Chatbot Platform Using Language Model Semantic Embeddings
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Solution Overview
Problem
Existing chatbot implementations require significant manual configuration to identify user intents and generate responses, consuming unnecessary computing and network resources.
Innovation Solution
A specialized chatbot platform uses language models to programmatically determine answers from semantically similar documents in a knowledge base, reducing the need for manual curation and updating of intents and responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual configuration is used to identify user intents and generate responses, then chatbot functionality can be implemented, but computing and network resources are consumed unnecessarily
Solution Approach 1:
The system enables self-service by allowing the chatbot to automatically configure itself using language models to identify user intents and generate responses from knowledge base documents, eliminating the need for manual configuration and reducing computing resource consumption
Solution Approach 2:
The patent replaces manual mechanical configuration processes with automated language model-based systems that can programmatically determine user intents and generate appropriate responses, thereby reducing the need for human intervention and optimizing resource usage
2Reliability
If manual curation and updating of intents and responses is performed, then chatbot accuracy can be maintained, but the number of manual operations increases
Solution Approach 1:
The chatbot system performs self-updating by automatically learning from new interactions and knowledge base documents, maintaining response accuracy without requiring manual curation operations
Solution Approach 2:
The system performs preliminary processing of knowledge base documents and intent identification in advance, so that when queries are received, the chatbot can quickly retrieve and generate responses without requiring real-time manual intervention
3Extent of automation
If language models are used to programmatically determine answers from knowledge base documents, then manual operations are reduced, but computation costs and latency may be affected
Solution Approach 1:
The system performs preliminary processing by pre-processing knowledge base documents into structured formats and pre-computing relevant information, so that during actual query processing, the language model can quickly retrieve and generate answers with reduced latency
Solution Approach 2:
The system extracts only the most relevant information from knowledge base documents using the language model, rather than processing entire documents, thereby reducing computation time and latency while maintaining answer accuracy
Data Source
AI summary
Technology is disclosed for programmatically implementing a chatbot that utilizes a language model to determine answers from a knowledge base or external resource. In one implementation, a conversation with a user is accessed. A representation summarizing the conversation is generated based on applying the conversation to a language model. An embedding corresponding to the representation is generated. A response is determined based on computing similarity of the embedding corresponding to the representation to embeddings corresponding to sentences of documents in a knowledge base. A corresponding representation of the response is communicated to the user. In one implementation, in response to a user input received in the conversation, an external resource, such as a third-party website or application is accessed and chatbot output is generated in response to a user input in a chat session.