# General AI

```
General AI algorithm:

Natural language -> Python programming language -> Go through CPU -> If it is working, add that sentence to database to add weights to that sentence, if it is not working, minus weights for that sentence -> use words or long sub_string weights to generate more following natural language sentences -> it is a never end loop, but if the storage is about to blow, we need to find a way to do compression and find more way to store data.

Those code are generated in real time. For each response, it generate different algorithm or code. It adopts to any situation.

#yingshaoxo
```

```
General AI 的算法都是实时生成的

需要完成什么任务就生成什么样的代码

只要有自更新、自纠正，就可以很轻松的完成任务

从某方面来讲，这叫做“适应性强”
```

<!--
```
How to make "Text transformer based text generator" with only CPU?

Source Text: Did you see AA?\nI see AA.

Generalized Text: Did you {see} {AA}?\n I {see} {AA}.

So next time when you meet "Did you attack that monster?", you will get "\n I attack that monster." because of "Did you {attack} {that monster}\n I {attack} {that monster}."

#ai #idea #yingshaoxo
```

If you have a global dict, the key would be the rule text, the value would be the following rule text.

That dict would get updated in real time as previous context text grow.
-->
