AI agents are a fast-developing domain that leverages Large Language Models (LLMs) to autonomously perform and refine tasks, mirroring human-like efficiency and adaptability. Within the AI agent domain, multi-agent collaboration has been promising domain in recent research to solve complex tasks through multiple AI agents collaboration or debating. The talk will cover most recent research conducted in fields like finance, software and medicine and understand how multi-agent frameworks can help complete complex tasks, 

This session delves into the critical factors that businesses must consider when selecting both the right models and infrastructure for effective Generative AI deployment. It covers key strategic decisions to ensure successful AI operationalization.

• Evaluating the specific requirements and constraints of each application to determine the most suitable model.

• Considering factors such as model complexity, data availability, and computational resources when making choices.

• Continuously monitoring model performance and adapting model selection strategies as AI technologies evolve.

• Assessing organizational needs and stakeholder concerns to determine the optimal infrastructure.

• Establishing clear communication channels between technical and business teams to align priorities.

• Developing a roadmap for implementation, iteratively evaluating progress and adjusting strategies accordingly.