Who is the ultimate decision maker?

本文深入探讨了因果关系的根源与局限性,通过哲学视角解析因果链中‘某人’的存在及其对决策的影响。从休谟的因果连接理论出发,文章指出因果关系并非必然存在,而是基于对事件的记忆和归纳推理建立的。文章进一步阐述了现实世界中因果关系的复杂性,以及其作为知识来源的基础性作用。最后,文章提出因果关系的真正挑战在于理解描述与现实之间的差异,以及如何在不完全了解宇宙边界的情况下进行有效的自我娱乐。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

The answer seems simple:

Either "me" or something else in my brain makes them.

Because anyway, it has to be "somebody" at the end of the causal chain to make the decision so that something can eventually happen.

Hume's causal connection theory tells that one thing doesn't necessarily lead to another thing. All causal connections are only some inductions resulted from the capability to memorize.  We have memory, we gather different events/phenomenon together then compare them, and we found differences, then we built concepts for them and memorizes the connection/relationship between these events/phenomenon. And this's all.

It's all source of every thing we know until now. It means that it's the basic model for each piece of knowledge/belief we know.

Hume's right. But not enough.

Because the real reason that causality isn't true is not the A doesn';t necessirily cause B, It's that there is no A and B.

This is not easy to understand for most of the people. Even me myself forget it frequently. Because we're all materialists. And this statement itself doesn't mean in common sense also. It doesn't only means that most of us are materialists. It means that , literally, all of us, including every human being which is now living in this world, even animals whomever have brains, are all materialists.

One cannot live in this world without materialism. Or say that, one should at least be a materialism first, then he can be something else.

And also, another shocking theory can be infered from this theory: There is no "idealism".

And it doesn't mean that there is no people who believes idealism or holds idealism. It means that THERE IS NO SUCH THING which is thought or treated as the thing that idealism really means.

Since there is no A and B, does it means that there is no anything at all?

The answer is NO and it's the only good thing we've found since the beginning of this essay.

Things exist. And we can also describe them. As anyway we want.

It seems that this sends the causality back on the table again.......?

Well, one can really think in this way. In some situations. And this is also why knowledge works/worked for a very long time and it worked so well that it even suppots the whole human civilization history.

But yet there's still a very tiny but extremely significant difference between this way and another wiser, more accurate way to understand it--- the philosophy way.

Philosophers always care about the foundation. The foundation of causality lies on the limit on the meaning of "description".

Just think about the meaning of it for a while.

......

I won't go into the detail of the discussion about what is a description. There's actually a new emerged theory named it and it also discusses/studies the same thing that what I'm discussing here. The philosophy inside it is quite simple. But I don't recommend people to look for and read it because it's really at it's very beginning stage and nothing to read inside it.

Carry on.

We can describe things, and Causal is one of the tools. How I describe the world doesn't equal to how I believe this world is.

Simply says, Description≠The world.

No matter who;s the speaker, they can never convince me that they are talking or they can talk about anything.

Only one thing have been existed so long: the universe itself.

But before we really get to know where the border of it is, we can never talk about the universe. This makes us the unability to talk about anything?

Yes.

And I think this is exactly why the most part of the universe doesn't talk except us --- The stupidest species who think it has wisdom(to talk about the universe).

But if we really accept this theory, another more serious problem comes in. Because as a "fact", we know that we though did talked, and that also did(at least seems) "worked"... How would that be explained after all??

The answer is a question:

Any thing we've got in the past or we're going to get, and any progresses we've "made" or going to acquire, do they really exist?

The answer is a even bigger NO.!

Nothing exists out of human's brain. Or say, Everything exists (only) in brain. This means that, so far, all we did are just entertaining ourselves. Entertainment is everything we've got until now.

Wait, if we can really entertain ourselves, that means we can still do something for ourselves, even without knowing a bit about the real universe, right?

True.

And this is maybe the most important thing we should keep in mind for the whole life. We do can never know the world, but that also doesn't equal to our disability to entertain ourselves.

So it comes to a result that though the desire for the ultimate truth is really stupid, but the desire for using the "world" is yet a very good thing to hold. Cause desires are by nature "good". Everything we want is "good" and it's not arguble since it's nature.

Because goodness is always relative to the individuals.

Conclusion:

"Who is the ultimate decision maker?" is not a right question.

All we should do is describe the world, use the world, and never ask how is the world. The attritude is important:

To describe, not to find out.

"Finding out" is an hulluciation which produces from wrong/unstrict reasoning.

转载于:https://my.oschina.net/digerl/blog/37765

内容概要:该PPT详细介绍了企业架构设计的方法论,涵盖业务架构、数据架构、应用架构和技术架构四大核心模块。首先分析了企业架构现状,包括业务、数据、应用和技术四大架构的内容和关系,明确了企业架构设计的重要性。接着,阐述了新版企业架构总体框架(CSG-EAF 2.0)的形成过程,强调其融合了传统架构设计(TOGAF)和领域驱动设计(DDD)的优势,以适应数字化转型需求。业务架构部分通过梳理企业级和专业级价值流,细化业务能力、流程和对象,确保业务战略的有效落地。数据架构部分则遵循五大原则,确保数据的准确、一致和高效使用。应用架构方面,提出了分层解耦和服务化的设计原则,以提高灵活性和响应速度。最后,技术架构部分围绕技术框架、组件、平台和部署节点进行了详细设计,确保技术架构的稳定性和扩展性。 适合人群:适用于具有一定企业架构设计经验的IT架构师、项目经理和业务分析师,特别是那些希望深入了解如何将企业架构设计与数字化转型相结合的专业人士。 使用场景及目标:①帮助企业和组织梳理业务流程,优化业务能力,实现战略目标;②指导数据管理和应用开发,确保数据的一致性和应用的高效性;③为技术选型和系统部署提供科学依据,确保技术架构的稳定性和扩展性。 阅读建议:此资源内容详尽,涵盖企业架构设计的各个方面。建议读者在学习过程中,结合实际案例进行理解和实践,重点关注各架构模块之间的关联和协同,以便更好地应用于实际工作中。
资 源 简 介 独立分量分析(Independent Component Analysis,简称ICA)是近二十年来逐渐发展起来的一种盲信号分离方法。它是一种统计方法,其目的是从由传感器收集到的混合信号中分离相互独立的源信号,使得这些分离出来的源信号之间尽可能独立。它在语音识别、电信和医学信号处理等信号处理方面有着广泛的应用,目前已成为盲信号处理,人工神经网络等研究领域中的一个研究热点。本文简要的阐述了ICA的发展、应用和现状,详细地论述了ICA的原理及实现过程,系统地介绍了目前几种主要ICA算法以及它们之间的内在联系, 详 情 说 明 独立分量分析(Independent Component Analysis,简称ICA)是近二十年来逐渐发展起来的一种盲信号分离方法。它是一种统计方法,其目的是从由传感器收集到的混合信号中分离相互独立的源信号,使得这些分离出来的源信号之间尽可能独立。它在语音识别、电信和医学信号处理等信号处理方面有着广泛的应用,目前已成为盲信号处理,人工神经网络等研究领域中的一个研究热点。 本文简要的阐述了ICA的发展、应用和现状,详细地论述了ICA的原理及实现过程,系统地介绍了目前几种主要ICA算法以及它们之间的内在联系,在此基础上重点分析了一种快速ICA实现算法一FastICA。物质的非线性荧光谱信号可以看成是由多个相互独立的源信号组合成的混合信号,而这些独立的源信号可以看成是光谱的特征信号。为了更好的了解光谱信号的特征,本文利用独立分量分析的思想和方法,提出了利用FastICA算法提取光谱信号的特征的方案,并进行了详细的仿真实验。 此外,我们还进行了进一步的研究,探索了其他可能的ICA应用领域,如音乐信号处理、图像处理以及金融数据分析等。通过在这些领域中的实验和应用,我们发现ICA在提取信号特征、降噪和信号分离等方面具有广泛的潜力和应用前景。
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值