hutuyingxiong / smg

"强人工智能"系统

SMG(强人工智能系统)

参考文档:https://github.com/jiaxiaogang/SMG_NOTE#点击查看

大家有交流需求或问题请直接Issues我,在Issues,我知无不言,言无不尽,回复及时,用词流利!(QQ/微信七天回复一次)

-------------------引言-------------------

第一梯队:1950年图灵提出"可思考的机器"和"图灵测试",他说:"放眼不远的将来,我们就有很多工作要做";

第二梯队:1956达特矛斯会议后,明斯基和麦卡锡等人穷其一生心血,虽未落地,却为AGI奠定了很多基础;

第三梯队:随着bigData,云计算等成熟,AI迎来DL热,但DL并不智能,故小僧希望通过此项目将AGI落地;

-------------------构架设计介绍-------------------

• 抽象
• 结构

-------------------优点分析-------------------

• 无黑盒问题;
• 通用
• 可运行于单机终端
• 可解决当下NLP的瓶颈
• 不依赖巨量数据
• 不过度依赖算法
• Mind温和友善;

-------------------系统的理念-------------------

• LOP编程**
• logThink与noLogThink
• 基于理解的NLP
• 深理解与浅理解
• 三维抽象架构
• 树形知识表示
• 类比,归纳与统计
• 抽象与结构
• 树形智能神经网络
• 不过度依赖算法与大数据
• 先天noData
• 等等

-------------------特征-------------------

• 先天noData,需要像人类一样较长时间的学习与成长期;

-------------------意识-------------------

• 意识并不神秘,只是这个"词汇"含盖了大量的含义;所以这个词汇是泛化了很多含义;要分解分布到系统中...
• 意识是开发出来的,不是电影和小说里的觉醒那么玄幻;
• "意识"的分解
• 意识流(AIAwarenessModel)
• 意识层(logThink)
• 意识行为
• 第6感
• 潜意识
• 点击查看相关笔记

-------------------SMG架构-------------------

1. Mind引擎

2. 数据:

• 数据在Input时,从SMG架构图底层流向高层;
• 理解的过程其实就是数据的处理过程;
• logThink和noLogThink
• AIMemory AIAwareness AIMK AIMindValue AIMind...

3. "性能塔"及"唯一性的性能优化"方式;

• 性能塔:(见数据流)底层流向高层;
• "唯一性的性能优化":避免了重复;性能良好;基于:类比、归纳与统计的理解系统:(反转替代优先原则)
  • 唯一类比方式:
    • 从可获取到的特征对比;(如夜间,根据声音)
    • 从最显著的特征开始对比;(如杯子的颜色)

3. 基于理解

只有基于理解的NLP才有可能达到人类同等水平;

4. 基于:类比、归纳与统计的理解系统;
5. 先天noData;
6. 基于能力开发;
7. 后天学习
8. 灵活性

• 动态继承
• 动态属性
• 动态接口等
• 基于data的方式使其灵活,通用;

9. 神经网络

• AILine(Stong等)
• AIPointer
• LightArea
  • 纵向点亮
  • 横向点亮

10. 想像力

想像力:组合颜色,材质等，铺到模型上,GAN;

11. 创造力

参考:(见笔记:AI/框架/创造力)

12. 预测

基于常识CommonSence

13. 知识表示

数据拆分(在Memory->AIAwareness的过程中,自然而然的实现拆分与抽象;)
参考:

https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%A1%86%E6%9E%B6/%E7%9F%A5%E8%AF%86%E8%A1%A8%E7%A4%BA.md

-------------------时间线-------------------

2017,05,21

• 重绘了新版架构图;
• AIFoundation

2017,05,22(OOP2DataLanguage)

• 颠覆现有的编程方式
• 知识表示(已解决)

2017.06.01左右

• 三维架构(参考笔记/AI/框架)

2017.07.10左右

• BrainTree(参考N3P7,N3P8)

2017.07.21

• ThinkTask(参考N3P11，Awareness->Demand->ThinkTask)

2017.08.01

• 意识

2017.08.13

• 思考流程整理

2017.08.14

• LightArea-区域点亮
• GeneralFeel-通用的感觉

2017.08.23

• 神经网络
  • AILine
  • 知识表示与神经网络
  • 树形智能神经网络
  • 神经网络的抽象方式
  • 网口

2017.09.13

• 感觉体系
  • 内感觉
  • 外感觉
  • 感觉的知识表示
  • 神经网络的全局搜索

注:
	1. 大家有交流需求或问题请直接Issues我;
	2. 在Issues,我知无不言,言无不尽,回复及时,用词流利!
	3. (QQ/微信七天回复一次)

SMG (Strong artificial Intelligence system)

Reference documentation:https://github.com/jiaxiaogang/SMG_NOTE#点击查看

# I have a communication needs or questions please directly I am, in the Issues, I know nothing, words endless, reply in time, words fluent! (QQ / micro letter seven days to reply once)

------------------- Introduction -------------------

The first echelon: 1950 Turing put forward the "think of the machine" and "Turing test", he said: "look forward to the near future, we have a lot of work to do";

Second echelon: 1956 Dartmouth meeting, Minsky and McCarthy and others poor life of their own efforts, although not landing, but for the AGI laid a lot of foundation;

The third echelon: With bigData, cloud computing and other mature, AI ushered in the DL heat, but DL is not smart, so the monk hopes to AGI landing through this project;

------------------- Architecture Design Introduction -------------------

• abstract
• structure

------------------- Advantage Analysis -------------------

• no black box problem;
• Universal
• can run on a stand-alone terminal
• can solve the bottleneck of the current NLP
• do not rely on huge amounts of data
• no overridden algorithm
• gentle and friendly;

------------------- The concept of the system -------------------

• [LOP programming ideas] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%89%8B%E5%86%99%E7%AC%94%E8%AE%B0/Note4. md # n4p13loplayer-oriented-programming170803)
• [logThink and noLogThink] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%A1%86%E6%9E%B6/%E8%87%AA%E6%88%91.md # Two operations)
• [based on understanding NLP] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/Light%E5%8F%8A%E5%BA%94%E7%94%A8/Light.md#nlp language Be sure to describe the meaning of the core to achieve 100 correct rate)
• [deep understanding and shallow understanding] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%A1%86%E6%9E%B6/%E6%B3%A8%E6%84%8F % E5% 8A% 9B.md)
• [three-dimensional abstract architecture] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%A1%86%E6%9E%B6/3%E7%BB%B4%E6%8A%BD% E8% B1% A1% E6% A6% 82% E8% BF% B0.md)
• [tree knowledge representation] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%89%8B%E5%86%99%E7%AC%94%E8%AE%B0/Note3 .md # n3p7 data tree theory)
• [analogy, induction and statistics] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%89%8B%E5%86%99%E7%AC%94%E8%AE%B0/ Note5.md # n5p2 intelligent neural network)
• abstraction and structure
• No reliance on algorithms and large data
• congenital noData
• and many more

------------------- Features -------------------

• naive noData, need to be as long as human learning and growth period;

------------------- awareness -------------------

• consciousness is not mysterious, but this "vocabulary" contains a lot of meaning; so the vocabulary is generalized a lot of meaning; to decompose distributed to the system ...
• consciousness is developed, not the film and the awakening of the novel so fantasy;
• the decomposition of "consciousness"
• A stream of consciousness (AIAwarenessModel)
• consciousness layer (logThink)
• Conscious behavior
• the first six sense
• Subconscious
• [click to view related notes] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%89%8B%E5%86%99%E7%AC%94%E8%AE%B0/Note4 .md)

------------------- SMG architecture -------------------

1. Mind engine

2. Data:

• data in the Input, from the bottom of the SMG structure to the high level;
• the process of understanding is actually the process of data processing;
• logThink and noLogThink
• AIMemory AIAwareness AIMK AIMindValue AIMind ...

3. "performance tower" and "unique performance optimization" approach;

• performance tower: (see data flow) the bottom of the flow to the top;
• "Unique performance optimization": avoid duplication; good performance; based on: analogy, induction and statistical understanding system: (reverse substitution priority principle)
• the only analogy:
• from the available feature contrast; (such as night, according to the sound)
• from the most notable features began to contrast; (such as the color of the cup)

3. Based on understanding

Only NLP based on understanding is possible to achieve the same level of human beings;

4. Based on: analogy, induction and statistical understanding system;
5. naive noData;
6. Capacity-based development;
7. acquired learning
8. Flexibility

• Dynamic inheritance

• Dynamic properties

• dynamic interface and so on
• based on the data to make it flexible, generic;

9. Neural network

• AILine (Stong et al)
• AIPointer
• [LightArea] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%89%8B%E5%86%99%E7%AC%94%E8%AE%B0/Note4.md # n4p17lightarea)
• vertical light
• Lights up

Imagination

Imagination: combination of color, material, etc., spread to the model, GAN;

11. Creativity

Reference: (see note: AI / frame / creativity)

12. Forecast Based common sense

13. Knowledge representation

Data split (in the Memory-> AIAwareness process, the natural implementation of the split and abstract;) Reference: [https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%A1%86%E6%9E%B6/%E7%9F%A5%E8%AF%86%E8%A1%A8 % E7% A4% BA.md] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%A1%86%E6%9E%B6/%E7%9F%A5%E8%AF% 86% E8% A1% A8% E7% A4% BA.md)

-------------------timeline-------------------

2017,05,21

• redraw the new version of the composition;
• AIFoundation

2017,05,22 (OOP2DataLanguage)

• subversion of existing programming methods
• knowledge representation (resolved)

2017.06.01 around

• 3D architecture (reference notes / AI / framework)

2017.07.10 or so

• BrainTree (see N3P7, N3P8)

2017.07.21

• ThinkTask (refer to [N3P11] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%89%8B%E5%86%99%E7%AC%94%E8%AE%B0/ Note3.md # n3p11awareness-demand-thinktask --- or old info demand), [Awareness-> Demand-> ThinkTask] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%A1%86 % E6% 9E% B6 / Understand.md # awareness-demand-thinktask task))

2017.08.01

• [awareness] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%89%8B%E5%86%99%E7%AC%94%E8%AE%B0/Note3.md # n3p15 awareness 170801)

2017.08.13

• [thinking process finishing] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%89%8B%E5%86%99%E7%AC%94%E8%AE%B0/Note4 .md # n4p2 thinking evolution of the essence of ai thinking 170714)

2017.08.14

• [LightArea-area lit] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%89%8B%E5%86%99%E7%AC%94%E8%AE%B0 /Note4.md#n4p17lightarea)
• [GeneralFeel - general feeling] (https://github.com/jiaxiaogang/SMG_NOTE/blob/master/%E6%89%8B%E5%86%99%E7%AC%94%E8%AE%B0 /Note4.md#n4p18 general feeling)

2017.08.23

• Neural network
  • AILine
  • knowledge representation and neural network
  • tree intelligent neural network
  • neural network abstraction method
  • network port

2017.09.13

• sensory system
  • inner feeling
  • outside feeling
  • knowledge of sensation
  • global search for neural networks