Alessandro Cappelli

This talk argues that reinforcement learning (RL) is crucial for moving AI models, particularly large language models (LLMs), from pilot stages to production. The speaker posits that the common failure of GenAI pilots stems from the "myth of the last mile," where initial MVPs built on proprietary models or instruction fine-tuning lack systematic improvement pathways. RL, by its nature, allows for the mathematical integration of feedback, leading to more effective model steering and enabling scaled, cost-efficient, and faster deployments.