Introduction

ChatGPT, or the underlying large language models (LLMs) today, are able to generate contextualized responses given a prompt.

As a next step in the LLM evolution, we expect the responses to be more and more personalized with respect to the persona, conversation history, current conversation context and sentiment of the end-users.

The key benefits of LLM personalization include:

• Personalized responses: The Gen AI solution adapts its language, tone, and complexity based on the user it is interacting with. This ensures that the conversation is more aligned with the user’s expectations and communication style.
• Conversation context: The Gen AI solution is aware of the user’s typical use cases, preferences, and history, allowing it to provide more contextually relevant and personalized responses.
• Content customization: The Gen AI solution can prioritize or highlight different features, or types of content, based on the user’s needs, making the interaction more efficient and user-friendly.
• Proactive Assistance: The Gen AI solution anticipates the needs of different users and offers proactive suggestions, resources, or reminders tailored to their specific profiles or tasks.

In a previous article [1], we wrote about designing a use-case based evaluation strategy…