J.A.R.V.I.S. LLM
The JARVIS project involve the use of LLM with a focus on personalization. Indeed, the idea is to investigate the possibility of designing an Digital Agent able to use Adaptive Personalization.
The AI needs to continuously learn from the user’s inputs and feedback to improve and adjust suggestions, making the experience feel tailored and unique.
LLMs could adjust their tone, style, and even choice of content based on a user’s past interactions. For instance, they might recognize if a user prefers concise responses, casual language, or specific domains of knowledge (e.g., a technical user might prefer more detail in scientific explanations). Models could incorporate memory modules (Memory Mechanisms) that help them retain important context from previous interactions, enabling more continuous and coherent conversations. However, memory retention must be handled carefully to avoid storing unnecessary or sensitive information. Research could focus on enabling LLMs to create more sophisticated user models that evolve as user preferences change over time, dynamically updating without needing explicit user input or resetting preferences (Long-Term User Models).
Goal
The potential impact of this research project is significant, as the development of a personalized digital assistant, powered by LLMs, has the potential to revolutionize the way we interact with technology, and to make our daily lives more efficient and enjoyable.