Multimodal Algorithmic Reasoning Workshop

Large AI frameworks have been increasing in their data modeling abilities at an ever more vigor in recent times, with compelling applications emerging frequently, many of which may even appear to challenge human intelligence. Yet despite such impressive performance, there remain open questions about whether these models include the foundations of general intelligence, or whether they perform these tasks without human-like understanding. This necessitates development of better tools for assessing these models in tandem with developing the models themselves. This workshop focuses on the topic of multimodal algorithmic reasoning, where an agent needs to assimilate information from multiple modalities towards deriving reasoning algorithms for complex problem solving. In the last year, we have seen rapid advances in AI capabilities that better bridge across modalities, bringing both optimism about superhuman capabilities and skepticism about the limits of current approaches. Through talks from outstanding researchers and faculty, we hope to dive deep into this exciting topic at the intersection of theory, multimodal learning and cognitive science to understand what we have achieved thus far in machine intelligence and what we are lacking in relation to the human way of thinking, towards finding the missing rungs on the ladder to truly intelligent reasoning.