Seekr Technologies, Inc.

Robin J Clark

Stefanos Poulis

Patrick C Condo

Diego A Mesa

Andrew J Bauer

Ali Taleb Zadeh Kasgari

A system and method for explaining and contesting outcomes of AI models, such as generative AI models, provides a desired explanation with desired explanation properties and provides a contestability feature. The system and method may also provide a remediation process when an AI model response is contested.

System and method for explaining and contesting outcomes of generative AI models with desired explanation properties

A question and answer (QA) pairs generation system and method uses an agentic workflow system and method to align 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.

Question answer (QA) pair generation using agentic workflow system and method that aligns artificial intelligence model with domain-specific principles

An agentic workflow system and method generate question and answer pairs and prompts that may be used to 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 also generate aligning processes that may be used to 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.

Agentic workflow system and method for generating synthetic data for training or post training artificial intelligence models to be aligned with domain-specific principles

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.

Search system and method having civility score

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.

Search system and method having quality scoring

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.

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Vienna, VA, United States of America

Robin J Clark