Mindey, 
跨学科的语言文字
Introduce a tiny set of exhaustive transdisciplinary concepts that most people are intimately familiar with, that can represent all processes that people go through to build their worlds, then use them to organize information, and get people understand the modern world.
One of the hardest things in ensuring access know-how is knowledge representation. It is not easy to find concepts that most people would be intimately familiar with, and yet that those concepts would map well across disciplines. So, here is one set of such concepts: to ask Questions, then proceeding to search for Ideas to answer them, then to start and run Projects based on those ideas, and to do Tasks (or "Challenges") with respect to relevant Places to obtain Results. The below is an illustration of how transdisciplinary those concepts are, comparing them with the equivalent concepts in computer science and how they are related to the physics.
In Computer Sciences, these concepts correspond to what programmer does within their programs, that rely on TYPES, FUNCTIONS, VARIABLES, VALUES, OPERATIONS and PROCESSES. However, as Alan Turing had shown, these processes decompose into simple INPUT/OUTPUT of bits.
In Physics, scientists study INPUT/OUTPUT processes of MATTER and ENERGY instead, and use mathematics to model the changes they see, formalizing and approximating their behaviors with field equations describing phase spaces. (Note: as we discussed on the idea "MRSGREN", humans do that I/O of M/E as they live as well.)
Think of "FIELD FLUX" in the image as computation -- in that sense, our industries are "physics apps", and if projects are examples of groups of humans "self-programming" to execute on their dreams, then having such examples of contextualized execution (or running of projects) in public would work like open source software, and this is an idea of one set of hypothetical of concepts to achieve this. This idea is currently is being tested here on 0oo.
The sole purpose is to introduce, evolve and maintain data alignment protocol.
This protocol (NRV v3) is based on this idea. Correspondance:
- 'VALUE' is '100 RESOURCE',
- 'TYPE' is '200 CATEGORY',
- 'FUNCTION' is '300 METHOD',
- 'PROCESS' is '400 SYSTEM',
- 'OPERATION' is '500 OPERATION',
- 'VARIABLE' is '600 LOCATION'
I / O如何变为：<类型，函数，过程，操作，变量和值？>
10100111011010101101101101101100101011 这一切都使我感到奇怪，一个简单的图灵机如何变成这6种事物，我们如此共通。 明显地：
-值：这是 Turing Tape 数据或状态。 -类型：仅是图灵磁带上的常见图案。 -变量：放在 Turing Tape 上。 -操作：当时钟带有读写位置时，会发生这种情况。 -过程：是物理的时钟使操作得以实现-图灵机的电机和读/写头。 -函数：它是“变量”的“函数”类型，它存储尽可能多的值来执行操作。
不难看出计算机的所有功能如何清晰地分解为这些东西。我很想学习如何完全由NAND门构建计算机，或者如何完全由异步神经元构建大脑，以及从这些低级事物如何变成这6个概念的理解中我们可以获得什么见解，因为我确实看到了这些相同的concepts跑步协会。也许了解信息流程如何变成这六件事，将有助于提出一些根本上是新的东西（例如组织形式）。还有更多抽象的东西，例如等式模型，甚至还有更多抽象的东西，例如polycontext metasymbol。是否存在普遍可加性之类的东西，它如何收敛到普遍性物品？
有趣的是，“类别”和“类型”是“问题”，“任务”和“查询” ...与“目标”，“意图”，“问题”，“领域”，“兴趣”相吻合。这意味着查询是类别：每个搜索查询都是一个类别。
How does I/O become:
10100111011010101010101101101100101011 That all makes me wonder, how does a simple Turing Machine become these 6 things, that we are so common with. Obviously:
It's not hard to see how everything what computer does, clearly breaks down to these things. I would be interested in learning how computer is built entirely out of NAND gates, or how brain is built entirely out of asynchronous neurons, and what insights can we get from the understanding of how these low-level things becomes these 6 concepts, cause I do see these same concepts running societies. Perhaps understanding how information processes become these 6 things, would be help to come up with something (like a form of organization) that's fundamentally new. There are more abstract things, like the equation model, and even more abstract thing like polycontext metasymbol. Is there something like universal additivity, and how can it converge towards the universal good?
It's interesting to observe, that
CategoriesandTypesareQuestions,QuestsandQueries... coincide withGoals,Intents,Problems,Domains,Interests. It means that Queries are Categories: every search query is a category.我认为重要的是要注意类型、变量、类、方法、类型类只是编译器使用的语法糖。因此，它们实际上并不存在于计算机代码中。
最终，编译器生成的是一系列指令。没有针对变量、方法或类型的说明。
编译器抽象导致没有计算！我认为计算机如此不兼容的部分原因是这是一个不幸的限制。重要的是实现之间共享的数据结构和字段。这就是使代码兼容的原因。
我将为不兼容的计算机代码创建一个类别。
I think it is important to note that types, variables, classes, methods, typeclasses are just syntactic sugar used by the compiler. As such they dont actually exist in computer code.
Ultimately what gets generated by the compiler is a sequence of instructions. There is no instruction for a variable or a method or a type.
Compiler abstractions result in no computation! I think part of why computers are so incompatible is that this is an unfortunate limitation. What matters is the data structure and fields that are shared between implementations. This is what makes code compatible.
I will make a category for incompatible computer code.