Real-time identification of fact hallucinations in artificial intelligence (AI)

A non-transitory computer-readable media in an artificial intelligence (AI) validation server, implemented at least partially in hardware, when executed by a processor, for real-time identification of fact hallucinations in query results produced by AI, the method comprising the steps of:

• receiving, in real-time, an AI query response processed by an AI module using a neural model as an input, wherein the AI query response involves at least two facts;
• performing real-time verification of the AI query response by locating and retrieving compressed blocks from a token database having word-level similarity to the AI query response, by tokenizing data of the AI query response, wherein word-level similarity is computed from a weighted sum of Euclidian vector distances, by tokenizing data of the AI query response, wherein tokenizing comprises retrieving Kaggle tokenIDs associated with one or more words of the query response;
• comparing the AI query response to one or more tokenized facts of the compressed blocks at a data level, wherein comparing includes computing a similarity score of a vector derived from the tokenized query response to one or more vectors derived from the one or more tokenized facts;
• responsive to a verification result failing to meet a similarity score threshold, determining that a hallucination exists in the AI query response and taking a policy-based action on the AI query response;
• and
• responsive to the verification result meeting the similarity threshold, allowing the AI query response to proceed.

An artificial intelligence (AI) validation server, for real-time identification of hallucinations in query results produced by AI, the AI validation server:

• a processor;
• a network gateway communicatively coupled to the processor and to the data communication network;
• and
• a memory communicatively coupled to the processor and storing modules, comprising:
• an API module configured to receive, in real-time, a query response processed by an AI module using a neural model as an input, wherein the AI query response involves at least two facts;
• a sentence retrieval module configured to perform real-time verification of the AI query response by locating and retrieving compressed blocks from a token database having word-level similarity to the AI query response, by tokenizing data of the AI query response, wherein word-level similarity is computed from a weighted sum of Euclidian vector distances, by tokenizing data of the AI query response, wherein tokenizing comprises retrieving Kaggle tokenIDs associated with one or more words of the query response;
• a sentence score module configured to compare the AI query response to one or more tokenized facts of the compressed blocks at a data level, wherein comparing includes computing a similarity score of a vector derived from the tokenized query response to one or more vectors derived from the one or more tokenized facts,
• wherein the sentence scoring module is configured to, responsive to a verification result failing to meet a similarity score threshold, determine that a hallucination exists in the AI query response;
• and
• a veracity policy module configured to, responsive to the verification result failing, take a policy-based action on the AI query response,
• wherein responsive to the verification result meeting the similarity threshold, allow the AI query response to proceed.