Reasoning is one of the most interesting, yet mysterious, abilities of our brain and Deep Learning models have long sought to mimic this unique gift of humanity efficiently. To address this challenge, Destiny investigates sequence-to-sequence models' capabilities on long-sequence reasoning such as recurrent and state space models. He aims to understand which efficient-driven choices to make to build optimized and simple architectures to enhance reasoning capabilities in Deep Learning.