Abstract: A scoring system and method identifies personal attacks in a piece of audio content and generates a civility score for the piece of audio content that can differentiate between personal attacks and vernacular/casual banter. The piece of audio content may be a podcast.

Abstract: A scoring system and method identifies personal attacks in a piece of audio content and generates a civility score for the piece of audio content that can differentiate between personal attacks and vernacular/casual banter. The piece of audio content may be a podcast.

Abstract: A search system and method generates a quality score and/or a political lean score for a piece of content and returns the one or more scores to the user when returning search results from a query to the user. In one embodiment, the system and method may use artificial intelligence/machine learning to determine the one or more scores for each piece of content.

Abstract: A scoring system and method identifies personal attacks in a piece of audio content and generates a civility score for the piece of audio content that can differentiate between personal attacks and vernacular/casual banter. The piece of audio content may be a podcast.

Abstract: A search system and method generates a quality score and/or a political lean score for a piece of content and returns the one or more scores to the user when returning search results from a query to the user. In one embodiment, the system and method may use artificial intelligence/machine learning to determine the one or more scores for each piece of content.

Abstract: A system and method aligns generative artificial intelligence (a large language model (LLM) or a large multimodal model (LMM) with the principles of a specific domain so that the generative artificial intelligence is better able to respond to a user query in the specific domain. The system and method may post-train an already trained generative artificial intelligence system or fine tune the training of the generative artificial intelligence system to align that generative artificial intelligence system with the principles of the specific domain. The system and method may be used to align the generative artificial intelligence system to a plurality of different domains.

Abstract: A search system and method generates a quality score and/or a political lean score for a piece of content and returns the one or more scores to the user when returning search results from a query to the user. In one embodiment, the system and method may use artificial intelligence/machine learning to determine the one or more scores for each piece of content.

Abstract: A system and method aligns generative artificial intelligence (a large language model (LLM) or a large multimodal model (LMM) with the principles of a specific domain so that the generative artificial intelligence is better able to respond to a user query in the specific domain. The system and method may post-train an already trained generative artificial intelligence system or fine tune the training of the generative artificial intelligence system to align that generative artificial intelligence system with the principles of the specific domain. The system and method may be used to align the generative artificial intelligence system to a plurality of different domains.

Abstract: One or more techniques and/or systems are provided for implementing a pipeline used to generate, train, test, and implement a document scoring model for assigning document scores to documents. Features from various sources are combined to create a joined page level feature set, a joined domain level feature set, and a host level feature set. Numerical features and content features are extracted from ground truth documents and random documents. The numerical features are joined with the joined feature sets to create a set of joined features. The document scoring model is trained using the set of joined features and a training technique. A document is scored with a document score using the document scoring model based upon the content features and the set of joined features with document scores obtained during training.

Abstract: A scoring system and method identifies personal attacks in a piece of audio content and generates a civility score for the piece of audio content that can differentiate between personal attacks and vernacular/casual banter. The piece of audio content may be a podcast.

Abstract: One or more techniques and/or systems are provided for implementing a pipeline used to generate, train, test, and implement a document scoring model for assigning document scores to documents. Features from various sources are combined to create a joined page level feature set, a joined domain level feature set, and a host level feature set. Numerical features and content features are extracted from ground truth documents and random documents. The numerical features are joined with the joined feature sets to create a set of joined features. The document scoring model is trained using the set of joined features and a training technique. A document is scored with a document score using the document scoring model based upon the content features and the set of joined features with document scores obtained during training.