说明:
Kindly read the Instructions before installing the software.
Aibase is optimized for structuring thoughts and ideas in an efficient information space, leading to many positive effects on learning, creative work, task solving and project management. An efficient information space relieves the human memory in many ways. Computer memory is typically used as long-term memory. But optimized information spaces like Aibase also adapt to the specialties of the human short-term memory: They cluster related information visibly, and by links and notes. They emphasize information by colors. Fast navigation, automatic document-creation and single-key operations give you more time to focus on your information. You can quickly break down complex information into trees for better understanding. Aibase allows you to solve tasks with largest complexity. Such a task can grow up to thousands of linked documents (by help of automatic document-creation). The more complex a task, the higher the demands on the human memory. And the reverse: If the human memory is relieved, then the solvable complexity, quality and security increases. Users who spend much time with Aibase will even find that they never reach limits to understand new complex information.
Aibase already optimizes well-known information structures: trees (collapsible), tables, shapes, equations, animations, hyperlinks, notes. These structures represent a solid platform for going into information spaces with more complexity. Future versions of Aibase will optimize further and will add many scientific structures, so we can interactively explore science in many dimensions (2D, 3D, and time). Aibase's main goal is to build a multilevel platform for knowledge-exploration. Higher levels (science) build on lower levels (visualization, simple math). Understanding a problem depends on the visualization of carefully chosen perspectives. The goal is to explore knowledge multiple times more efficient than with traditional methods. Experienced users are fascinated by the gained ability to understand complex or unknown knowledge worlds; computer-empowered methods are the indispensable basis for this new level.
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