Knowledge Engine based on Significant Experiences
- Significant Experiences
Significant Experiences(SEs) are regarded by us as the basic units of knowledge, like cells in biological creatures. Significant Experiences are like Ray Kurzweil’s “Qualia”(Consciousness Experiences). SEs have self-vote of importance and usefulness vote by others, which are like the weights in biological neural networks.
The basic relation btw knowledge is “containing”. Frame is the embodiment of such “containing” relation, it constructs life centers at the higher level and is capable to engage in large parallel computation and pattern recognition.
Tag establish connections btw knowledge (like synapses rewiring)
Tag Tree is to extract out abstract knowledge structure or patterns (we think it is better to use Life Centers instead of patterns) through SEs.
For a period of time, you can focus on working in a certain WorkingSet, which is a set of tags in KE.
When working with a lot of SEs, cache helps to store some SE ids temporarily.
Dynamic folders that retrieve SEs by pre-configured search terms.
Structured Knowledge on top of SEs
- Learning Areas
Learning Area is a large domain of learning, such as Software Programming. It automatically collects your SEs and structured knowledge in an area for knowledge display and discovery.
- Learning Groups
Learning Groups are groups of learners who are interested in the same topic of learning. Some users in the group can have some teaching roles.
- Learning Salons
Learning activities organized based on knowledge structures from learning groups.
- Learning Plans
Regular plans (weekly and monthly) and reviews, together with scheduled reminders, forming good learning habits.
Workflows to work with lists of SEs to accomplish learning and thinking processes. Workflows can be shared to spread good learning methods.
Core functions and beliefs
- Quick capture of SEs in various contexts
Quickly note down SEs at the moment without interrupting current work in hands. Various contexts can be automatically appended to the SEs.
- Quick and flexible display of SEs and knowledge
Knowledge at your fingertips.
- Cultivation of self-reflection skills
Self-reflection makes consciousness grow, from drops of SEs to understanding of the whole.
- Learning or thinking accomplished through simple editing
Learning or thinking can be done in layers and steps, so it can be transformed into many short steps of simple editing operations, making it a highly efficient process with minimum thinking. One task a time, zoom in.
- Workflows helps you learn and think efficiently
Learning and thinking workflows can be configured and shared.
- Learning Plans cultivate good learning habits
Weekly plans, monthly plans, yearly plans. Reviews and stats.
- Visualization of knowledge and brain
- Smooth transitioning btw learning and teaching. Teach effectively
Rendering of one’s knowledge and instructing in a finer grain.
- Generating knowledge of conventional forms smoothly
wiki, pdf, ppt/slide, blog, book, and so on
- Powering and transforming various types of knowledge related activities
Knowledge is flowing in all kinds of activities, and all have “Learning Embedded”.
- Knowledge needs to be applied, and knowledge is everywhere
Knowledge formed from KE can be shared to various social networking sites with one click, with url to reference back and interact.
Ideas behind and Design Concerns/Challenges
- Engine in the knowledge era
As the engine in the industrial age powers automobiles, ships, airplanes, and razors, the engine in the knowledge era powers learning, teaching, blog writing, paper publication, book writing, project management and so on.
- Instill wisdom into the machine from the human crowd
By taking drops of wisdom from billions of human beings, the machine can have intelligence, like PageRank provides search service by absorbing the wisdom of the crowd.
- Fragmented Learning
Fragmented Learning is the truth of real life learning. Learning should never be separated from life and from play. KE makes it easier for everyone to learn while play.
- Self-Directed Learning or Selflearning
There is no learning other than Self-Directed Learning or Selflearning.
- Understanding of Consciousness
Our understanding of consciousness，how this understanding applies to the design of KE，and similarity with Ray Kurzweil’s PRTM. Briefly，consciousness is hierarchical lists on top of SEs.
- About tags
The flexibility of tags and how to manage it. Tag Tree represents abstract knowledge structure, and it can be applied to the KE itself, thus fulfilling a self-reference system.
Current knowledge produced (in progress)