<![CDATA[Mindey]]> 0, and L(A) → ∞.]]>http://localhost:2368/http://localhost:2368/favicon.pngMindeyhttp://localhost:2368/Ghost 3.35Wed, 25 Nov 2020 15:09:46 GMT60<![CDATA[一起逃离熵的黑洞]]>人会死亡,文明和文化会被接管或遗忘他们的过去,我们的基因组会被分解,或被辐射、环境污染、疾病所破坏;我们的神经网络会忘记,或终将退化。人类和所有生命的共同敌人是熵(物质的不确定性)。反之,我们的共同目标是获取信息。

下面是对这些情况的信息论和物理学解释,以及一些帮助我们实现共同目标的想法。

关于黑洞

当著名的牛顿看到一个苹果因为重力掉在地上时,他没有注意到另一件事——苹果不仅落在地上,它还从过去落到了未来(现在)。是什么力量把苹果拉到了未来?

根据对现有证据的解释,我们确实掉进了一个“黑洞”——不是引力,而是熵。

我们所知道的信息,实质是减少信息来源的不确定性。当一枚硬币(信息源)在空中旋转,你并不知道它落地时是正面还是反面向上,即其结果具有“熵”(随机性),当它落地时(你观察到结果),你得到“信息”(关于结果的确定性)。

人类的生活是结果的累积,因此可以说是随着时间的推移而积累的“信息”。

人类思维很大程度上是将习得的经验编码于神经网络权重分布中。然而,随着时间的流逝,大多数 每个人最终都死了。事实上,

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http://localhost:2368/2018/07/23/yiqi-taoli-shang-de-heidong/5f8b9685abdc8a4be94a1cfdMon, 23 Jul 2018 00:00:00 GMT人会死亡,文明和文化会被接管或遗忘他们的过去,我们的基因组会被分解,或被辐射、环境污染、疾病所破坏;我们的神经网络会忘记,或终将退化。人类和所有生命的共同敌人是熵(物质的不确定性)。反之,我们的共同目标是获取信息。

下面是对这些情况的信息论和物理学解释,以及一些帮助我们实现共同目标的想法。

关于黑洞

当著名的牛顿看到一个苹果因为重力掉在地上时,他没有注意到另一件事——苹果不仅落在地上,它还从过去落到了未来(现在)。是什么力量把苹果拉到了未来?

根据对现有证据的解释,我们确实掉进了一个“黑洞”——不是引力,而是熵。

我们所知道的信息,实质是减少信息来源的不确定性。当一枚硬币(信息源)在空中旋转,你并不知道它落地时是正面还是反面向上,即其结果具有“熵”(随机性),当它落地时(你观察到结果),你得到“信息”(关于结果的确定性)。

人类的生活是结果的累积,因此可以说是随着时间的推移而积累的“信息”。

人类思维很大程度上是将习得的经验编码于神经网络权重分布中。然而,随着时间的流逝,大多数 每个人最终都死了。事实上,平均每天有超过15万人死亡。每个人的大脑约有860亿个神经元,人脑死亡的时候,我们就丢掉了在这些神经元里被编码的信息。

我们说,过去的信息正在流失。如果仔细观察,这个过程与物质进入黑洞事件视界的过程非常相似。看看“现在”这个时刻:作为相对稳定结构的一部分,未被复制到未来(“现在”的下一刻)的信息永远丢失在过去。“现在”现象非常类似于一个事件视界,或在抛光的风熵中增长的表面边界。

熵(“随机性”)破坏信息,但也揭示了新信息。它并不完全站在我们的一边,它有助于我们创造,也让我们失去了我们拥有的部分。理想情况下,我们希望世界能够保存我们的现状,并发现新的信息。

共同的目标

我们的隐含目标是相同的,即使是40亿年前。生命起源于第一个分子,也许是RNA,能抵抗熵的破坏力。就像地球能够抵抗重力一样,RNA分子能够通过复制自身来抵抗“熵力”。在熵的压力下,信息扩散过程开始进化以抵消它。DNA、细胞、性、神经元、大脑、书籍、电线、处理器等等,这些都是信息增殖机制的例子。所有这些进化的共同之处,是它们都解决了在空间和时间距离上复制信息的问题。例如书籍,像DNA一样,是一种更稳定的信息媒介,使我们能将古人的知识复制到现在。

在大脑和计算机处理器的情况下,很明显,思维是通过神经突或电线将信息从一个地方复制到另一个地方而发生的。有些信息被复制到另一个神经元,有些则不会。在性行为的情况下,它可能不那么明显,但性是进化思维的工具,它一步一步地增加了后代的变异:某些环境中的某些基因型被复制(繁殖)到未来,有些则没有(它们会死亡)。就像我们更可能保留不断传播的解决问题的想法(神经元的信号),进化倾向于支持那些能解决问题的后代分支,并有望在未来更可能抵消熵(=保留信息)。

换句话说,世界的熵(F)在训练我们这些变异复制器(=信息),寻找关于熵(世界)本身结构的最佳模型(F’)(=更多信息),采取行动(X)来抵消它,这是我们隐含的目标(Y)。因此,我们做科学,研究物理定律来理解(F),通过构建我们自己的(F’)去应对它。*

我们的目标方程很简单:F(X)=Y,我们需要找到X,为什么?我们不想死。我们不希望在我们的神经元中被编码的生命体验消失,我们不希望在我们的人民中被编码的文化破坏,被熵摧毁,终结于噪音制造者、污染物、蚊虫叮咬、病毒、政治恐怖分子和文化入侵者。

与熵相反,我们的共同目标是创造和保留信息。

谷歌、中国和伊隆马斯克有什么共同之处?

一个公司,一个国家和一个个人。

早在199X年,谷歌就已经确定了组织世界信息并使其普遍可用和有用的使命。该任务定义准确地抓住了拯救信息的要领,它正在重新排列信息结构,以使更多样化的信息存在。

在2008年夏季奥运会期间,中国宣布了一个崇高的目标:“同一个世界,同一个梦想”。这个共同的目标可能难以捉摸,但鉴于以上思考,我们,生命,有一个共同的隐性目标:战胜熵(组织信息)。

最近,伊隆马斯克明确承担了一项拯救生命的使命。既通过资助FLI挽救使命宣言中声明的生命,又采取其他努力,例如SpaceX通过太空船扩散生命,使其多样化地存在于其他星球。

我很确定这些实体在某种程度上花了很多时间来思考同样的问题。

什么宇宙飞船能拯救我们?

现存风险不仅存在于全球层面,也存在于个人层面。生物有机体的预期寿命可由冈珀茨-梅卡姆死亡率定律预测。这里有一个很好的介绍,但重点是我们的生命体经历了一个类似于俄罗斯方块游戏的过程。

在俄罗斯方块中,当砖块下落的速度超过某个阈值时,你会迅速失败。同样,当人类生命体达到一定阈值时,人会快速死去。生命的环境影响(如游戏中下落的砖块,如食物和其他许多因素)对我们的身体来说太快了。两者很相似,因为像俄罗斯方块的砖块一样,我们生命体中的恶性结构也是多样的和非均质的。它们起初可能很小,但最终会导致大问题,例如空气污染微粒,因为类似结晶作用形成凝块,最终导致中风(参考)。

无论如何,对于比上面提到的范围更广泛的问题,已经有了系统的解决方案,这给了我们希望。Henry W. Lin和Max Tegmark最近的见解和发现表明,我们的物理定律确实很简单,深度学习算法(和我们的大脑)可以解决它们。

解决方案

教育+

用深度学习 首先使用大脑

如果你得了一种没有已知治愈方法的疾病,或者想让你的祖父母免于死亡,那么你要做的第一件事是进入能够灵活解析和理解异常结构的年轻人的思维,并运用我们三维游戏中的技术来表现生物数据的世界——可以击败“俄罗斯方块”的思想。

你可以投资“教育超级通道”,运用人类的海马神经可塑性(hippocampal neuroplasticity)、奖励依赖(reward dependence)(例如由于博彩中奖的不确定性,导致玩家沉迷于其中)、社会吸引力(social attraction)(例如人们习惯在社交网络中寻找朋友)和引人入胜的故事情节等,去创造一种强大且易于成瘾的社群,以此来吸收世界各地的人才。然后便可以输出治疗绝症、逆转衰老的方法,设计出新的概念汽车和其他新型交通工具,气候控制的解决方案,以及各种有用的设备,像人体内的远程手术机器、可植入人体的健康监测传感器,确保人体没有任何部分脱离动态平衡。

这个电脑游戏,我称之为3D学习迷宫,现在已经有了一个工作原型。除了3D方面,基于Schema.org的结构,目前正在进行关于秘密锁位置的结构化数据。它可以为VR技术提供改变世界所需的动力。

计划从细微开始,然后指数增长。

组织+

教育+只是一个想法,我们需要一个在全球性挑战的背景下进行批判性和建设性讨论的地方。这是WeFindX追求的理念和项目:一个金融智库。在那里你可以谈论世界上最大的挑战,给出建议,分享解决问题的想法,启动或资助基于它们的项目,并且可以半自动控制投资。无穷项目的完整描述超出了本文的范围。

住所+

随着我们的环境的熵增(比如污染,噪音),特别是在发展中地区,我们需要保护自己免受食物、空气、水、传染病、高温或低温等熵的影响。针对此问题,我有一个称之为胶囊公寓的想法,因为通常传统意义上的“家”(房屋)是昂贵的,所以很多人会因为这个“家”而终生不离开一个地方。把房屋和汽车连成一体的想法,可以作为一种替代方法来解决这个问题,使我们能够降低死亡和流行性疾病等风险,并使人类群体更加灵活。当气候不断变化时,可以让人们自由的在地球上的任何地方生活。

【胶囊公寓(capsulated habitation)】它有潜在的扩展空间,允许我们安装更多的传感器来监控我们的健康,当我们的身体发生病变时,应急系统会自动启动。自然死亡的老年人往往是在睡梦中死去。如果可以在床上安装某些传感器,当躺在床上的人身体发生某些变化的时候,应急系统便会自动采取紧急行动(发出警示或者基础治疗等)。胶囊公寓就是这种床的外推法,并且它可以让我们在任何地方工作。

机器人+

我们的手是我们能够创造地球上所有技术的关键因素之一。现在,我们已经拥有具有触觉和力反馈的假手。如果我们把这样的假手小型化,用电子手套取代电脑鼠标,并允许互联网上的人通过控制这些手,在微观层面上直接从电脑游戏中进行所有类型的手术,他们能做些什么?

如果我们能用较小的手创造更小的手,然后重复这个过程会怎么样呢?若有足够多的人脑控制这些手,我们可以解决很多问题。

通过微型肢体,游戏玩家可以练习对各种小动物进行手术,比如对昆虫、蠕虫、虫子,最终达到某个临界点,纳米机器人可以广泛地用于灵活有效地修复我们,在我们死亡之前。*

熵的宇宙飞船

生命本质上是一个从细胞到细胞,从大脑到大脑,从计算机到计算机,产生新技术,抵消熵压力的信息扩散过程,就像在恒星核心燃烧的核燃料产生抵抗重力的力量一样。

我们如何构建信息火箭?

当我们燃烧燃料并使用第三牛顿定律加速到轨道速度时,生命会在熵场中复制信息以推动自身发展。

想法 1 - 大脑间的接口

类似火箭的连接,大脑与大脑可以直接连接,通过插入高分辨率感观像素矩阵板并整合到脑胼胝体中,使我们的思想能够在彼此的大脑之间自然流动,就像在我们的左右脑半球之间流动一样。如果个性、记忆和梦想不仅仅储存在一个大脑中,我们就可以通过改善沟通来互相挽救。

想法 2 - 并行人工神经元

类似人工神经细胞,它被注入血液时会发现其他神经细胞并附着在它们周围,创建一个并行的神经网络,与底层的生物网络具有完全的双向通信,并且能够提供与外部设备和大脑的无线通信,在许多人的脑海中复制我们的记忆和个性。

想法 3 - 通过VR技术连接

利用VR技术来连接我们的能力。-- 3D迷宫的想法

想法 4 - 通过冷冻保存信息

还有人体冷冻技术,尽管它更像是一个冰冷的轨道停车,而不是“推进”本身。

想法 5 - 加快技术奇点

超级智能迅速发展。这是非营利组织SIAI在2000年开始实施的目标。

值得注意的是,第一枚火箭更常坠落,而且很可能如果我们从(2)或(3)开始,我们可能只有一次机会,并且在使它们安全之前解决超级智能控制问题是很重要的。

结论

我们是信息,我们需要新信息基质,否则我们会死。我提供了一些关于新技术的想法,比如教育超级通道(education hyper tunnels)、通过计算机游戏控制的力量操纵器(force manipulators)、胶囊公寓(habitation cells)、胼胝体连接点(corpus callosum junction)和其他一些想法,以帮助预防大规模流行病、进行急救处理、创造更多可靠的人体冷冻法,帮助组织和管理对想法发展的投资,以提高我们更早创造可靠的脑海可以存在的信息基质的概率。

既然有一些想法对我们所有人都有用,人是文化的信息基质,但不同的文化竞争编程它,与其专注竞争互相覆写更有道理的是,我们不惜一切代价合作创造更好、更多的信息基质,来维持、保护和发展我们所有的文化。

如果我们尽早采取行动,与相关人员分享相关信息,相关技术将更快实现,我们的头脑可能会成为更可靠的基质,以便在未来数十亿年内亲身生活和探索宇宙,就像我们的DNA一样

那么,想想从这里要和谁分享哪些部分,让我们一起达到熵的逃逸速度:

如果像俄罗斯、美国、中国等竞争实体、情报机构、竞争公司和一般人,都意识到如果我们更多地投资于医疗、文化和信息技术中,那么我们就可以从死亡中拯救自己(否则在没有安全的技术进步的情况下,我们大多数人在未来几十年都将死去,这在地质时间尺度上只是一瞬间),创造一个更高级的保留意识和帮助我们各种文化繁荣的基质,而非作为信息基质互相取代。

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<![CDATA[Hash Pill]]>Fact is, you are a unique information pattern in the world, defined by your mind, rather than just your private key.
How do you prove that you are you?

In mathematics, there is often a large number of ways to prove a fact if that fact is a universal truth.

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http://localhost:2368/2018/04/27/hash-pill/5f8b964cabdc8a4be94a1cf5Fri, 27 Apr 2018 00:00:00 GMTFact is, you are a unique information pattern in the world, defined by your mind, rather than just your private key.
How do you prove that you are you?

In mathematics, there is often a large number of ways to prove a fact if that fact is a universal truth. For example, there is a large number of ways to prove Pythagoras theorem. If something is true, you can look at it from many angles and arrive at the same conclusion. However, in cryptography, this hardly ever true. If you had lost your private key, you cannot access your assets, or decrypt messages, even if there is other strong evidence that they are yours.

The ability to prove things is critical to creating a world of fair credit and access to information. If you had ever lost a password, or wallet of bitcoin or other digital currency, or simply your data locked under your encryption key, you know how unforgiving is the fact that you only have one way to prove facts. For example, you may have proofs such as transaction records in other databases, governmental records and legal bank transactions, even people's memories, but that all doesn't count to recover a credit on cryptographic systems, if you do not have your private key.

Fact plain as the day of light remains: you are not your private key, and a multi-method provability of cryptographic facts about identities therefore would be a desired property for cryptographic methods.

Hash pill?

If the pattern that makes you - you, were to have the integrity of a blockchain, then you potentially could use the hash of your biological pattern at arbitrary moment, to provide a proof of yourself.

Question: does nature at physical level run on some kind of blockchain? The irreversibilitly of time may be an indicator that this is the case.

Question: Life is a process running on a much higher than physical level -- the expression of DNA also happens to be a computational process. Would introducing a substance (like a "CRISPR hash pill") to one's body, make a complex change in the further patterns that evolve in the body, that can be used to prove that the person had taken that pill before?

Biomarking yourself with a biomarker pill can work like something that binds a cryptographic key to a biological pattern forever. E.g., everyone who has a specific crypto-key, could log the proof of fact, when they swallowed the pill, in an existing blockchain, that tracibly binds them to that key.

Question: how hard would it be to fake those biological patterns, and what would the introduction of those patterns do to your very self?

Answer -- depends on the amount of information hashed at the moment of the bio-marker binding, and retained in the further evolution of the pattern that is you.

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<![CDATA[Escaping Entropic Black Hole Together]]>People die, civilizations and cultures are taken over or forget their past, our genomes decompose or are disrupted by radiation, pollution in our environments, diseases; our neural networks forget, or eventually suffer from degradation. The common enemy of humankind and all life is entropy. Contrarily, our common goal is attaining

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http://localhost:2368/2017/01/03/escaping-entropic-black-hole-together/5f8b95aeabdc8a4be94a1cd5Tue, 03 Jan 2017 00:00:00 GMTPeople die, civilizations and cultures are taken over or forget their past, our genomes decompose or are disrupted by radiation, pollution in our environments, diseases; our neural networks forget, or eventually suffer from degradation. The common enemy of humankind and all life is entropy. Contrarily, our common goal is attaining information.

The below is an information-theoretic and physical interpretation of these circumstances, and a number of ideas to help us achieve our common goal.

The Black Hole

When famously Newton saw an apple fall, he didn't notice one thing -- it fell not just towards the ground. It fell from past to the future. What force pulled it into the future?

According to an interpretation of the existing evidence we are indeed falling into a "black hole", - not gravitational, but entropic.

Information as we know it, is the substance that reduces the uncertainty about an information source. When a coin (information source) is spinning in the air, and you don't know if it will land heads or tails, it is said to have "entropy" (randomness) about the outcome, and when it lands (and you observe the outcome), you get "information" (certainty about the outcome).

We as humans who live their lives, are a result of outcomes, and thus could be said to be "information" accrued over time.

Human minds are largely coded in weight distributions within our neurons as results of what we've learned. However, as time goes by not most, but all people end up dead. In fact, on average over 150,000 people die every day. The information coded in approx. 86 billion neurons per brain eventually is lost to environment's natural noise background (even the stones succumb to erosion by the noise of winds and sand).

We say, information is being lost in the past. If you look closely, this process is quite similar to how matter enters an event horizon of a black hole. Look at the moment of "now": the information that is not copied over to the future (the next moment of "now") as part of relatively stable structures, is lost forever in the past -- a phenomenon of "now" is very similar to an event horizon, or a growing surface boundary in the polishing entropy of wind.

The entropy ("randomness") destroys information; but also uncovers new information. It's not quite on our side, it helps us create, but it makes us lose parts of what we are. Ideally, we would like the world where we can preserve what we are, as well as uncover new information.

Common Goal

Our implicit goal was the same, even 4 billion years ago. Life had arisen as the first molecules, perhaps the RNA, which were able to resist the destructive force of entropy. Much like Earth is able to resist the force of gravity, RNA moleculs were able to resist the "force of entropy" by replicating themselves. Under the pressure of entropy, the information proliferation process started to evolve to counteract it. The DNA, cell, sex, neuron, brain, book, wire, processor, etc. are just examples of information proliferation mechanisms What's common to all of these evolution's inventions is that they all solve problem of copying information over distances of space and time. For example, the books, like DNA, being a much more stable medium for information, enabled us to copy over knowledge of the ancients to the present time.

In the case of the brain and a computer processor it is very evident that the thinking happens as a result of copying information from one place to another through neurites or wires. Some information gets copied to another neuron, some doesn't. In the case of sex it may be less evident, but sex is a tool of evolutionary thinking, which granularly increases the variation of offsprings: some parts of genotypes in some environments get copied over (reproduce) into the future, some don't (they die). Just like we are more likely to retain the propagating thoughts (signals of neurons) that solve a problem, evolution tends to favor the extending lines of progeny that solves problems and are hopefully more likely to counteract the entropy (= retain information) in the future.

In other words, we could say that the world's entropy (F) trains us, the mutating replicators (=information), to look for best model (F') (=more information) about the structure of entropy (world) itself, and to take actions (X) to counteract it, and that it is our implicit goal (Y). Thus, we do science, research the laws of physics to understand the (F) by constructing ourselves (F') to counteract it.

Our goal equation is simple: F(X)=Y, and we need to find that X. Why? We don't want to die. We don't want our life experiences coded in our neurons, our cultures coded in our people be destroyed by entropic invaders, noise makers, starting from pollutants, mosquito bites and viruses, ending with political terrorists and cultural invaders.

Contrary to entropy, our common goal is creating and retaining information.

What do Google, China and Elon Musk have in common?

A company, country and an individual.

Google, back in 199X, has defined its mission to organize the world's information and make it universally accessible and useful. This mission definition captures accurately what saving information is about, it is rearranging information structures to enable more diverse information to exist.

Back in 2008, during the summer Olympics, China has declared a lofty goal - "One World, One Dream". This common goal might have been elusive, but in the light of the above reflections, we, the life, have an implicit common goal to beat the entropy (organize information).

Recently, Elon Musk, has explicitly taken on a mission to save life, both through funding the FLI with objective to save life in the mission declaration, as well as other endeavors, such as SpaceX with a spaceship to spread life by diversifying its presence to other planets.

I'm pretty sure that these entities in some way had spent significant amount of time thinking about the same issue.

What Spaceship Can Save Us?

There is existential risk not only on global level, but on personal level as well. The life expectancy of a biological organism is predicted by Gompertz-Makeham law of probability. There is a very good introduction to it here, but the main point is that our organisms experience a process similar to the game of Tetris.

In Tetris, you fail rapidly, when the speed of falling bricks is beyond some threshold. Similarly, human organisms fail rapidly, when they reach a certain threshold, where the environmental effects (falling "bricks", such as food, and many other factors) of life are too fast for our bodies to deal with. The similarity is close, because just like the bricks of Tetris, the malignant structures in our organisms are also diverse and non-homogeneus. These may be small, like the air pollution particles initially, but result in large issues eventually, due to effects similar to crystallization, for example, forming clots and resulting in strokes (ref).

However, there are systematic solutions to the problems of much broader scope than the ones mentioned above, which gives hope. A recent insight and discovery by Henry W. Lin and Max Tegmark shows that our laws of physics indeed are simple enough that deep learning algorithms (and our brain) can tackle them.

The Solutions

Education+

Use   deep learning   use brains first.

If you were to be sick with an disease without a known cure, or would like to save your grandparents from death, first thing you want to do, is to tap into the creativity of the minds of the young people with flexible abilities to parse and make sense of novel structures, and represent the world of data in biology that we have onto a computer game -- the minds that can beat "Tetris".

You could invest into the "education hypertunnels", which would enable us to employ our hippocampal neuroplasticity, movie-like suspense, irregular rewards, and the social attraction to search for friends like in social networks to create a super-addictive and very powerful combination, that sucks in the talents of the world, and outputs treatments for cancer, reversed aging, comes up with new car and rocket designs, solutions to equations for climate control, and all kind of useful gadgets like telesurgery machines and health monitoring sensors inside our bodies to make sure that not any fraction of them goes out of homeostasis.

This computer game, which I call 3D Study Maze, is described here. There is a working prototype. Apart from 3D aspects, the structure based on Schema.org is underway for structured data about secret, locked locations. It's something that could give VR technologies the momentum they need to change the world.

The plan is to start small, and get exponential.

Organization+

The education+ is just one idea, and we need a place to critically and constructively discuss about many of them in context of the world's challenges. This is the idea and a project pursued by WeFindX to do it - a financial think-tank, where you can talk about the world's greatest challenges, suggest and discuss ideas to solve them, start and fund projects based on them and semi-automatically control the investments. The full description of the Infinity project is outside the scope of this article.

Habitation+

As our environments become more entropic (=polluted, noisy), especially in developing regions of the world, we need ways to protect ourselves from the entropy in foods, air, water, also from the communicable diseases, high or low temperature, and other negative factors. The traditional home and cars are expensive to do all that. The idea such as what I call home cell, connecting home and car into one, could solve the problem by providing an alternative that enables us to reduce the risk of death, pandemic, etc., and make human populations more flexible when it comes to relation to live anywhere on Earth as the climate continues to change.

The [capsulated habitation] paradigm has a potential to allow us to pack more sensors to monitor our bodies, and emergency systems to save them. Old people tend to die in beds. There is no reason why the beds shouldn't have sensors to predict such events, and take emergency actions. The home cell is an extrapolation of that, so that it would work where-ever we go.

Robotics+

Our hands is one of the key elements that allowed us to create all the technology on Earth. Right now, we already have prosthetic hands with tactile and force feedback. What would people do if we miniaturized the very same prosthetic hands, replaced the computer mouse with cyber-gloves, and allowed people from the internet do work by controlling these hands to make all kind of procedures at micro-level, directly from a computer game?

What if we could use smaller hands to create even smaller ones, and repeat the process? With abundance of people's brains able to control hands, we could fix a lot of things.

With micro-sized limbs, the game players could practice to do surgery to all kind of small animals like insects, worms, bugs, eventually reaching a point, where the nano-workforce is widely available to fix us dexterously and efficiently before we die.

Extropic Spaceship

Life is essentially an information proliferation process from cell to cell, from brain to brain, from computer to computer, producing new technologies, and counteracting the pressure from entropy, much like the nuclear fuel burning in the cores of stars produces force to oppose gravity.

How do we build that information rocket?

While we burn fuel and use 3rd Newton's Law to accelerate to the orbital speeds, life makes copies of information to propel itself in the field of entropy.

Idea 1 - Interfacing with Brains

An analogy of a rocket may be a direct connection from one brain to another via something like a high resolution sensory pixel matrix plate that is inserted and integrates with corpus callosum to enable our thoughts to flow across the brains of each others just as naturally as they flow between our left and right brain hemispheres. If the personality, memories and dreams were to remain in more than a single brain, we could save each other in one another through improved communication.

Idea 2 - Parallel Artificial Neurons

An analogy may also be a artificial neural cells, which, when injected into the blood stream finds other neural cells and attach around them, creating a parallel neural network, which has full bi-directional communication with the underlying biological one, and is able to provide wireless communication with external devices and brains, replicating our memories and personalities across many minds.

Idea 3 - Connecting via Virtual Reality

Use virtual reality to connect our abilities. The 3D Maze Idea.

Idea 4 - Freezing to Preserve Info

There is also cryonics, however, it would be more akin to a cold orbital parking rather than "propulsion" per se.

Idea 5 - Speeding Up Technological Singularity

A superintelligence, that evolves rapidly. That's what SIAI non-profit was started for in 2000s.

It is worth noting that the first rockets fall more often, and likely, if we start with (2) or (3), we might have only one shot, and it's important to solve superintelligence control problem before to make them safe.

Conclusion

We are information and we need new media, or we'll die. I provided a couple of ideas for new technologies, such as the education hypertunnels, force manipulators controllable via computer games, [habitation cells], corpus callosum junction and a couple of ideas of others to help prevent pandemic, deal with medical emergencies, create more reliable cryonics, and help organize and manage the investments into development of the ideas, to increase the chances that we create more reliable media for our minds to exist earlier rather than later.

Since there are ideas that would be useful to all of us, instead of taking over each other's cultures by using media to reprogram people as substrate, it makes much more sense for us to cooperate at all costs to create more capable media to hold, preserve, and let evolve for all of our cultures.

If we take action to share relevant information to relevant people sooner, relevant technologies will get implemented earlier, and our minds just might make it into a more reliable substrate to personally live and explore the Universe for billions of years to come, just like our DNA did.

So, think which part from here to share and with whom, and let's reach the extropic escape velocity together:

If competing entities like Russia, U.S., China, etc., intelligence agencies, competing corporations, and people in general realize that if we would invest more into medical, cultural and information technologies together, then we might literally save ourselves from death (which otherwise without assuming safe technological advances is imminent to most of us within the next couple of decades, which is a tiny moment at the geological timescale) by creating higher order substrate for our consciousness and our cultures to flourish, rather than trying to overtake each other as a substrate of information.

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<![CDATA[Open Knowledge, and its Risks]]>Today, we have many organizations that are striving to organize knowledge and make it universally accessible: Wikipedia, Google, Open Knowledge Foundations to name but a few. While this knowledge is good for empowering people to solve problems, there is risk that making procedural knowledge easily available to people will have

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http://localhost:2368/2017/01/03/open-knowledge-and-its-risks/5f8b9627abdc8a4be94a1cedTue, 03 Jan 2017 00:00:00 GMTToday, we have many organizations that are striving to organize knowledge and make it universally accessible: Wikipedia, Google, Open Knowledge Foundations to name but a few. While this knowledge is good for empowering people to solve problems, there is risk that making procedural knowledge easily available to people will have undesired consequences. For example, enable machines to self-replicate, or enable the creation of dangerous warfare. I'll talk more about the former, since the latter is quite well known.

The event of such autonomous self-replication could occur earlier than superintelligence, if some types of procedural knowledge are made available in computer-readable form.

Procedural Knowledge

First off, what I mean by procuedral knowlege?

Definition: Procedural knowledge is a representation of the outer world in an intelligent agent, such that the intelligent agent is confident that performing a certain sequence of known actions (programs) yiels a known result. This sequence of actions is to be called a procedure, the known result - a product.

Here, representation is the influence that the outer world had for the intelligent agent through the physical interactions ("education"); the intelligent agent is an entity capable of volition, cognition, action; confident means aware of high probability of success in yielding a result; known result - goal conditions to be met, known actions - actions performable by the agent (as script-like methods (procedures) are performable by an object in OOP).

The State of Today's Procedural Knowledge

Today most of the procedural knowledge is concentrated in the task management systems of diverse companies. Companies are using internal task management systems, as well as public (SaaS) ones, which are largely transparent to intelligence agencies.

The AI planning research is on-going in universities how to automate the planning of actions. The public sees the manifestation of such planning as the optimal road discovery algorithms in their driving directions. However, these same algorithms are being applied on other mathematical spaces, for example, the search of chemical reaction sequence to produce a desired compound (destination).

Each production machine, such as metal cutting, welding, etc. that makes something from something else is a piece of this know-how graph, representing a set of roads that can lead matter from one state to another.

Each manufacturing company, that makes something from something else, is a piece of this know-how graph too.

Almost surely such procedural knowledge map graph already exists. The theory is in our physics textbooks. The map is the databases of all tools available on equipment markets (Amazon included) with corresponding transformation functions for each equipment/device/tool (i.e., what transformations can the tool make to materials). Tools are no more than catalysts for shaping matter, therefore, even companies are tools to other companies. Each tool has properties, regarding what materials they can affect, and in what ways - these are the abstract "destinations" (vertices) of that graph, while the tools themselves are the "roads" (edges): G(tools,transformations).

There is no "driving directions" service to public, where you would enter a thing, e.g., "bolt", and it would output you roads (a combination of machines) to manufacture it, but it's highly likely such service exists.

The advanced (probably classified) research is highly likely to be carried out on using such knowledge to enable robots to mass produce the assets needed for military-industrial complexes. Such automation efforts are more likely to happen in the regions of the world, where human labor is scarce, IQs are high, and ambition to dominate the world is great.

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<![CDATA[MOOCs Could be Studied]]>"If something's important enough you should try. Even if the probable outcome is failure."

In other words, -- if value is large, the expected value is still large, even if the probability is small. Unfortunately, today, insurance industry is only considering the bad things of low probability that are important

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http://localhost:2368/2017/01/03/moocs-could-be-studied/5f8b9603abdc8a4be94a1ce5Tue, 03 Jan 2017 00:00:00 GMT"If something's important enough you should try. Even if the probable outcome is failure."

In other words, -- if value is large, the expected value is still large, even if the probability is small. Unfortunately, today, insurance industry is only considering the bad things of low probability that are important enough, not the good things. We insure against catastrophes, ill health, and car accidents. We don't insure ourselves from the extremely good things that could happen -- namely, from what would happen if we didn't miss an important invention or technological breakthrough. What happens if coming up with a viable cryoprotectant is 5 years earlier than it would be otherwhise without the inverse insurance incentive? What happens if emergency vascular pump is brought a year earlier than it would be without an incentivize?

These questions can be answered based on general statistics. 150K people die every day, and approx. 20K from ischaemic heart disease. So, these are the people we could save every day. We could compute very specific losses if technological breakthrough does happen earlier rather than later.

Prize foundations is a good start for such inverse insurance. However, this perhaps is not enough, and probably not the right way to do it. Usually, prize sizes are relatively arbitrary, depending more on the desire of possible donors than a rational computation of expected loss on an event. However, they could be calculated, based on expected loss with respect to early breakthroughs implementation, and be used to reward the economy. For example, many companies have hidden new products in secret "refrigerators," that they think the time has not yet come for the market, calculating when it will be the right time to release them. The inverse insurance could also be used to reward early releases of transformational products.

We could reform the insurance industry to insure not against, but for the early implementation of great ideas. And, an international "inverse insurance day" could be the day, when manufacturers massively release new not seen before products.

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<![CDATA[Universally Accessible Scholarships]]>Why it matters?

A possible scenario:

5 years later: we encounter unknown risk x. (e.g., a disease)

  1. UBI Scenario: the talent pool is not large enough, and we die.
  2. UAS Scenario: educated people quickly find a cure.

Problem

Artificial intelligence and robotization is projectedL to replace human labor

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http://localhost:2368/2017/01/03/universally-accessible-scholarships/5f8b95e0abdc8a4be94a1cddTue, 03 Jan 2017 00:00:00 GMTWhy it matters?

A possible scenario:

5 years later: we encounter unknown risk x. (e.g., a disease)

  1. UBI Scenario: the talent pool is not large enough, and we die.
  2. UAS Scenario: educated people quickly find a cure.

Problem

Artificial intelligence and robotization is projectedL to replace human labor in nearly every job. At the same time, we have a number world's challenges that need talent to be addressed - health, engineering, science, climate change, modelling the universe, and even arts to help express ideas and align political philosophies.

UBI: Universal Basic Income

The unconditional basic income (UBI) has been proposedL as a remedy for the technological unemployment. However, I am convinced that the UBI is unlikelyL to have significant impact on solving the world's pressing issues, including the problem of unemployment itself. The majority of people seem to think locally and short-term, thus without any guided incentives, UBI is unlikely to support the activities directed towards addressing the fundamental problems of society.

UAS: Universally Accessible Schlarships


MOOCs Could be Studied

A hope has been placed on the massive open online courses (MOOCs) to provide free or nearly-free education to peole. Unfortunately, MOOCs had failed to create the talent they promised, as their course completion rates remain low.L (below 5%?)

Talent Could be Created

The reasons are, perhaps, not that people do not want to study, but rather, that the time investment needed to learn and fully comprehend all the details in the MOOCs is prohibitive for people to do that.

If We Help People Learn

It stays a hypothesis, that if the MOOCs paid hourly wage of at least half of the minimum hourly wage in a country, there would be many people who would suddenly find the time to study, and eventually become experts in their fields of interest, eventually finding paid positions, or doing very useful paid work, providing value to society, and maybe saving our lives some 5 years later.

SUMMARY

I argue that the idea of Unconditional Basic Income proposedL (UBI) is sub-optimal for creation of the talent needed to address the world's emerging challenges. Instead, I propose the idea of negatively priced education as an alternative that provides the financial resources through universally available scholarships (UAS) to learn skills on the abundantly available MOOCs, which had automated the self-education process.

L: is a reference to "Link" -- meaning I had seen this datum somewhere on the Internet, and will add the link later when I find exactly where.

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<![CDATA[如何超级加速教育?]]>教育对单个个体和整体社会的全面发展很重要。你有没有想过将教育游戏化,使得受教育的过程更加愉悦?

之前在大学时有学习过现在很火的在线公开课,比如,Coursera,Udacity 。有的课无聊的让人昏昏欲睡。当我在一门课上几欲入睡,挣扎着强打精神的时候,我开始问自己:为什么一上课就变困?为什么看两个小时的侦探片的时候从来都不会困,上两个小时的课就那么难集中注意力?如何将看侦探片的劲头转移到学习上?于是我想到做个如下的3D迷宫游戏帮助孩子学习:

  1. 每个房间的墙上有理论,它的应用例子,提示等。
  2. 在每个房间之间有隧道,里面有门。门上有基于之前的房间的理论的问题。要解决门上的问题才能打开门锁。

我们不想停止看侦探电影因为我们想知道它的结局。在这样的迷宫中,玩家会想知道开锁门后会发现什么。这样我们可以创造一种类似侦探片中的悬念。

这个想法咋一看只是小孩的教育,但深入的考虑下去,它的潜在涉及各种人:小孩,成年人和老人,大学生和职场人士。它可以影响科技发展,加快我们治愈疾病的研究,提高我们控制超级智能的能力等等。想一想 – 随着孩子的长大,他们学会如何走路,如何开门。他们在成长的过程中要开多少次门!如果从小我们为了能开门必须要解决各种各样复杂的问题,那孩子的脑子将非常灵活。我认为通过这样的方式,孩子肯定可以比现在更早的学会如何解决各种我们在高中/大学学习的知识。实际上,2岁的孩子已经可以认识形状,数字。如果在虚拟环境中包括现实的东西上的提示(

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http://localhost:2368/2016/11/24/xmaze/5f8b9570abdc8a4be94a1ccdThu, 24 Nov 2016 00:00:00 GMT教育对单个个体和整体社会的全面发展很重要。你有没有想过将教育游戏化,使得受教育的过程更加愉悦?

之前在大学时有学习过现在很火的在线公开课,比如,Coursera,Udacity 。有的课无聊的让人昏昏欲睡。当我在一门课上几欲入睡,挣扎着强打精神的时候,我开始问自己:为什么一上课就变困?为什么看两个小时的侦探片的时候从来都不会困,上两个小时的课就那么难集中注意力?如何将看侦探片的劲头转移到学习上?于是我想到做个如下的3D迷宫游戏帮助孩子学习:

  1. 每个房间的墙上有理论,它的应用例子,提示等。
  2. 在每个房间之间有隧道,里面有门。门上有基于之前的房间的理论的问题。要解决门上的问题才能打开门锁。

我们不想停止看侦探电影因为我们想知道它的结局。在这样的迷宫中,玩家会想知道开锁门后会发现什么。这样我们可以创造一种类似侦探片中的悬念。

这个想法咋一看只是小孩的教育,但深入的考虑下去,它的潜在涉及各种人:小孩,成年人和老人,大学生和职场人士。它可以影响科技发展,加快我们治愈疾病的研究,提高我们控制超级智能的能力等等。想一想 – 随着孩子的长大,他们学会如何走路,如何开门。他们在成长的过程中要开多少次门!如果从小我们为了能开门必须要解决各种各样复杂的问题,那孩子的脑子将非常灵活。我认为通过这样的方式,孩子肯定可以比现在更早的学会如何解决各种我们在高中/大学学习的知识。实际上,2岁的孩子已经可以认识形状,数字。如果在虚拟环境中包括现实的东西上的提示(比如,键盘照片上写小点数),他们可以自己理解要做什么。比如,在门上看到了5个点,点击键盘上的“5”键。我编写了这个游戏的试玩版,并且在2岁的孩子身上进行过测试,她成功了解决3个门上的问题(关于数字,关于颜色,关于不同的颜色的数)。她妈妈想让我继续开发这样的迷宫游戏,但因为我要上学没有时间继续而搁置了。

随着时间的流逝,我越来越觉得这个想法很有价值:(1.) 我们可以在迷宫中添加作业题 (2.) 我们可以在迷宫中添加一些公司提供的实际应用遇到的问题。

这个想法是像“点击广告赚钱”,各种公司可以在游戏平台上上传问题,玩家在游戏里解决这些问题就可以有收入。当然好处不止于此。

海马体神经可塑性可以帮忙大人有像孩子的学习能力

我们都知道孩子有特别好学习能力。因为孩子的大脑的神经网络在不断发展,所以他们学新事物的能力很强。但长大后人的脑子变得不那么灵活。但根据最近的研究,成年人的脑子也有一些特别灵活的部分。

喜欢旅游的人可能有这样的经历,一天旅游后在梦到一天走过的路。其实,这个能力在人类进化上非常重要。其实,很多动物(鸟,哺乳动物等)对一些生存攸关的事情有很强的记忆力,比如哪里可以找到食物,哪里可以找到资源。

许多记忆力超常的人说他们通过构建情景来帮助记忆。1999年科学家们做了一项研究,测量了出租车司机的大脑。他们测量了刚刚开始工作的司机的大脑,以及工作两年后的司机的大脑。他们发现司机们的海马体显著增大了。[1]

那么,我认为如果我们在迷宫的墙上展示各种各样的图案/模式,应该可以帮助玩家建立关于所学知识的情景记忆,就像那些记忆天才一样。

满足社交需要

想一想:从一个房间可以有多个隧道到不同的其它的地方。玩家可以选择自己更感兴趣的方向。如果多个玩家自己选择更感兴趣的方向,他们最终会发现其他/她有类似兴趣的小伙伴。

我们都有兴趣发现特别的、我们喜欢的、跟我们有类似的兴趣的朋友们。所以,现代的世界很多人对社交网络上瘾。找朋友们是一种需要。社会网络满足它。

想想如果我们玩家解决了问题可以发现对同样领域感兴趣的朋友。比如,我对天文学感兴趣,去了那里,开始解问题,解决了之后在另一个房间发现已经解决它的其他玩家。因为这是一种办法能找到有相似兴趣的人,我觉得很多人解决问题的动机也可能为了发现朋友。

预防老年痴呆症

有老年痴呆症的亲戚的小伙伴都知道,一个人丢失回忆、甚或丢失经验多么痛苦。可是,最近的研究发现,开车的老人患老年痴呆症的机率较小。科学家发现,其实没有必要实际上开车,给老人游戏玩儿同样有效[2]。给老人在这样的系统里玩儿,就可能可以帮助其更长时间不发病。

设计

想像在某个森林,或者在城市附近的自然环境,好玩和舒服的地方,玩家开始走路探索,发现各种树洞,或者鼹鼠洞。试试进去就发现在里面的房间和隧道的迷宫,基于下面简单的设计。

我首先希望做个非常简单的,模块化的迷宫生成工具,为了老师们可以创造自己的课程,附加学习内容、视频、文章、问题等。我希望做个非常简单的、简约主义的程序,为了可以自动生成多种 织纹/大小/方向 模式的迷宫,而且为了浏览这个迷宫不需要太多处理能力。我选择的最简单设计是长方体系统。长方体的房间,而且在墙上可以挂上对象,比如图片、视频,隧道到另有一个房间。老师可以加房间,加隧道,在隧道里加门(=问题),在隧道的尾端挂上另一个房间,这样类推。为了每个老师可以简单地编辑它。我4年前编辑的测试系统就包括了这些功能。为了减少内存的需要,我们可以只加载邻近的房间而不是加载所有的迷宫。

现在,我觉得如果我们合并了上面描写的两个事,就可以做个更有意思的玩家。

为了一些更有意思和无法预测的体验,我们也可以随机化邻近的房间,这样每个玩家可以有一点不同的经验(一点像颗,如果了解下房间的材料没有必要学习之前的房间的内容,可以随机化,否则就像要预修课程,不太可以很多随机化)。

然后让各种各样的老师们和组织创造自己的子迷宫,连接到一个大迷宫。每个组织,比如,公司,可以有自己的子迷宫,而且为了进去这个公司的子迷宫可能需要先过去一些其它的迷宫。

其实,就好像现在组织对每次点击付费广告花钱,如果想在有多聪明人的迷宫附加自己的问题,组织可以对子迷宫的所有者花钱,就是每次解决问题开门付费迷宫可以给一个办法对玩家也赚钱。

启示

想象,在下一些十年,机器学习和人工智能技术,有可能会超过人的大脑的能力。我们有风险计算机会比人更《聪明》,而且人没有聪明到能够控制人工智能。现在世界有70多亿人在地球上。这些人就是我们的最大的资产。我们必须想出新的办法来合并我们的智慧,从而形成合作的力量,否则很快人工智能会比人更强大。

有些公司特别专注计算机的发展(比如发展计算机能力模拟大脑)。但是,为了帮人理解计算机,我们要多关注通信技术。这还不是全部的可能性。想想,未来我们可以请玩家做远距外科,或者控制无人机,设计东西等...

结论

这只是一个我们如何可以改善和提高人的能力解决问题的例子。如果我们有更多、更好的主意,早一点分享吧。教育是所有技术的基础,而这个想法是一个也许可以像真空管运输对运输业那样实现教育和工作游戏化。哪一个 “超回路列车”更重要——交通的,还是教育的 ?

[1] Eleanor A. Maguire, David G. Gadian, Ingrid S. Johnsrude, Catriona D. Good, John Ashburner, Richard S. J. Frackowiak, and Christopher D. Frith: Navigation-related structural change in the hippocampi of taxi drivers. PNAS, 1999.

[2] Preventing Alzheimer's Disease: Video Games May Help Seniors Retain Cognitive Function.

[3] 我的在2012年创造的测试系统

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<![CDATA[Staying in Control of AI]]>Decision Transparency

An important part of being rational is knowing one's goal, why one has it, taking actions maximizing the probability of achieving it, and being able to tell why one takes certain actions over the other. Our success in staying in control of AI clearly depends on how well

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http://localhost:2368/2016/06/25/staying-in-control-of-ai/5f8b9530abdc8a4be94a1cc5Sat, 25 Jun 2016 00:00:00 GMTDecision Transparency

An important part of being rational is knowing one's goal, why one has it, taking actions maximizing the probability of achieving it, and being able to tell why one takes certain actions over the other. Our success in staying in control of AI clearly depends on how well we as a whole, and well as each individual is able to control why one does what one does, and decide what one wants to do.

  • If you don't know why the search results are ranked the way they are, you should worry, because this ranking is part of your daily decisions.
  • If you can't know why a specific trading bot made a decision to sell stocks, resulting in thousands changing their jobs, you should be concerned, too.
  • If you can't know why a task management system at your work is recommending you to do task X that you do, you are out of control.

The AIs are already largely in control of corporate world, both at micro and macro levels, replacing middle managers, so probably:

  • AIs used for non-trivial human decisions should all be transparent and make sense: rankings, recommendations, trading, etc.

Tomorrow's Society

Tomorrow most people might live by working on virtual tasks in augmented reality, paid by businesses for works both virtual and real. People might live on basic income, become free to play most of the time. The majority of people may start putting on smart glasses the moment they wake up in the morning, and spending their day time sculpting new objects and writing programs for the augmented reality world. The data overlay to real world may become the new canvas. The traditional programming with keyboard and mouse may be replaced by precise typing with silent mouthpiece and hand gestures.

While free to explore most of the time, skilled people may tend to sign smart contracts, and have high penalties of not doing emergency tasks they are proficient at. There may also be popular incentivizing contracts that create smart bonuses for taking virtual courses to learn skills in demand.

Most people may come to love it, as they can freely meet people, live and travel almost for free in sacrifice of their privacy, not having full access to the data about their histories, their recorded experiences, full data about their search queries, etc. They might not know why and how the answers of their intelligent assistant are generated, and how the virtual tasks matched with their interests and location. In fact, most of them may not really care about it, since most of the time they would do tasks they like, by searching for tasks much like they used to search for videos to watch. They might enjoy the company of the constantly found new friends and game partners, and not lack the sense of meaning, because such systems could give them a story of why they live, a narrative, and an imaginary destination, with hopes to live longer, or perhaps even forever, which may motivate most of them to solve the problems in biotechnology, nanotechnology and other. While this is not necessarily bad, it is a concern that:

  • Most of this technology tomorrow may be closed, and the competitor companies like Google, Microsoft, Tencent may try to keep their recommendation and matching algorithms based on very private information of people's lives, a secret and a strategic competitive advantage.
  • Most people may not really know what these specific tasks belong to, for example, who are the patients whose telesurgeries they perform, and what ultimate goals do some micro-tasks actually serve.

It is not unfathomable that to moderate all this, there may be a small number of people who program the algorithms to distribute business problems to augmented realities for the vast majority of people serving interests defined by these large companies and businesses paying them to place problems.

What Could Be Done

There are many things that could be done to ensure that people stay in control of AI. One of them is passing transparency laws. If a search engine is part of daily decisions of most people, people should be able to investigate theoretical rationale, as well as source code explaining how it works, where and how the data is being stored, etc., or if a proprietary social network can decide the outcome of an election, the recommendation, ranking, and content injection algorithms should also be open.

  • The law at international level could be passed, requiring the theoretical rationale, the designs and software of AI systems be opened, if they are used as the basis for non-trivial human decisions, opening the access to the processes of defining their objective functions and optimization algorithms, as well as sources of data (with possibility to request access from the data sources) that are and were used to train the weights and set rules in decision models.

While such law might be against the incentives for corporations to profit from innovative algorithms, it may prove critical in making AI decisions transparent, putting humans at large in control of the AIs, not the other way around.

It may be relevant today, not tomorrow, because, as mentioned above, we already have AIs deciding in markets and workplaces.

Note: although decisions of large corporations are largely transparent to the intelligence agencies, arguably, staying in control of AIs may need the transparency at individual level, for each of us individuals to know why one does what one does, and decide what one wants to do, and if it makes sense in the grand scheme of things.

Originally posted on https://wiki.mindey.com/topic/ai/DecisionTransparency.html

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<![CDATA[The $10bn Mouse Cryonics Prize]]>The central problem of cryonics is a bit like Fermat's Last Theorem -- easy to understand for a child, but hard to solve: how to freeze water without making it expand and break cells. So, let’s be bold — what about a $10bn cryonics prize to a team that freezes

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http://localhost:2368/2016/04/01/why-10bn-mouse-cryonics-prize/5f8b9504abdc8a4be94a1cbdFri, 01 Apr 2016 00:00:00 GMTThe central problem of cryonics is a bit like Fermat's Last Theorem -- easy to understand for a child, but hard to solve: how to freeze water without making it expand and break cells. So, let’s be bold — what about a $10bn cryonics prize to a team that freezes a mouse brain, keeps it under a cryogenic temperature (below −180°C) for 24 hours, and then brings back the mouse to life?

Why?

We're getting there

In 2016, Kenneth Hayworth’s Brain Preservation Foundation awarded its one-time Small Mammal Brain Preservation Prize to an organization called 21CM for successfully freezing a rabbit brain in “near-perfect” condition, with the cell membranes, synapses, and intracellular structures intact. According to Hayworth, this is the first time a cryopreservation was provably able to protect everything associated with learning and memory.[1]

The idea was to “use glutaraldehyde-based fixative, then slowly perfuse increasing concentrations of ethylene glycol over several hours in a manner similar to techniques used for whole organ cryopreservation. Once 65% w/v ethylene glycol was reached, vitrify brains at −135 °C for indefinite long-term storage.” (link).

And this actually worked, so there’s a reason to believe that by thinking in analogies, we could come up with less aggressive chemicals to ensure brain preservation in-vivo.

$10bn?

This number small. Roughly 150,000 die every day, and insurance puts human life value approximately at $8.5 million each. If only 1200 lives were saved, this would pay off the prize. If anything, the probability of this event to happen in a year in the next few years is so small, that expected loss is accordingly, perhaps billions of times smaller than $10bn, so what do we have to lose?

Pooling Insurance

Even if your organization could insure that, it’s a global problem that matters to all. Insurance industry could cooperate on pooling resources, and marketing the prize. It’s a simple problem to think about, most kids of the world would be able to think about, because they can understand water expansion upon freezing, and a brilliant idea could come from anywhere in the world.

Would you like to see this happening? Forward the idea!

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<![CDATA[Will Deep Learning Be Monopolized?]]>Artificial neural networks are a kind of cognitive memory. They are memory, because they save information in terms of weight distributions, but they also work as processors, exchanging information between units, and updating weights - recognizing patterns and learning.

Considering that there are companies today working on new kind of

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http://localhost:2368/2016/03/10/will-deep-learning-be-monopolized/5f8b94d2abdc8a4be94a1cb5Thu, 10 Mar 2016 00:00:00 GMTArtificial neural networks are a kind of cognitive memory. They are memory, because they save information in terms of weight distributions, but they also work as processors, exchanging information between units, and updating weights - recognizing patterns and learning.

Considering that there are companies today working on new kind of processors emulating neural networks (e.g., RPUs), I would expect, that soon computers may start having something we could call cognitive memory units (CMUs), a new kind of hybrid between RAM and GPU, implementing powerful artificial neural networks.

Will GPU computing power be monopolized?

Today, GPU computing power can be easily turned into money by mining coins, solving Kaggle or stock market prediction problems without much mental effort of your own. Given their power in automating very tangible, real tasks, like coming up with strategically superior moves in global political game, there are all incentives to compete in monopolizing the deep learning by amassing the GPU computing by every superpower in the world, to execute their political agendas.

Who is going to be in control?

Today, we have hand-helds owned by individuals, but supercomputers owned by governments and large organizations, used to do all kind of tasks, including track and control individuals.

Unlike with programmable computers, someone who comes up with a better general-purpose learning system, is likely to go the way of AlphaGo — beating all other political opponents in the strategic global geopolitical game.

Once we start having CMUs, it is worth considering the consequences. People may get CMU power in their smartphones, however, considering that the vast majority of such cognitive power would belong to large organizations, it is a danger, that these organizations would be outsmarted by their own supercomputer, which then takes over the world.
Unlike Bitcoin, which has alternatives (in case of >50% attack), organization that gets to own more than 50% of the cognitive power, is likely stay there un-dethroned, like one that had taken out the genie from the bottle.

Controls on GPU market

Considering that computational cognitive power is likely to be treated like commodity, the GPU power is susceptible to blind buy-ups by the establishment, and some controls are necessary to ensure equal and fair access to GPU computing power (and CMU computing power in the future), anti-monopoly laws, and safeguards to regulate computing power distribution.

In addition, something like a resolution about Universal Human Rights To Computing Resources may also be important, because with the exponentially increasing computing power, it is only a matter of time, when almost every human mental task will be possible to automate: just like today computers are better at mining bitcoin, tomorrow, they will be better at coming up with ideas and ways to control muscle movements to produce valuable goods, and thus, without human rights to computing resources, humans will be irrelevant.

Will the Internet save us?

Considering the number of people’s brains carrying energetically cheap computers — human brain, I think, a real thing that can help us retain control over the computers for a little longer, is forming a connected mind through communication power of the Internet.

Even today, we could easily create an app for people to cooperate (read books, etc.) by enabling them to share screens of smart phones, code together, and cooperate in virtual game worlds, and especially, exchange objectives and ideas about them more efficiently.

Improving the communication between people’s minds on the Internet obviously could enable them to collaborate much more efficiently, and may help to keep A.I. safe.

So, will deep learning be monopolized?

It could be, but there are steps take to decrease the likelihood of it —

  1. control the GPU (and CMU) power distribution and market,
  2. implement equal human rights to computing power (test: does everyone have enough power to mine bitcoin?),
  3. improve communication between people’s minds, such as smart phone screen sharing, and virtual collaborative learning technologies, direct neural interfaces.
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<![CDATA[A Future Without Buildings, Schools and Jobs]]>A world without buildings

You probably don’t imagine a life without buildings. However, buildings for living may become as obsolete as horses for transportation. They have many shortcomings:

  1. Buildings are not good enough in protecting people from communicable diseases (second? highest risk to mankind!)
  2. Buildings are inconvenient to transport
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http://localhost:2368/2016/03/10/a-future-without-buildings-schools-and-jobs/5f8b9413abdc8a4be94a1ca5Thu, 10 Mar 2016 00:00:00 GMTA world without buildings

You probably don’t imagine a life without buildings. However, buildings for living may become as obsolete as horses for transportation. They have many shortcomings:

  1. Buildings are not good enough in protecting people from communicable diseases (second? highest risk to mankind!)
  2. Buildings are inconvenient to transport from in cases of emergencies (think about the ease of migrations after global warming!)
  3. Buildings prevent people from free exploration of planet surface (think of sleeping every night of your life without seeing stars, because of your ceiling!)

So, imagine a capsule hotel on the wheels. Not an ordinary one, but of a shape of honeycomb cell, so that one or more of them can connect into a larger structure. Moreover, imagine the chassis which allows the capsule move horizontally like a car, or vertically like on a segway. Wouldn’t that be cool to be able to explore cities like that, and then to sleep in a bed with a transparent ceiling and see the real stars above before at nights, then see whatever beautiful landscapes in your office during the days in vertical position, and connect into larger spaces with your friends during the day for play and socialization? For me, it would be! There are just too many good friends whom I can’t live together with, because we are on different parts of the world, but I would love to spend more of my time with them, and an automated slow, safe driving algorithm could take care of organizing our meetings automatically.

But it’s just a tip of the iceberg of what such cells could do. Everyone of us would be fully protected from dangerous pathogens by filtering air, water and controlling nutrients. We would be able to live for prolonged times close to any medical facilities when we anticipate the need. Dedicated servicing pipelines could allow people’s bodies to be medically serviced fast, and at low cost.

Moreover, — just replace the chassis with propellers, skis, and you have an amphibious vehicle. Attach robotic arms to our cell, and we can safely perform some actual field work.

Would we still really need buildings? Probably, just like monuments like pyramids today.

I’m serious. It’s happening some time in the next 10 years, if not someone else, and if no better idea is suggested, then I’m doing it, and you can join me (hivecell@mindey.com) — mankind can live like one family.

A World Without Schools

Today people hardly can imagine society without schools. However, due to the Internet and mobile devices, knowledge for doing could become as ubiquitous as air, and current education systems have shortcomings:

  1. Schools don’t provide knowledge we need right now (I wanted to build a spaceship since kindergarten, but when I went to elementary school, they didn’t teach me physics and astronomy. They answered astronomy would be 12 years later, but there was none, it was omitted from curriculum.)
  2. Schools usually do not compensate for time spent (And people do need resources to live. With automation of jobs, there will be increasingly more people who need to go back to school. Wouldn’t it be great if school paid for time, like jobs do? It’s better than universal basic income if you think.)
  3. School home assignments usually are not fun! Let’s face it — schools where knowledge is broadcasted down to pupils is an out-dated concept. We know it doesn’t really work. What works — is computer games, and games in general. One possibility to imagine — a 3D computer world, which is a maze of rooms and tunnels. From initial environment, it could look like a beautiful meadow, where we could have entrances, like mole-holes, tree hollows, caves, and other portals to mazes of different kind. Each with a different flavor and appearances, which would attract people of different personalities — some pitch black, and some colorful.

Imagine then, that once one enters a maze, one would start bumping into the doors, which are locked with various problems — some with puzzles of simple pattern recognition, some with mathematical puzzles, some with art puzzles, yet others with science experiments, and social interaction puzzles, to cover broad range of possible initial interests.

Once a player unlocks a door, he or she meets others who had lead the path, can see their trails, and sometimes meet them. Moreover, imagine that the players can look see video materials, and various messages on the walls of the virtual 3D mazes.

Imagine that eventually the problems would get harder, but the study material in form of 3D objects, videos on the walls, and other media inside would become increasingly helpful and close to real life.

Moreover, imagine that solving any problem gives rewards not just of curiosity, but also, of real money, so players actually play and learn for a living from the very start.

Imagine that at some point deep in the mazes, the problems start being so close to reality, and the players who navigate those remote places — so proficient — that if you add a real problem on a place in the maze, a player is highly likely to solve it, and such solutions bring real value to society. For example, figuring out a new molecule that could bind to a cancerous cell site, or analyzing some complex data to extract important features, or quickly figuring out how to deal with a fast-spreading virus (human computing).

This would be as fun to play as it is fun to watch a detective movie and exploring a social network, because of finding new people with common interests.

Would we still need schools? Probably, just like Hyperloop has revolutionized long-distance transportation, so will hyper-educational tunnels revolutionize education.

It’s happening some time in the next 10 years, if not someone else, and if no better idea is suggested, then I’m doing it, and you can join me (studymaze@mindey.com) — we can enjoy love for learning and exploring in virtual worlds like one home together.

A World Without Jobs

Today most of us cannot imagine society without jobs. We are used to living on wages from corporations, each pursuing its own profit interest. However, this has shortcomings:

  1. Closed corporate pursuits creates a danger of creating competitive super-intelligence (a top existential risk to mankind!)
  2. People work on things that are not the most important (high reward low probability projects are important!)
  3. Humans and their organizations are commodified and made to compete wasting resources rather than being enabled to cooperate to work on the best ideas together via the Internet. (Just like the neural systems allowed life to find optima in seconds where an evolutionary process would theoretically require deaths of many generations of competing mutants, — similarly, by fully utilizing the Internet creating new communication technologies, could enable ourselves to find optima by thinking systematically together in the level of ideas, without subjecting individuals and groups to the unnecessary competition that currently poses a threat to global security. [Mindey’s comment to Max Tegmark’s post from FLI on the wisdom race.])

However, due to the automation of production of goods needed for life and new models in rational global decision-making, we are going to be free to do what we love, and where we are likely to be able to contribute the most at any given moment — we will do works, just like we make comments on social networks — on topics we care about, and will get compensated in terms of real credit.

In fact, with WeFindX, I’m working on this type of solution — we call, The Infinity Project — to enable this kind of collaboration. It is a work in progress to create a model to explain everything, work together, and share work results fairly. If you are interested in cooperation, write us, or me directly (infinity@mindey.com), and we’d love to work together to create a better future for us all.

Mindey, 2016–03–10

P.S. I think buildings, schools, and jobs may still be quite important to people in the next 5 years, just like vinyl records and radio, we don’t see them go away any time soon. It’s just their relative importance, that will diminish over time, and banks investing in real estate should start thinking of this today — the loss of value of buildings is coming. We’re living in transformational times.

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<![CDATA[AI Goals and KPIs]]>If you look at the modern world, perhaps the closest thing to formulation of goals for an AI is the formulation of KPIs of our companies — our artificial social intelligences. They sometimes go wrong. For example, a company may choose maximization of total time spent on site, rather than the

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http://localhost:2368/2016/03/02/ai-goals-kpis/5f8b9492abdc8a4be94a1caeWed, 02 Mar 2016 00:00:00 GMTIf you look at the modern world, perhaps the closest thing to formulation of goals for an AI is the formulation of KPIs of our companies — our artificial social intelligences. They sometimes go wrong. For example, a company may choose maximization of total time spent on site, rather than the people's time well spent.

The very reason why people use KPIs, is that money is not good enough an abstraction of our goals, which are complex and expressible only in an evolving diversity of assets.

How organizations define KPIs?

People have centuries of experience defining KPIs for their organizations. With a few searches on-line, you may find, that some of the modern abstractions are:

Image credits: Bryan Cable @ Transportation Insight.

However, this is just a start. There is a whole Universe of things with respect to which to define what we want.

Every even tinyest dot in this image, is a galaxy, not to forget the mathematical universes and all potential futures of individual experiences of every one of us...

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<![CDATA[个人故事,无穷项目!]]>                                        以《“让我们所有的梦想实现! ☆”》之心!
                                                  由[Mindey]撰写,2015年9月
                                                                [翻译,草稿]

背景问题

问题1 - 知识获取!

2005年的时候,我的继父希望我可以去找一份工作。但是我非常不喜欢“为钱而工作”,我喜欢“为实现梦想去工作”。其实像很多人一样,我也知道几乎所有我们需要的东西都在被工厂制造,然后我们花钱去购买它们。但是我对如何去创造它们更感兴趣,而不是去考虑如何赚钱去购买。所以我决定要去学习如何用时间和物理学去创造它们。对于这一点,我需要新的知识。
次偶然的机会,我看到维基百科在2003年的时候,用新的集体编辑模式整理了世界的语义知识,我认识到了我们应该也可以用类似的方法,整理并提供世界通用的程序性知识(办事的操作步骤),而且这本来就是我最初的想法,事实上在我很小的时候我就希望可以全世界有一种通用的程序性知识。 我花了很多时间思考如何提取并转化为程序性知识。因为有大量的知识都是隐藏的“诀窍”,由于某些因素创造者无法进行分享,我希望把可以共享的信息提取出来,并分享给感兴趣的人。

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http://localhost:2368/2015/09/15/infinity-story-cn/5f8b93afabdc8a4be94a1c9dTue, 15 Sep 2015 00:00:00 GMT                                        以《“让我们所有的梦想实现! ☆”》之心!
                                                  由[Mindey]撰写,2015年9月
                                                                [翻译,草稿]

背景问题

问题1 - 知识获取!

2005年的时候,我的继父希望我可以去找一份工作。但是我非常不喜欢“为钱而工作”,我喜欢“为实现梦想去工作”。其实像很多人一样,我也知道几乎所有我们需要的东西都在被工厂制造,然后我们花钱去购买它们。但是我对如何去创造它们更感兴趣,而不是去考虑如何赚钱去购买。所以我决定要去学习如何用时间和物理学去创造它们。对于这一点,我需要新的知识。
次偶然的机会,我看到维基百科在2003年的时候,用新的集体编辑模式整理了世界的语义知识,我认识到了我们应该也可以用类似的方法,整理并提供世界通用的程序性知识(办事的操作步骤),而且这本来就是我最初的想法,事实上在我很小的时候我就希望可以全世界有一种通用的程序性知识。 我花了很多时间思考如何提取并转化为程序性知识。因为有大量的知识都是隐藏的“诀窍”,由于某些因素创造者无法进行分享,我希望把可以共享的信息提取出来,并分享给感兴趣的人。因此,我在大学学习数学的过程中,以及在任何的活动中,继续思考如何把程序性知识来简单化。我希望可以把它提供给非专业领域但是对它感兴趣的人甚至是儿童,然后我写了这个

只是这类知识的提取就是一个不小的挑战:我们可以尝试通过逆向工程,把每一次创造的各个环节递归打破。比如在创造新东西的同时生成说明文档,描写人们所有创造活动的方法。让感兴趣的人了解整个过程,包括使用的是什么工具,通过怎样的步骤,最终得到了什么样的结果。但是这会需要大量的时间,于是我开始问自己 如何可以自动化记录这些方法和流程,同时如何最大化其教育的价值?换句话说,就是如何让知识提供者快速记录信息,让每个感兴趣的人都可以轻松地了解所有技术的工作分解结构

程序性知识的表达也是一个挑战: 每个人的原始知识储备情况和需求目标都不相同,所以不存在适用于所有人的一种方法。比如有人简单的问“如何制造一辆车?”,不同的人有不同的需求,他们可能问的是不同车的制造方法,这导致我们需要根据每个提问者原始知识储备的差异,给出不同的做法,同时需要匹配每种车的制造方法。假设世界上每个人都感兴趣车子是如何制造的,那么我们应该有(包括) (7 x 109)2 种可能的答案(假设全球70亿人口,只存在2种原始知识储备的差异。但我们知道,事实上对于原始知识储备的差异远不止2种),这个集合还没有包括不同车子制造工艺的差异性,它将是一个非常复杂的计算难题。

1现在情况→  ◯  ◯  ◯
2现在情况→  ◯  ◯  ◯      ← 通用的答案
N现在情况→  ◯  ◯  ◯
                            ↑     ↑     ↑
                           人1  人2  人N  
                           目    目   目
                           标    标   标
                           情    情   情
                           况    况   况

(通用的答案应该提供方法如何从任何的“现在情况”得到任何的“车”)

那么我们应该怎样分享“如何制造一辆车”这个知识呢?

幸运的是,现在的人们习惯了记录和完善。我们有标准的计量单位和换算方法,我们可以利用技术图纸和物理定律来记录和开发流程,可以依据反复试验来完善方法,可以通过故事的方式来分享“如何制造一辆具体的车”。每个企业都有他们所有产品详细的创建流程,不管是什么行业。因为记录过程也是为了更好的标准化制造以及完善,所以每当有新的项目开展,人们都会把它分解到步骤,生成工作分解结构。我们只要想办法收集和分享这些工作分解结构就可以了。 这个假设成为了我开始建立程序性知识表达的关键。我从很久以前(2005年)便开始建立一个维基,用来收集这种工作分解结构。比如我收集的关于哥伦比亚号航天飞机的建设步骤。

通过创建无穷项目,我希望更多的人可以分享(提供和使用)这些程序性知识,让每个有兴趣的人都知道如何没有钱也可以用时间和物理学生产他们看到的所有的东西。

问题2 - 众筹难点

2001年我家里有了永久可以在线的互联网服务。我发现了一个名为'Halfbakery.com'的地方,它是一个从1998年到现在一直非常活跃的一个创新论坛。人们在这里分享疯狂的创新想法,激烈批评和分析它们,尝试去验证你的想法是不是真的,是不是新的,享受这个过程中的快乐。如果他们找到在世界上已经存在了的想法,就会说它是"baked",意味着你输了(不是新的想法)。我从使用它的第一天就迷上了它,以后的每年我都会提出很多想法。可是虽然我很喜欢讨论这些想法,但是我更有兴趣通过实现想法来支持自己的生活。可是,遗憾的是没有人愿意为这些创新的想法去付钱。

就这样过了许多年,直到诞生了KickStarter、IndieGogo和其它的众筹网站。可是创新者和发明者们无法通过简单的方法获得支持实现想法的资金,为了得到资源,他们不得不花费金钱和大量本该专注工作的时间来创造有吸引力的原型、有说服力的专业视频和营销活动,为了更好的展示自己的想法给可能的投资人,为了获得更多的资金支持。

可是不管是多么好的想法,如果没有一个原型,它甚至不能进入众筹平台。但是创造一个原型需要的时间和资源是巨大的,大多数人不一定有能力放弃工作去实现自己的想法。很多人离开工作一两个月就会很拮据,这个时间也许还只是在完善原型,是不是可以被众筹,是不是有人愿意买单都还是未知数。所以他们没有勇气去实现自己的想法,因为这对他们来说风险太大了。其实我在最后一次尝试去做一个原型的时候,为了可以专注的完成它,我甚至退出了读博。我相信任何和我有一样经历的人,都能感同身受我说的这些。

没有原型的想法在KickStarter和Indiegogo这样的平台上不能得到资源,这是一个大问题。因为愿意在KickStarter和IndieGogo这样的平台上投资的人更像是商人,他们需要快速看到优秀的里程碑,需要立等可取的盈利。而我则希望获得有共同理想的投资人进行注资,想法不需要精美的原型和冗长的宣讲来进行包装,投资人可以共同讨论和提出其他建设性的意见,而不是仅仅做金钱的交易。我们需要热爱思考、富有想象力,即便没有图片和标准的原型也可以理解我们想法的人。就好像是那些愿意在 Halfbakery.com、LessWrongEverythingList 等智库上交流和思考新概念的人。

其实像智库那样的社区实际上是存在的,并且发展的很好,在我看来这类社区只是缺乏如何简单安全地在网站的讨论板上公开分享资源,如何激励资源分享和资源完善的方法。从而我想到如果可以在发布和评论中增加货币交易,让资源提供者获取信息流通后的价值,通过有偿使用信息的方式,不仅可以促进社区的活跃,也可以带动更多愿意思考的人贡献更多有趣的想法(谁不愿意在思考的同时获得金钱的鼓励呢)。我计划在评论中加入“可编程资金管理交易发生器”,通过科学的算法去计算用户的贡献价值。

我希望通过创造无穷项目,让有理想的人们花费最少的时间(不需要原型,不需要视频,不需要图片)利用这些想法去赚钱。

问题3 - 如何在一起!

自从我开始寻找女朋友,我就知道如果两个人没有共同的目标,就一定无法走下去。我在寻找可以跟我一起研究科学和一起创新的人,并用这种方式表达互相的爱。我需要热爱科学,数学和编程的人,因为我觉得们可以帮助很多人实现梦想。

但是我每次遇到对科学或数学感兴趣的朋友时,他们常常会因为工作的劳累或者公司的保密政策,使他们不想在休息的时间谈论关于科学和数学的话题,或者无法进行信息的分享。

我不喜欢这样,我想可以有大量的时间与我的好朋友们一起思考关于创新的想法,思考如何实现令人振奋的新系统和新发明。 但是朋友们大多数的时间都要去工作,而且这些公司不愿意把自己的成果与外界分享。另外随着年龄的增长,有些朋友有了自己的家庭,他们需要把下班之后的时间留给家人。

为了解决这个问题,我想到了一个方法,那就是让我的朋友们可以开放式工作,让所有有相同兴趣的人成为一个大家庭,这也是我希望通过无穷项目实现的目标。我希望通过创造无穷项目让我的朋友们可以离开朝九晚五的工作环境,可以自由开放的去实现他们想实现的理想。

前景问题

问题1 - 下定义世界的梦想

在我十几岁的时候,我自私地想着“如何让大多数人为了我的目标而工作?”,我想到了一个解决方式 - 需要找到一个目标,这个目标符合大多数人的需求,这样大家就会为了实现共同的目标进行合作。因为多人合作比独自完成会更有效率,我用了很长的时间来思考这件事情。

如果我们希望世界有一个好的目标,那么我们需要先定义“好”和“坏”的标准。在我看来“好”就是让世界可以保持存在的事情,而“坏”就是会摧毁世界的事情。这标准里面的“世界”表示万物(指宇宙内外一切存在物)作为一个整体,以及它的每一个无论大小的实体(比如人、蚂蚁、细胞等)。

这个标准暗示了,我们需要创造一种状态,使每个实体都可以存在,而且可以充分表达它的性质。后来我想出一个更具体的方式来描写它,就是“创造一种状态,使我们实现心中的梦想”。这个描述验证了“真心性”,即每个实体要把它的意识延伸到全部实体(万物),用来验证这个实体的想法确实为心之所向。比如如果我们身体里的一部分细胞可以思考(或者创造一种可以思考的细胞),它们会考虑究竟是希望杀死宿主还是促进宿主的成长(因为细胞和宿主之间是相互依存的关系,没有宿主细胞也会死去)。我觉得如果我们身体的细胞之间可以有良好的沟通,它们便可以更有效的对待病症(细胞的心中所愿)。

通过创建无穷项目,我希望可以通过创造允许人们公开追求他们真正想要的东西的条件来定义一个事实上的世界的目标。

问题2 - 创造友好人工智能!

现如今,为了增强竞争力,几乎每个大型组织都会去搭建自己的人工智能。

然而,这些公司的行为不一定都是正向的,不一定对所有使用者都是友好的。大多数公司和组织并没有向产品使用者表明他们全部的行为(是否具有某些隐藏属性、是否是友好的),使用者几乎不清楚这些公司和组织他们的自动化业务决策系统是基于什么标准来实现决策的。

如果某家公司拥有一种强大的人工智能系统,它会比其他公司更有生存力和竞争力,并能传播开来。

因此,我认为与其秘密地做自己的个人或公司系统来实现自己的目标,不如开发一个公共的、开源的、包含风险管理的系统,也许这样会更好。

通过创建无穷项目,我希望创建一个开放的风险管理体系。后期可以通过对访问数据的收集兼并开发推荐系统,从而创建一个友好、开放、无隐私和可以自我解释的人工智能系统。这样所有的信息可以在更大的范围内回报需求者,而不是只为某些组织服务。

问题3 - 全球语言障碍!

考虑到不同语言之间可能存在的沟通障碍,为了使无穷项目更好的服务于不同语言的使用者,为了更多人可以更顺畅的交流想法,无穷项目将会实现语言互译,这个互译可以是自动翻译,也可以是互助性质的人工翻译。

无穷项目的设计

世界(X)=梦想!
     F(X)=Y

为了解决知识获取的问题,我总结出一种“从需求到工作”的工作分解方法。它们分别是:

需要   目标      思路         计划            步骤               任务                  工作

解释

需要 - 任何的人或者组织想要任何的事情或者东西的时候,他们用一些基础的概念来描述它,这些基础的概念指经济资源即资产(资产=任何东西或者事情)。在无穷项目中,“需求”代表实现这些资产的条件。

目标 - 任何的人或者组织在定义他们的需要的时候,他们需要为经济资源(资产)定义目标条件集合(Y),比如 Y: 0 < Y < 2(矢量不等式,Y为资产向量)。在无穷项目中,“目标”就意味着这样的条件集合。

思路 - 每当这些人或者组织想出实现目标的想法,实际上他们通过假设动作(X)对世界(F)产生影响得到属于目标的域(Y)的 F(X) 值。在无穷项目中,“思路”就意味着方程式的解(X)。

计划 - 每当他们制定出一个计划,实际上是他们想出了一套具体的动作。这个计划就是具体的技术(X)步骤,从而可以生成一个动作链(x1、x2、x3、xn)。在无穷项目中,“计划”就是将工作进行分解。

步骤 - 当他们想出具体步骤(xm)的时候,实际上他们需要拿到一些资源,然后把这些资源换成相应的交付成果(ym)。在无穷项目中,“步骤”就是资源兑换成果的过程。

任务 - 当他们清楚任务后,他们为了实现成果(ym),会做一些具体的动作Z。在无穷项目中,“任务”就是指具体的动作。

工作 - 这些人在做一个任务的时候,实际上是在进行可行性的实践z’,这种实践需要交付具体的结果(工作证明)。在无穷项目中,“工作”就是指对可行性的实践。

所以在无穷项目中,我们提供内容类型和数据库结构两种方式来实现这个“需求到工作”的分解。因为这些工作分解都是公开的,所以我们希望用户可以通过看这些工作分解来学习如何创造任何东西。并且在学习的过程中他们会理解创造的过程就像解决数据方程式F(X)=Y一样。

为了解决众筹的问题,我设计了“交易发生器”,即用户可以在平台上自由进行虚拟交易(贡献者可以售卖自己的想法)。因为之前我长时间活跃在halfbakery上,我发现它只是通过用户投票的多少来描述想法的优劣,并在每个想法前面加上面包(好的想法)和鱼刺(不好的想法)的标志来等级化它们。我希望可以做的更多,比如让有能力实现这些想法的人去实现它,激励那些有好的想法的人去分享。

如果20个朋友可以下定义交易发生器每个月发给500人民币为了一个朋友做什么他们喜欢的项目,那这个在做项目的朋友可以有10000人民币一个月,就应该可以营生。这些交易发生器应该可以解决长期收入为长期项目的问题。

为了解决如何在一起的问题,我计划创建一个开源的系统,所有人都可以去自由的使用它。一旦这个系统开始运行,我们就可以开放的去工作,公开的分享我们的成果。我希望最终我们会模糊公司和家的概念,让所有人共同去进行创造和生活。为了保证交易记录的安全性和完整性,我考虑使用区块链技术,将相关信息永久的记录下来,这样每个人都可以去验证哪些工作是由谁来完成的。

为了实现梦想,我努力去创建个公开透明的系统。我计划开源全部的源代码,并且创建开放的API接口, 这样每个人都可以在使用的过程中去修改和完善它。

关于创造更友好的人工智能,我计划用统计和人工智能技术来处理数据,从而达到一种完全透明的方式。每个人都可以看到我们正在优化的东西、使用了什么算法,以及计算全球风险,并将其计算为每一项目标的每种资产的概率分布。

为了解决语言障碍问题,我开始用一种跨语言的概念图,用定义和概念来代替单词,描述人们的需求。所有的内容类型都有它们的“语言”字段,因此,编写新条目的用户可以半自动地选择所写的语言。这就可以将不同局域网的使用者聚集在一起。

无论如何,这个项目是一项正在进行中的工作,如果您有任何好的意见和建议,欢迎随时告诉我。

                                                                            ∞

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<![CDATA[Personal Story, The Infinity Project]]>                                             In the spirit of “Let Everything Exist! ☆”

                                                           By [Mindey], 2015, Sept.

                                                                        [draft]

Background Problems

Problem 1 -- The Knowledge Acquisition

In 2005, due to the lack of resources my mother's second husband was telling me to go get a job. However, I strongly disliked the idea of 'work for money'.

]]>
http://localhost:2368/2015/09/01/infinity-story/5f8b9358abdc8a4be94a1c95Tue, 01 Sep 2015 00:00:00 GMT                                             In the spirit of “Let Everything Exist! ☆”

                                                           By [Mindey], 2015, Sept.

                                                                        [draft]

Background Problems

Problem 1 -- The Knowledge Acquisition

In 2005, due to the lack of resources my mother's second husband was telling me to go get a job. However, I strongly disliked the idea of 'work for money'. I highly liked the idea of 'work for ideas', so I started viewing all things as subject of making rather than subject of receiving for money. Like many, I knew that things are made in factories semi-automatically, so, instead of thinking how to make money for a living, I got absorbed into thinking how to automate the production of everything what I need for living. For that, I needed knowledge.

Seeing how Wikipedia had around 2003 organized the world's semantic knowledge suggested that we could do the same with the procedural knowledge as well, and here is my initial idea.

I spent much time thinking how to extract and represent the procedural knowledge. Large amount of which is the hidden "know-how”, which I wanted to make widely available. So, during both my undergraduate mathematics studies, as well as in the further occupations, I continued to think how to do it in such a way as to make it easily accessible to both children and adults. A result is this paper.

The extraction of such knowledge alone presents a challenge: we could try to obtain it by reverse-engineering things recursively breaking down every thing into its components and asking what tools were used to manufacture them, and breaking down each of the tools into their components, and repeating so until the tool='ancient stone tool'. However, it would require enormous amount of time. So, I asked myself -- how to document all the mankind's creation in the process of making in such a way as to maximize its educational value, i.e., how to make everyone easily understand the work breakdown structures of all technology?

The presenting the procedural knowledge is also a challenge: there is no universal way to describe how to make something, because every person’s situation and desired outcome is different. I mean, a simple question like 'How to make a car?' has ~(7x109)2 (Cartesian product of initial states and desired states of every person, if all of them want it) of possible answers. It becomes infeasible to cover them all. So, how do we share the knowledge of how to make a car?

Fortunately, people are good at copying and modifying, and we can explain how to manufacture things by using the conventional units, drawings and the laws of physics, and to answer the question 'How a specific car was made?' is possible by simply sharing the exact story. Every specific company has a story how they built what they built, so the answer to a question of how it was made is unique and existing. Moreover, every time someone does a project, it is generally decomposed into milestones along the way, producing some understandable work breakdown structure, we just need a way to collect them and share.

This was the keyhole for me to start creating the desired knowledge representation, and long ago, I started an initiative to assemble a wiki of such decompositions like in this remaining wiki. You can look at an example there on how the Space Shuttle Columbia was made.

By creating Infinity Project, I am trying to represent the procedural knowledge openly in public, so everyone can know how to make things they see, even without money.

Problem 2 -- The Entry Barrier

In 2001, when I got the permanent internet at home, I found a place called 'Halfbakery.com'. It was and still is an active community of innovators, where people actively criticize and dissect ideas, and have fun in the process. I was hooked since the first days of using it, and the number of new ideas was increasing over the years. So it was nice that we can discuss ideas, but I wanted to make a living from working on some of them, however I had no resources for that.

And although after many years now we already have systems like KickStarter, IndieGogo and others, but we have to spend much time and money to create attractive prototypes, convincing professional videos, and the marketing campaigns to present ideas to the crowd of laymen.

Unfortunately, ideas, no matter how brilliant, usually don't make it into crowd-funding platforms without prototypes, and when people generally are one or less salaries away from being broke without a job, they simply cannot afford to invest the time to making the prototype. The last time I tried to make a prototype, I had to quit my PhD studies to focus on it, and just for one idea. Consider someone who has hundreds of ideas that they want to realize, and they have a problem.

The problem is that ideas without prototypes don’t get funded on KickStarter or Indiegogo, because investing people who come there are visual, instant-gratification driven individuals. Therefore, the ideas (unlike prototypes) must be evaluated and funded by different kind of people -- people who read books, who can imagine, and who need no pictures to visualize ideas. It is a different kind of crowd, the crowd like on Halfbakery.com, LessWrong.com, EverythingList, where people like to talk about concepts.

The fact that such communities exist suggested that what we are lacking are the opportunities to easily share resources in our conversations online, and thus, the idea of transactions inside comments was born. The idea evolved into what people could use to direct and manage the cash flows right from within their comments by programmable transaction generators.

So, by creating Infinity Project, I am trying to create the conditions for people to make a living from working on ideas they love, without the marketing barrier.

Problem 3 -- The Being Together

Ever since I started looking for a girlfriend, I knew that we would break up unless we share the same goals. I looked for someone with whom we could engage in science and create together, and with whom the creation be expression of our love. I needed someone who loves science and mathematics and programming, because I viewed them as probably the only viable means to achieve anything of true significance.

However, whenever I would find a girlfriend, who said she was interested in science, or mathematics, it was often that she would not want to talk about it, mainly because the day of work would make her tired of thinking about it, and made her just want to rest or do something else after it. Moreover, the NDAs and company policies prevented her from sharing inside information with the outside.

Such situation did not look good. The time of my best friends, which they would love to spend ideating and working on new exciting systems and inventions is bought up by corporations which don’t readily share the joy with outside. Moreover, those who had families, had almost no time for friends at all, because after the day of work, they are have their family time instead.

Wishing more stimulating creative engagement, I saw one way -- to create an opportunity to free my friends by enabling them to work directly in society without the middle-men like corporations -- making mankind into one family.

So, by creating Infinity Project, I am trying to create the conditions to allow all of my friends to quit their jobs, and start working on what they love, and be together.

Foreground Problems

Problem 1 -- Defining world’s goal

As a teenager, I thought selfishly - how to get everyone work on my goal? The solution was clear - come up with the goal that everyone wants to realize, in that case, it would be logical for everyone to cooperate on it (more precisely, it would make sense for everyone to cooperate, if the thing that everyone wants the most is easier to get by cooperation than for any subset of people to get it on their own). I thought of it for a long while.

If we want the world’s goal to be a good one, we have to define the criterion to separate “Good” from “Evil”, and I came up with such criterion, specifically, “Good” is to create conditions for the World to exist, while “Bad” is to destroy the World, where the “World” is defined as the Everything (universe, multiverse,...) as a whole, as well as everything as its every no matter how small or large entity (a human, an ant, a cell,...).

The criterion suggested, that the ideal is to create the conditions, where every entity can exist in the full expression of what it is. I later came up with a more specific, formulation - to create the conditions where everything that anyone truly wishes would come true, which should theoretically be possible without a conflict, because the wording “truly wishes” implies the necessity to extend one’s consciousness up to the global identity to verify that what one thinks one wants is truly the thing that one wants. For a simple example, if there was a “wise cancer” (or wise growth), it would consider if it truly wants to grow as much as to kill its host. I think, if we had more open communication between the cells, they could inform each other better, and be aware of the contradiction their true wish (just like we are hopefully are aware in the case of CO2 emissions.)

By creating Infinity Project, I am trying to define a de-facto world’s goal by creating the conditions that allow people to openly pursue what they truly want.

Problem 2 -- Creating friendly A.I.

Every large organization today is effectively creating AI-augmented corporations and states.

However, corporations and states have been observed to conduct unethically, and not benevolently to people. There is no guarantee of responsibility, sentience and friendliness of a corporation or a state in general. Moreover, it is not entirely clear what particular goal is a particular corporation’s automated business decision-making systems are driven by.

We run a risk, that if some single corporation comes up with (or evolves) a strong A.I. that is better at survival than others, it outcompetes all others, and spreads.

So, instead of secretly doing one’s own personal or corporate system to achieve its goals, I think, for the sake of creating a friendly A.I., it could be much better to develop a public, open-source, risk management and planning system that’s acceptable, understood, and desired by all.

By creating Infinity Project, I am trying to create an open risk management system, which, extended with the statistical learning and recommendation systems on its data, could work as a friendly, open, non-hidden, self-explanatory A.I. system that optimizes the returns globally for the world, and not just for some closed organization.

Problem 3 -- Global language barrier

Today, the world still has no common human language, and it lacks cross-talk between the people in different countries who are interested in the same topics. Currently, there does not seem to be a common system focused on general problem-solving, that supports concept and topic mapping across multiple languages.

By creating Infinity Project, I am trying to create a place where people to cross the language barrier, when talking about problems and their solutions.

Design of The Infinity Project

World(X)=Dream

F(X)=Y

To address the B.1 (background problem 1), I came up with the hierarchy of content types that could explain to all how things are made. Specifically, I observed that everything that was ever made by people, was driven by people’s work to satisfy their needs, and that everything that was ever constructed, could be broken down to the following decomposition:

  • Need
  • Goal
  • Idea
  • Plan
  • Step
  • Task
  • Work

Explanation:

Whenever someone wants something, they conceptualize it in terms of some concept, which refers to some asset class Y. Whenever someone says that they want something, they specify conditions for the instances of concepts (assets y) they refer to, e.g., 0 < y < 2. Let's represent a condition as a Need, and a set of such conditions as a Goal.

Whenever someone comes up with an idea to get what they want, they effectively had come up with some principle to influence the world F by some hypothetical actions X, to satisfy the goal’s inequality by equality F(X) with value within those conditions. Let's use word Idea to refer to such a solution.

Whenever someone comes up with a plan, what they did, is they came up with a concrete set of actions using some technology to realize the hypothetical actions X as fully or partially ordered set (x1, x2,..., xN). Let's use word Plan to represent such a decomposition.

Whenever someone comes up with a milestone xM, what they did, is they had just set out to take some amount of resources and convert into some likely corresponding deliverable yM. Let's use word Step to represents such an assumption.

Inductively, a milestone can be subdivided to arbitrary depth, until a non-divisible ("atomic") step is reached. Call that step a Task, and it's deliverable, - a Work.

This provides a generic framework for the design of the Infinity Project, where we simply have content types for each of these categories, believing that, if people can publicly see the decompositions of work this way, it will be natural for them to understand how making of anything was a piece of math to solve F(X)=Y, and to understand how it was done by looking at the decompositions, and learn and understand the society like we learn software code.

To address the B.2 (background problem 2), I came up with an idea that people could control their money by making them part of their speech in comments. Specifically, I was fed up with the fact that we just get buns on Halfbakery, and not the real money, so I first came up with this idea, and then extended it to the idea of programmable transaction generator within comments.

If 20 friends can set up transaction generators that send 100 EUR per month for some friend to do something, e.g., work on some project, then one could easily get 2000 EUR/month for a living. The transaction generators would solve the problem of long-term income to work on long-term projects.

To address the B.3 (background problem 3), I tried to make the system open to everyone, so that, once society starts working this way, we don’t have closed corporations and families, and my dear friends can actually share their work in open. To assure that contribution record is not tinkered with by people who have access to database, I am thinking of applying blockchain technologies, to make the record of someone making some contribution, public and permanent, so that everyone can verify that some work was done by someone.

To address the F.1 (foreground problem 1), I tried to make the system public and transparent. I plan to open-source the project, and make open APIs, so that everyone can fix the issues along the way.

To address the F.2 (foreground problem 2), I plan to apply statistical and A.I. technologies for data generated by the people in a completely transparent way, so that everyone could investigate what we are optimizing, using what algorithms, and what for, and compute global risk down to the probability distributions of every asset concerning every goal.

To address the F.3 (foreground problem 3), I started defining the people’s needs in terms of concepts rather than words by using an interlingual concept map, the OmegaWiki and (soon) WikiData. All the content types have their “Language” field, so a user who is writing a new entry can semi-automatically choose the language, in which it is written. This allows to bring together speakers of different languages interested in the same topics to the same ground.

At any rate, this project is a work in progress. Feel free to give your suggestions!

                                                                       ∞

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<![CDATA[Why Logarithmic Thinking?]]>The impact of an idea is like the strike of an earth-quake, and I think we should have a “Richter scale” of magnitude for potential impact of ideas to compare them.
In a world, which is moving exponentially [1], it is important to have the right scale to look at

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http://localhost:2368/2015/03/10/why-logarithmic-thinking/5f8b92b7abdc8a4be94a1c8cTue, 10 Mar 2015 00:00:00 GMTThe impact of an idea is like the strike of an earth-quake, and I think we should have a “Richter scale” of magnitude for potential impact of ideas to compare them.
In a world, which is moving exponentially [1], it is important to have the right scale to look at innovation — a scale suitable to our linear thinking.

I think, just like the Richter scale, the scale measuring the impact of innovations should be logarithmic, and hence — the logarithmic thinking.

[1] http://www.kurzweilai.net/the-law-of-accelerating-returns

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