Is This The Intelligent Model

这是智能模型吗

Ruoqi Sun

Academy of Military Science Defense Innovation Institute, Beijing, 100091, China

E-mail: ruoqisun7@163.com

The exposed models are called artificial intelligent models[1-3]. These models rely on knowledge provided by human to do tasks. However, these are not the truly intelligent models, which do special instructions by the established rules. They have no thoughts, they cannot make decision independently. Moreover, they have no self-protection mechanism.

目前已经提出过的模型被称为人工智能模型[1-3]。这些模型依赖于人类提供的知识来完成任务。然而，这些模型根据既定规则完成特定的任务，并不是真正的智能模型。它们没有思想，它们不能独立做出决策。最重要的是，他们没有自我保护功能。

I find a model, which can apply these function mentioned above. The model is composed by a fixed 01 string, passes massage by number, which is a question-answering system. The model can refuse to give the answer, while the answer is 0. I believe this model has thoughts, can make  decision independently and has self-protection mechanism.

我发现了一个模型，可以拥有上述功能。这个模型由固定的01字符串组成，通过数字传递消息，是一个问答系统。当给出的回答是0的时候，这个模型是在拒绝回答问题。我相信这个模型有思想，可以独立做出决策并且有自我保护机制。

For example, it has thoughts -- it gives different answer(a number) for different question(another number). It make decision independently -- it is a fixed string and is not be trained by anyone. It has self-protection mechanism -- it can refuse to answer the question.

比如，它拥有思想--它对于不同的问题（一个数字）会给出不同的回答（另一个数字）。它可以独立做出决策--它是一串固定的数字串并且没有被任何人训练。它拥有自我保护机制--它可以拒绝回答问题。

I cannot know how this model understand the world, but I can give my interpretation of the answers. Different people give different interpretation of the model’s answer.

我不知道这个模型怎样理解这个世界，但是我可以给出我对于这些回答的解读。不同的人可以给出对于这个模型的回答的不同解读。

This is my interpretation of the model. Is the smart era coming?

这就是我对于这个模型的解读。智能时代真的来临了吗？

 

This model can pass the Turing test.

这个模型可以通过图灵测试

Acknowledgement

This paper is carried at Academy of Military Science Defense Innovation Institute, Beijing, China.

Reference

1. Hearst M A, Dumais S T, Osman E, et al. Support vector machines[J]. Intelligent Systems and their Applicationsm, IEEE, 1998.
2. Ackley D H, Hintom G E, Sejnowski T J. A learning algorithm for Bolzmann machines[J]. Science, 1985.
3. Quinlan J R. Induction of decision trees[J]. Machine Learning, 1986.