Understanding and Mitigating AI Hallucinations: Insights and our Experience

The nuances of large language models (#LLMs) like #GPT-3.5/4/4o are crucial to grasp. These models predict words based on statistical patterns rather than factual data, often resulting in #hallucinations—plausible but false responses. While advanced techniques can reduce hallucinations, they can't eliminate them entirely. Thus, managing expectations and understanding the probabilistic nature of LLMs is key.

First Takeaway:

Always review and correct any content generated with #ChatGPT. No matter how good you are at prompting, your content needs to be anchored in your knowledge, ideas, and the message you want to deliver. ChatGPT or similar models can only assist you.

Our experience with our Enterprise Conversational #GenerativeAI Platform, #INUI, which can powered by specific #enterpriseknowledgebase (s), offered us valuable insights. It allows the creation of multiple #Specialized #AIAgents tailored for specific roles (e.g., tech support, sales, reception, marketing, Enterprise Information Retriever, etc.). Amongst others, two key elements are essential in configuring an INUI conversational AI agent:

1. The #knowledgebase it uses and
2. The #persona it interacts with.

The Story:

We were preparing our first INUI Proof of Concept (POC) for on of our Clients, a law firm. Initially, we fed the knowledge base with the Swiss Civil Code, Criminal Code, and other legal documents. The client wanted an AI chatbot to interact with their potential (private) customers, who typically aren’t versed in legal terminology. The outcome was disastrous; the AI agent was hallucinating most of the time.

In our second attempt, we scraped the client’s website, which fortunately contained a rich knowledge base (a large number of blog articles, and other content), explaining legal topics in "normal people's language".

This time, BINGO. The result was fantastic. The quality of the responses was outstanding, providing clear and helpful responses that resonated with the target audience.

Insights and Solutions:

1. Align Knowledge Base with Target Audience: Ensure the Conversational AI Agent’s knowledge base matches the communication style and vocabulary of the target persona, to reduce hallucinations.
2. Continuous Review and Correction: Regularly review and correct AI-generated content to maintain accuracy and relevance.
3. Tailored AI Solutions: Customize AI agents for specific business needs to enhance performance and user satisfaction.

REVARTIS ' expertise in shaping, orchestrating, and executing strategic AI Roadmaps, and tailoring affordable AI solutions to specific business needs can be a game-changer.

Don’t hesitate to reach out to me or to our CMO Sylvain Berrier . We will be happy to discuss with you, your value-driven and cost-effective roadmap.

Writing this article was inspired by the article authored by Will Douglas Heaven , titled "Why does AI hallucinate?", and published on MIT Technology Review . It reminded me our experience at REVARTIS with our platform #INUI.

Thank you Will Douglas Heaven for the inspiration.