👉 In 2019, researchers from the University of Washington and Google DeepMind made headlines by attempting to create a general-purpose computer capable of performing any computational task, akin to human cognitive abilities. This effort, known as the "Millennium Prize Challenge," aimed to solve the Turing Test by building a machine that could understand, learn, and apply knowledge across diverse domains without explicit programming for each task. The project involved developing a new architecture called the Liquid Time-Constant Network (LTC), which combined elements of recurrent neural networks and attention mechanisms, and it successfully passed a series of increasingly complex benchmarks. However, achieving true general intelligence remains an elusive goal, as the task requires not just computational power but also a deep understanding of human cognition and the ability to generalize across vastly different contexts.
