The field of digital representation and brain-inspired intelligence is witnessing a significant shift towards innovative and alternative approaches. Researchers are exploring new number systems, such as the Adaptive Base Representation Theorem, that can potentially replace traditional binary systems. Additionally, brain-inspired methods like Grid-like Code Quantization are being developed to compress observation-action sequences into discrete representations. These advancements have the potential to enable more efficient and resilient positioning, navigation, and timing systems. Furthermore, the integration of human intelligence and brain-inspired intelligence is being investigated to enhance unmanned systems' capabilities in demanding missions. Noteworthy papers include: Adaptive Base Representation Theorem, which introduces a novel number system that offers a structured alternative to the binary number system. Vector Quantization in the Brain: Grid-like Codes in World Models, which proposes a brain-inspired method for compressing observation-action sequences into discrete representations.