Organised by NUSAiL, join Assistant Professor Dorsa Sadigh, Computer Science at Stanford University, as she discusses the problem of interactive learning by discussing how we can actively learn objective functions from human feedback capturing their preferences and sharing some preliminary results on how large models can be effective pattern machines that can identify patterns in a token invariant fashion and enable pattern transformation, extrapolation, and even show some evidence of pattern optimization for solving control problems.