI and support processing nodes being selected from a plurality of available nodes provided by the hosting service. Insufficient performance of such available nodes drives custom, automatic training of AI nodes and/or creation of support processing nodes with and without auto programming assist.

Abstract: Based on user work product and underlying source data information, automatic generation of artificial intelligence (AI) topology defining operations for future AI generations each mimicking the approach and format of the user work product. Hosting services supports user interaction to gather work product examples and source data information, and also supports automatic identification of: (i) frames or elements of user work product; (ii) primary AI and support processing nodes to service content generation for each frame (or element); (iii) cross frame topology influence linkages; (iv) pattern data associated with each frame; and (v) AI and support processing based topologies for each frame. AI and support processing nodes being selected from a plurality of available nodes provided by the hosting service. Insufficient performance of such available nodes drives custom, automatic training of AI nodes and/or creation of support processing nodes with and without auto programming assist.

Abstract: Based on user work product and underlying source data information, automatic generation of artificial intelligence (AI) topology defining operations for future AI generations each mimicking the approach and format of the user work product. Hosting services supports user interaction to gather work product examples and source data information, and also supports automatic identification of: (i) frames or elements of user work product; (ii) primary AI and support processing nodes to service content generation for each frame (or element); (iii) cross frame topology influence linkages; (iv) pattern data associated with each frame; and (v) AI and support processing based topologies for each frame. AI and support processing nodes being selected from a plurality of available nodes provided by the hosting service. Insufficient performance of such available nodes drives custom, automatic training of AI nodes and/or creation of support processing nodes with and without auto programming assist.

Abstract: Host services in an artificial intelligence (AI) infrastructure supporting a visual creation interface of multi-node AI based topologies in segments and partitions to service various overall AI objectives across multiple host, creator, user and third party devices and systems. Training of AI nodes, testing, automatic topology assessment and adjustment is provided. Secure interaction between topology partitions supports privacy concerns. Influencers and celebrities provide personal data to AI topologies to automatically generate topology node configurations, training data and datasets that can be swapped into any topology for those addressing host's digital rights management compensation and restrictions. Host services provide platforms for sharing created AI topologies, AI generations based on such AI topologies, and celebrity and influencer elements thereof.

Abstract: Host services in an artificial intelligence (AI) infrastructure supporting a visual creation interface of multi-node AI based topologies in segments and partitions to service various overall AI objectives across multiple host, creator, user and third party devices and systems. Training of AI nodes, testing, automatic topology assessment and adjustment is provided. Secure interaction between topology partitions supports privacy concerns. Influencers and celebrities provide personal data to AI topologies to automatically generate topology node configurations, training data and datasets that can be swapped into any topology for those addressing host's digital rights management compensation and restrictions. Host services provide platforms for sharing created AI topologies, AI generations based on such AI topologies, and celebrity and influencer elements thereof.

Abstract: Host services in an artificial intelligence (AI) infrastructure supporting a visual creation interface of multi-node AI based topologies in segments and partitions to service various overall AI objectives across multiple host, creator, user and third party devices and systems. Training of AI nodes, testing, automatic topology assessment and adjustment is provided. Secure interaction between topology partitions supports privacy concerns. Influencers and celebrities provide personal data to AI topologies to automatically generate topology node configurations, training data and datasets that can be swapped into any topology for those addressing host's digital rights management compensation and restrictions. Host services provide platforms for sharing created AI topologies, AI generations based on such AI topologies, and celebrity and influencer elements thereof.

Abstract: Host services in an artificial intelligence (AI) infrastructure supporting a visual creation interface of multi-node AI based topologies in segments and partitions to service various overall AI objectives across multiple host, creator, user and third party devices and systems. Training of AI nodes, testing, automatic topology assessment and adjustment is provided. Secure interaction between topology partitions supports privacy concerns. Influencers and celebrities provide personal data to AI topologies to automatically generate topology node configurations, training data and datasets that can be swapped into any topology for those addressing host's digital rights management compensation and restrictions. Host services provide platforms for sharing created AI topologies, AI generations based on such AI topologies, and celebrity and influencer elements thereof.

Abstract: Host services in an artificial intelligence (AI) infrastructure supporting a visual creation interface of multi-node AI based topologies in segments and partitions to service various overall AI objectives across multiple host, creator, user and third party devices and systems. Training of AI nodes, testing, automatic topology assessment and adjustment is provided. Secure interaction between topology partitions supports privacy concerns. Influencers and celebrities provide personal data to AI topologies to automatically generate topology node configurations, training data and datasets that can be swapped into any topology for those addressing host's digital rights management compensation and restrictions. Host services provide platforms for sharing created AI topologies, AI generations based on such AI topologies, and celebrity and influencer elements thereof.

Abstract: Host services in an artificial intelligence (AI) infrastructure supporting a visual creation interface of multi-node AI based topologies in segments and partitions to service various overall AI objectives across multiple host, creator, user and third party devices and systems. Training of AI nodes, testing, automatic topology assessment and adjustment is provided. Secure interaction between topology partitions supports privacy concerns. Influencers and celebrities provide personal data to AI topologies to automatically generate topology node configurations, training data and datasets that can be swapped into any topology for those addressing host's digital rights management compensation and restrictions. Host services provide platforms for sharing created AI topologies, AI generations based on such AI topologies, and celebrity and influencer elements thereof.

Abstract: Host services in an artificial intelligence (AI) infrastructure supporting a visual creation interface of multi-node AI based topologies in segments and partitions to service various overall AI objectives across multiple host, creator, user and third party devices and systems. Training of AI nodes, testing, automatic topology assessment and adjustment is provided. Secure interaction between topology partitions supports privacy concerns. Influencers and celebrities provide personal data to AI topologies to automatically generate topology node configurations, training data and datasets that can be swapped into any topology for those addressing host's digital rights management compensation and restrictions. Host services provide platforms for sharing created AI topologies, AI generations based on such AI topologies, and celebrity and influencer elements thereof.

Abstract: Optional segmented generative AI (Artificial Intelligence) topologies with multiple AI type outputs participate to serve overall AI generation objectives. Multiple remote and local topology nodes within overall topology segments utilize pattern based influence along with both inner and inter segment influence to adapt as new generations occur, to maintain context and to address changing circumstances. Outside influence delivers such change notifications. AI output and input interface elements provide some such change notifications and provide alternatives to conventional driver based circuit architectures. Support processing nodes, discriminative AI elements, generative AI elements along with outside influence from input, output and communication circuity along with other outside interactions are arranged in sub-segments that are carried out to deliver generated pieces of a multimedia based objective.

Abstract: Optional segmented generative AI (Artificial Intelligence) topologies with multiple AI type outputs participate to serve overall AI generation objectives. Multiple remote and local topology nodes within overall topology segments utilize pattern based influence along with both inner and inter segment influence to adapt as new generations occur, to maintain context and to address changing circumstances. Outside influence delivers such change notifications. AI output and input interface elements provide some such change notifications and provide alternatives to conventional driver based circuit architectures. Support processing nodes, discriminative AI elements, generative AI elements along with outside influence from input, output and communication circuitry along with other outside interactions are arranged in sub-segments that are carried out to deliver generated pieces of a multimedia based objective.

Abstract: Optional segmented generative AI (Artificial Intelligence) topologies with multiple AI type outputs participate to serve overall AI generation objectives. Multiple remote and local topology nodes within overall topology segments utilize pattern based influence along with both inner and inter segment influence to adapt as new generations occur, to maintain context and to address changing circumstances. Outside influence delivers such change notifications. AI output and input interface elements provide some such change notifications and provide alternatives to conventional driver based circuit architectures. Support processing nodes, discriminative AI elements, generative AI elements along with outside influence from input, output and communication circuity along with other outside interactions are arranged in sub-segments that are carried out to deliver generated pieces of a multimedia based objective.

Abstract: Optional segmented generative AI (Artificial Intelligence) topologies with multiple AI type outputs participate to serve overall AI generation objectives. Multiple remote and local topology nodes within overall topology segments utilize pattern based influence along with both inner and inter segment influence to adapt as new generations occur, to maintain context and to address changing circumstances. Outside influence delivers such change notifications. AI output and input interface elements provide some such change notifications and provide alternatives to conventional driver based circuit architectures. Support processing nodes, discriminative AI elements, generative AI elements along with outside influence from input, output and communication circuitry along with other outside interactions are arranged in sub-segments that are carried out to deliver generated pieces of a multimedia based objective.

Abstract: Optional segmented generative AI (Artificial Intelligence) topologies with multiple AI type outputs participate to serve overall AI generation objectives. Multiple remote and local topology nodes within overall topology segments utilize pattern based influence along with both inner and inter segment influence to adapt as new generations occur, to maintain context and to address changing circumstances. Outside influence delivers such change notifications. AI output and input interface elements provide some such change notifications and provide alternatives to conventional driver based circuit architectures. Support processing nodes, discriminative AI elements, generative AI elements along with outside influence from input, output and communication circuitry along with other outside interactions are arranged in sub-segments that are carried out to deliver generated pieces of a multimedia based objective.

Abstract: A multi-node artificial intelligence topology adapts to service many different overall purposes. Support processing nodes, discriminative AI elements, generative AI elements along with input, output and communication circuitry along with other outside interactions provide the nodal basis for the overall topology. Therewithin, outputs of several nodes drive a single node which uses influence balancing to optimize its own output. Influence is delivered in feed forward and feed back manner. Segmented processing is provided where sections of an overall output goal is processed through the topology in segments, e.g., chapter by chapter of a novel, episode by episode, a full topology processing using internal cross node influence followed by a second full topology processing using both internal cross node and cross segment influence. Pseudo random templating providing constraints used to progress through segments to control an output flow.

Abstract: A multi-node artificial intelligence topology adapts to service many different overall purposes. Support processing nodes, discriminative AI elements, generative AI elements along with input, output and communication circuitry along with other outside interactions provide the nodal basis for the overall topology. Therewithin, outputs of several nodes drive a single node which uses influence balancing to optimize its own output. Influence is delivered in feed forward and feed back manner. Segmented processing is provided where sections of an overall output goal is processed through the topology in segments, e.g., chapter by chapter of a novel, episode by episode, a full topology processing using internal cross node influence followed by a second full topology processing using both internal cross node and cross segment influence. Pseudo random templating providing constraints used to progress through segments to control an output flow.

Abstract: A multi-node artificial intelligence topology adapts to service many different overall purposes. Support processing nodes, discriminative AI elements, generative AI elements along with input, output and communication circuitry along with other outside interactions provide the nodal basis for the overall topology. Therewithin, outputs of several nodes drive a single node which uses influence balancing to optimize its own output. Influence is delivered in feed forward and feed back manner. Segmented processing is provided where sections of an overall output goal is processed through the topology in segments, e.g., chapter by chapter of a novel, episode by episode, a full topology processing using internal cross node influence followed by a second full topology processing using both internal cross node and cross segment influence. Pseudo random templating providing constraints used to progress through segments to control an output flow.

Abstract: A multi-node artificial intelligence topology adapts to service many different overall purposes. Support processing nodes, discriminative AI elements, generative AI elements along with input, output and communication circuitry along with other outside interactions provide the nodal basis for the overall topology. Therewithin, outputs of several nodes drive a single node which uses influence balancing to optimize its own output. Influence is delivered in feed forward and feed back manner. Segmented processing is provided where sections of an overall output goal is processed through the topology in segments, e.g., chapter by chapter of a novel, episode by episode, a full topology processing using internal cross node influence followed by a second full topology processing using both internal cross node and cross segment influence. Pseudo random templating providing constraints used to progress through segments to control an output flow.