五千年(敝帚自珍)

主题:【原创】围绕脑科学而发生的若干玄想 -- 鸿乾

共:💬461 🌺824 🌵2
分页树展主题 · 全看首页 上页
/ 31
下页 末页
                          • 家园 熵=phantom, insider your mind

                            first of all, thx for the forbes piece, a worth reading, and that motivated me to do a follow up;

                            1.

                            "熵不是亂度或無序",

                            http://proj3.sinica.edu.tw/~chem/servxx6/files/paper_2862_1231474464.pdf

                            丁尚武

                            國立中山大學 化學系

                            2.

                            the above is a great piece, but far from the core of the white logic, which I have commented many times already,

                            90岁彭桓武:对爱因斯坦两段话,至今未能真正理解 [ 晓兵 ]

                            "concepts such as 系综, 么正性, gauge, 測度, 度規, etc, the key physics/math aspects of the core of the white logic,"

                            3."熵不是亂度或無序", then what it is?

                            3.1

                            熵=phantom, insider your mind, inside my mind

                            if I can borrow "phantom of the opera"

                            么正性, gauge, 測度, 度規=路徑積分 of phantom, insider your mind, inside my mind, inside of every "free soul"

                            in a 洛伦兹流形

                            after all that kind of "phantom shaking out", and sometimes in a possibly very bloody way, we may be able to have a clue/路徑 about the real phantom, or 伟光正, kind of the white's version

                            http://www.youtube.com/watch?v=VlRnzANjVZs

                            3.2 phantom= an open-ended journey

                            short term: until we humanity as a whole figure out how to exit from earth in the next 1k to 5 billion years

                            3.3 廣義相對論's phantom

                            "由於等效原理(Equivalence

                            Principle) 所要求的廣義座標協變性(General

                            Covariance),廣義相對論基本上有一個無窮大的規範對

                            稱(gauge symmetry),大到使得這個理論中不存在任何

                            規範不變的局域物理觀測量"

                            4. there is this the greatest ocean between the white culture/science and those of asia, and us china in particular, and one of the reasons for us Chinese's very narrowed culture/mindset's 光譜 is that we don't really have religion, science in our 6k years old Chinese culture, and I don't want to talk about that too much

                            anyway, the forbes piece is a good one, and I will read it and will have a better idea about the authors of that paper

                            5. a great piece, thx, Alexander Wissner-Gross, is going to make a lot of money with his models, good for him

                            6.

                            "From Atoms To Bits, Physics Shows Entropy As The Root Of Intelligence", overall a good piece

                            Anthony Wing Kosner does not know that "熵不是亂度或無序", understandably since 熵 is such an over abused term, still, he some how managed to get some of the major points of dr. Alexander Wissner-Gross's paper;

                            Anthony Wing's writing is still a great piece, but Anthony Wing Kosner of the forbes writer, a possibly yale art major, does not really understand "熵不是亂度或無序", 熵 as a critical concept

                            http://www.forbes.com/sites/anthonykosner/2013/04/21/from-atoms-to-bits-physics-shows-entropy-as-the-root-of-intelligence/

                            7.

                            now, let us "read" through Alexander Wissner-Gross's paper, with Anthony Wing Kosner's 科普, and my comments (many from my previous posts)

                            ---------quoted from Anthony Wing Kosner's piece about Alexander Wissner-Gross's paper-------

                            “Casual Entropic Forces,” that seeks to formalize the “deep connection between intelligence and entropy maximization.”

                            In short, everything in nature (our minds included) seeks to keep its options open. Instead of seeing entropy as a form of destruction (things falling apart) Wissner-Gross shows it to be a state of active play.

                            They see “intelligence as a fundamentally thermodynamic process,” where any given system engages in a “physical process of trying to capture as many future histories as possible.”

                            "Future histories? They mean possible outcomes. "

                            --my comment-------

                            my comment: I have commented so much about "canonical (平衡正則) system", and such a system is time invariant=future outcomes are already "included" in the system, 决战千里之外=千里之外 is already "priced in" in the model, with our ass fully covered, so we don't go out there naked and get f---ed from behind.

                            my previous post: if we can manage "1" part, we basically have system's 么正性,因果关系, 逻辑链条 established, in terms of defining 測度 with 機率 distribution in a well defined (L2 可积 mathmatically,or 位能場平方力 physics model wise) hilbert space, 冯-诺伊曼's 泛函, etc;

                            and such a system is normally called a "canonical (平衡正則) system", and within the system, we can calculate from 因 to 果, or from 果 to 因, classical 哈密顿系统辛流形, and going further into QFT under 相对论框架 , we could have 虚時間,实時間, 虚粒子,实粒子, off the shell, on the shell, and their 么正性,因果关系, 逻辑链条, etc;

                            ---quoted---------

                            Wissner-Gross explains that some important landmarks in human evolution, like the use of tools, upright walking and social organization, are dening behaviors of the human ‘‘cognitive niche’’ that spontaneously emerge through the entropic forces that his theory describes.

                            ---my comment--

                            Verlinde: gr's 引力場 emerges just as an entropic force, a thermodynamic model of 引力場

                            ---quoted---

                            Because these are principles of physics, though, humans are not particularly privileged. Any system that can be acted upon by entropic forces can become intelligent. A recent theory by Eric Verlinde, a professor of physics at the Institute of Theoretical Physics at the University of Amsterdam, suggests that gravity itself is not an elemental force, but “simply a by-product of nature’s propensity to maximize disorder.” In other words, a special case of entropy.

                            ---my comment: the above about prof Eric Verlinde is a good summary-------

                            ---quoted----

                            A second example (see bottom sequence above) Shows how a “hand” can use a “tool” to extract “food” from a confined space (too small for the hand to reach in.) Again, it is only through programatic movement “governed by simple principles of thermodynamics,” that maximize access to “future histories” (in other words, entropy.) “It actually self-determines what its own objective is,” says Wissner-Gross. “This [artificial intelligence] does not require the explicit specification of a goal.” In this, Entropica is different from most AI systems. Similar, perhaps, is the way that Expertmaker encourages users to play with example sets of their data using “small AI” components instead of the more conventional “big data” expert systems.

                            --my comment---

                            “It actually self-determines what its own objective is,” says Wissner-Gross===marketing to the non-theoretical physics phd market, understandably

                            I have wrote before, once a

                            a "canonical (平衡正則) system" is assumed and modeled, we can we can calculate from 因 to 果, or from 果 to 因,etc, the system's own objective=given already by 么正性, or 因果关系 as defined in a Hilbert space which it self is well defined by 冯-诺伊曼's 泛函.

                            for a system to survive: it has to use 最小作用量, with 最大范围( to get information, often "最大體積" in 洛伦兹流形) 积分, kind of like the plant's animal behavior you guys discussed, and we could call that as plant's 最小作用量原理 or plant's AI, and from plant's AI to 費曼路徑積分, etc

                            2.

                            if we can manage "1" part, we basically have system's 么正性,因果关系, 逻辑链条 established, in terms of defining 測度 with 機率 distribution in a well defined (L2 可积 mathmatically,or 位能場平方力 physics model wise) hilbert space, 冯-诺伊曼's 泛函, etc;

                            and such a system is normally called a "canonical (平衡正則) system", and within the system, we can calculate from 因 to 果, or from 果 to 因, classical 哈密顿系统辛流形, and going further into QFT under 相对论框架 , we could have 虚時間,实時間, 虚粒子,实粒子, off the shell, on the shell, and their 么正性,因果关系, 逻辑链条, etc;

                            ----------quoted--

                            And physics equations themselves are incredibly efficient descriptions of movement. Unlike traditional animation in which everything must be specified, a physics movement has a starting point and some initial attributes and the rest, including the end point, just happens. And not only does this take less code and less processing time, it also feels more natural because we recognize physics intuitively as the way that things in the world “just work.”

                            What we see here is a mathematical description of spontaneity, of freedom—of play. Wissner-Gross writes that these “maximum entropy methods have been used for… strategy algorithms [that] have even started to beat human opponents for the rst time at historically challenging high look-ahead depth and branching factor games like Go by maximizing accessible future game states.”

                            ---my comment: a good "marketing" summary about the white's "canonical (平衡正則) system" and the logic behind it--------

                            ----quoted----

                            It may be that it has taken us more than century to acclimate to the intellectual disruptions set in motion by Einstein. In classical physics, entropy is the enemy, something that tears down what we build up. But in the quantum world, the chaos of entropy is the vitality of life. And it reveals itself not in grand historical revolutions or world wars, but in our casual, everyday activities. We cultivate open minds not because we are liberal or conservative, young or old, but because we understand intuitively that it is a matter of survival—physically, emotionally and intellectually—to maximize access to future possibilities.

                            ---my comment---

                            I don't think "a quantum world" is in Alexander Wissner-Gross's that paper

                            overall, a yale-humanity/art major (my guess) can write such a on the money summary on Alexander Wissner-Gross's paper, is pretty amazing;

                            I remember I wrote here may be a couple of years ago, that 老美 is a 疯子 society, financed by a 疯子 economy, with a 疯子 culture/ mindset;

                            疯子=phantom of opera;

                            8. 老美=爱因斯坦场, full of 疯子 with many of 疯子=引力奇点

                            8.1

                            引力奇点- 维基百科,自由的百科全书 - 维基百科- Wikipedia

                            https://zh.wikipedia.org/zh-hant/引力奇点

                            引力奇異点,也称时空奇異点或奇點,是一个體積无限小、密度无限大、時空曲率無限大的點。 两种最 ... 線性化重力、後牛頓形式論、爱因斯坦场方程、弗里德曼方程 ...

                            8.2

                            (as I wrote before) 引力, everywhere, as we interact with each other, and the more we move, the more we contribute to 引力場 from our 自能場 we create as we move, and the stronger 引力場 make us move even more, a full interaction type of evil, non-linear, 无穷大 stuff, kind of challenging issues for GR's gravity quantization, how can you quantize something non-linear?

                            if someday we have a breakthrough in gravity quantization, everybody will double their life spans from 30k day to 60k day, so far, I think we die, because our brain can't handle gravity in today's social 引力場;

                            9.

                            老美=火車頭 of human civilization as we know, for the foreseeable future

                            and if EU can put its ass together and do some real work,老美 will 如虎添翼 to move world economy forward out of the current sluggish qeed growth;

                            and for tg: all tg needs to do is to 搭顺风车, what a lucky tg, and tg's n-代, 再活500年?!

                          • 家园 "爱因斯坦场方程的解是个场" :决战千里之外

                            1.

                            Verlinde全息屏 moves around and scans globally, SR, GR:

                            “We cultivate open minds not because we are liberal or conservative, young or old, but because we understand intuitively that it is a matter of survival—physically, emotionally and intellectually—to maximize access to future possibilities.”

                            2. "爱因斯坦场方程的解是个场"

                            once a few possibilities of future survival and growth are narrowed in, they have to be tested by GR

                            "愛因斯坦的廣義相對論看起來是一個

                            局域的理論。不過另一方面,由於等效原理(Equivalence

                            Principle) 所要求的廣義座標協變性(General

                            Covariance),廣義相對論基本上有一個無窮大的規範對

                            稱(gauge symmetry),大到使得這個理論中不存在任何

                            規範不變的局域物理觀測量"

                            http://phy.ntnu.edu.tw/~linfengli/articles/holography.pdf

                            廣義相對論無窮大的規範對

                            稱(gauge symmetry),

                            this is saying, as an analogy, that regardless of your local 規範, gauge, including those of tg, if a GR AI machine works, it must work in Beijing as well, after passing test and figuring out what was in that boston guy'mind in US, and then you lease out and move that AI machine to Beijing, then you have

                            中科院 folks come over and adjust 規範, gauge parameter locally, then you try out that GR AI machine on MR. Bo, and see through his mind and know what he is thinking when negotiating a guilty plea package, if he is still alive by then; and Bo surrendered after seeing him totally naked in the room, nothing in his mind the other side would not know.

                            3.爱因斯坦氣吞山河

                            but once out of 爱因斯坦's beautiful theoretical kingdom as described in the above, and for

                            those doing real 决战千里之外 folks, 引力場 has to be 量子化 to be a first step, in an actual and operational physics,

                            and 引力場 量子化 is still out of reach;

                            4.Verlinde全息屏

                            as imperfect and disputed as it is, is at least operational, and he leveraged on 热力学, which works pretty well once once 邊界條件, 初始條件 are given for a macro system, and there are tons of local systems in the social 引力場 as such, and Verlinde全息屏 is a good start to analyze those local systems;

                            5. I talk about tg only in the sense of Chinese culture and its 光刻 of our brain and the consequences, more and mostly from a social physics point of view, Chinese's social and political development in the next decade is almost a physics reality already;

                            5.1

                            more or less, we all have our brain 光刻 with local 光譜, 愛因斯坦的 sr, 廣義相對論 in a way is also 一個

                            局域的理論, 等效原理(Equivalence

                            Principle), and basically, 愛因斯坦 is telling us, hey, folks,

                            locally, you can only be as good as invariant under the Poincaré group, meaning we can not really see beyond our local 光譜 world ;

                            and for us Chinese, most of our brain are locally 光刻 by Chinese culture 光譜 for 6k years, and with that, no matter what 卷積 we try, most likely, we input, process, output 光 signals according the Chinese OS pre-installed in our brain, wherever we go, we are 炎黄子孙,

                            and that 炎黄's 光譜 range is statically observable and stable, fairly "narrow" in terms of 政治大事, and it may vary a little as those 炎黄子孙 moves around in today's world, physically or internet wise, but since their brain matter as developed over 6k years, there should be very little 色散, and their brain natural AI 本征譜/標量波動方程 should be able to handle those little 色散 stuff

                            and again from a social physics point of view, if you are a sys admin working for tg, you know how to touch those 炎黄子孙 's soft spot, making them work the way you want;

                            does white do that? more or less to some degree, but white knows how previledged and powerful a sys admin position as such could be, so, for their own sake, they have to hedge, 寡斷, instead of 壟斷, US 4 政委, etc;

                            5.2

                            and 愛因斯坦 was also telling us, the way we see this world is locally valid, logical, elevator's local life: 局部范围等效原理:引力=局部惯性系加速,and if you want to be more "robust", 狭义相对论 Poincare group always works, and other than that, most of the time newton/classical physics is good enough (we can explain 引力 as 局部惯性系(伽利略慣性系)加速) no gr sweating, happy local elevator life 4 ever, the physics of why we often feel good about ourselves locally;

                            but that good feeling is only locally valid, because there is a GR world, and within the elevator, we are always short sighted but still feeling good, because even the world is way beyond our local horizon, even we "see" it (but physically or mentally still stay within elevator to be local per GR ), we can still interpret what we see with our elevator logic, and everything remains the same, still no sweating;

                            5.3

                            but as I said before, our brain is actually pretty smart, and may be in the sense of 下意识, we somehow connect to the SR/GR's idea/concept that 光子运动不满足伽利略相对性原理, and there may be an issue with 伽利略相对性原理 and its titanic 伽利略 ship;

                            and since 光子 is really important as our brain food, we can't afford messing up with 光子运动, that is perhaps why intuitively we do have 危機感 some where some times, and we are always out there trying to learn something, we want to "grow", we just don't know what/how to learn.

                            5.4

                            but if we can really figure out GR and manage jumping out of our locally 光刻 brain box, a brave and beautiful new world will emerge in front of us, and that is why I said, if we can figure out this GR AI, our brain will be able to interact/新陳代謝 with GR's world and get GR energy injected into our mind body.

                            did prof yang say that he feel totally 青春换发 when he married that 28 young gal?

                            that used to be an emperor's privilege, with GR AI, those non emperor folks may be able to see their 后宫·甄嬛传 come true as well.

                            6

                            but how to jump out of our local 光譜 world ? 愛因斯坦 gr, gauge field theory;

                            and now Verlinde is saying, hey folks, I have a 全息屏, try that and tell me how do you feel

                            7.

                            socially and commercially, a GR AI is basically saying, hey, folks, if you pay and have me,

                            I will help you jump first into that brave and beautiful new world once it emerges, so you don't miss out

                            一部分人先富起来 's dream coming true window, often with a very short time horizon, then it get entropy maximized out, and inflation, and everybody becomes a millionaire, no 后宫·甄嬛传 any more

                  • 家园 智力=catch it as it emerges

                    or models the system's 引力 as it emerges, and in a 剃度場 as such, 剃度 gets eaten up live by system's 自由能 almost @light speed, with entropy maximized, and then 黄花菜都凉了

                  • 家园 费曼路徑積分 vs 马尔可夫模型: ant AI

                    the paper you quoted is a good one, worth reading a couple of times and the referenced other ones,

                    in terms of their methodology:

                    1) getting information at system level or field level, are we near or moving towards a "canonical (平衡正則) system"? or field analysis of the ant folks

                    2)

                    then do "path" analysis to get further into operational level, such as how many path, and which path in terms of 測度 / 機率 density distribution, the ant is moving around, and once we have those information, we could tell ant: baby, we have got you.

                    1. 溫度 is a system level concept, and normally you can only define and measure 溫度 near/towards a "canonical (平衡正則) system"

                    2. once we have 溫度, we basically can do partitions @energy level, calculate entropy etc, with the subject heat system modeled and assumed as a heat 标量场, with 动力学 tricks such as 梯度, etc

                    3. the following article gives shows the common methodlogy behind

                    费曼路徑積分 vs 马尔可夫模型

                    as the auther said, 在量子电动力学的振幅是复number/complex number的,with 幅度和相位,可靠性马尔可夫模型 only deals with 实number and there is no 相位;

                    but with a lower order approximation of a "canonical (平衡正則) system" of the 可靠性 analysis , the author could still 積分疊加 all the 马尔可夫 path, as in 费曼路徑積分

                    ---------

                    . a google translation

                    所以,在这个简单的可靠性模型的上下文中,最低阶近似中,我们可以表示沿每一个可能的路径的转移速率的总和的产品的转移概率。不用说了,有更好的方法来评估的概率马尔可夫模型,但这种原油技术有趣的是,由于它的相似,至少在形式上,振幅在费曼的量子电动力学方法的过渡产品的总和。另一方面,也有一些显着的差异。首先,在量子电动力学的振幅是复杂的,既具有幅度和相位,而在可靠性模型的转换率是纯粹的实部和没有相位。第二,我们考虑的是可靠性模型,而专门的,在这个意义上,每一个路径从一个状态到另一个包括相同数量的单个转换。例如,从状态1到状态8的每个路径包括正好是三个转换。正因为如此,最低阶近似的贡献各路径的时间是相同的顺序为每个其他路径。

                    Feynman's Ants - MathPages

                    mathpages.com/home/kmath320/kmath320.htm

                    According to Feynman, the second ant follows the first path, but sometimes .... The lowest-order approximation of the probability of State 5 is given by the integral ...

                    ----------------

                    Maximum entropy production and the fluctuation theorem

                    FREE ARTICLE

                    R C Dewar

                    Show affiliations

                    Tag this article Full text PDF (127 KB) View as HTML

                    AbstractReferencesCited By

                    Brightcove logo

                    CrossRef logo

                    PMC logo

                    Google scholar logo

                    Nature blogs logo

                    CiteULike logo

                    Mendeley logo

                    Connotea logo

                    LETTER TO THE EDITOR

                    Recently the author used an information theoretical formulation of non-equilibrium statistical mechanics (MaxEnt) to derive the fluctuation theorem (FT) concerning the probability of second law violating phase-space paths. A less rigorous argument leading to the variational principle of maximum entropy production (MEP) was also given. Here a more rigorous and general mathematical derivation of MEP from MaxEnt is presented, and the relationship between MEP and the FT is thereby clarified. Specifically, it is shown that the FT allows a general orthogonality property of maximum information entropy to be extended to entropy production itself, from which MEP then follows. The new derivation highlights MEP and the FT as generic properties of MaxEnt probability distributions involving anti-symmetric constraints, independently of any physical interpretation. Physically, MEP applies to the entropy production of those macroscopic fluxes that are free to vary under the imposed constraints, and corresponds to selection of the most probable macroscopic flux configuration. In special cases MaxEnt also leads to various upper bound transport principles. The relationship between MaxEnt and previous

                • 家园 Atoms and bits

                  Bringing Computational Programmability to Nanostructured Surfaces

                  https://vimeo.com/62119585

          • 家园 这个信息很好。我猜想他们基本上是这样做的

            看了一下介绍,我猜想,基本上他们做的就是,建立一个基本的方程,这个方程可以对各种输入的方法计算某种值,他们称这种值为熵(熵是一个大筐子,什么都可以往里面放的),如果有几种输入的选择,他们就选熵小的(或者大的)那种。这样一来,就显出,更加智能的选项,其实就是熵小的选项。这些输入的方法,是面对一个问题可能的应对方法。

            他们的那个基本方程是什么?他们的软件是什么?就不得知了。谁能看到文章,来介绍一下。或者把PDF放出来。

            如果真是如此,那么,有可能他们的那个基本方程或许很有助于各方面的理解和建立更好的工具。

            具体一些来讲,我们前面提到,要建立感受与反应的测定,来看那种感受与反应的智能程度更高一些。或许他们这个基本方程就已经提出了这样的测定。这是有可能的。如果真是那样的话,我为我们的讨论高兴一下。我们感受到了比较前沿的研究了。

      • 家园 研究植物的智能是正确的路线

        类似的路线包括研究胎儿和新生儿的智能(发展心理学),原始人的智能(人类学),病人的智能(临床心理学),动植物的智能(智能进化论?)等等。可惜今天主流的研究集中在MRI什么的上面,就像Chomsky说的,有用,但是是死胡同。

      • 家园 百度的消息在这里

        http://memeburn.com/2013/04/baidu-goes-in-for-deep-learning-with-silicon-valley-china-ai-labs/

        http://www.wired.com/wiredenterprise/2013/04/baidu-research-lab/

        大概是借美国最近的AI热闹劲,搭便车吧。我提到百度是针对matt的说法美国这股AI热是骗人的,不过显然百度并不是这样看的,当然也许百度也被忽悠了,呵呵。

        这个视频很好,看到植物根部活动那里,甚至有个错觉这不是类似神经系统的样子么,似乎一个很强烈的暗示在片子里就是植物的智能活动不但是存在的,甚至于动物的智能很可能是在同一个原理的基础上存在的。

        这个片子给我个人带来的启发是在于把植物的行为用视频记录的方式展示出来,虽然这个都了解,但是真正看到还是会有不同的感触的。一直以来,我对植物的趋光性有个错觉是以为类似那个有名的“用进废退"的原理,但是在快速视频下观察,这实际上用“行为”来描述更准确,生长的确是植物的“运动”方式。另一个启发是概念的理解与直观(intuition)对我们大脑的感受还是不一样的,文字与PPT的区别也有类似的道理。

        一个猜想是,这个所谓的“智能",是不是就是植物大分子级别上的复杂化学反应慢慢进化而来的呢,以致最终出现了一个整体上的“行为”模式,本质上是一种复杂的机械原理,甚至从人眼中看去,总有一种”智能设计"的感觉,就是那个“智能设计"教的教义,扯远了。

        也许这种复杂的化学反应基础上的机械构造复杂到一定程度就出现大脑了,但是机制都是类似的。 视频中那个反应机制比较复杂的烟草类植物,因为可能相隔数百年才发芽生长,因为环境的不可预期性,因此进化出具备多重防御手段的体系,灵长类的大脑是不是也因为迁徙的原因,需要应付多变环境而进化出比较复杂的具有学习能力的反应系统-大脑呢? 对应鳄鱼那个例子,如果亿万年的环境都不变化,或者变化很小,那么依靠遗传基因作为学习与产生应付手段的机制也许自有其道理。

        • 家园 鳄鱼:亿万年的环境都不变化,或者变化很小=和諧

          1. bad mouth on Chinese culture

          6k years of social and humanity environment, any fundamental changes? I don't know, but with an example:

          a tg retired senior (don't know how senior he is, likely minister level(retire @65) guy had a casual talk with me at a casual place here in US, not long ago, not knowing each other at all, so no any "risk", and we talked about tg's accomplishments and tg's strategy going forward, and specifically he talked about 和諧

          2.和

          2.1 禾, left side, food, economy;

          2.2 口

          right side reasonable free speaking political environment , politics;

          禾+口=人民 happy

          He told me, and my comment, that is pretty much a farm management system model for 牲口

          3.

          "鋤和日當午,汗滴禾下土,誰知盤中飧,粒粒皆辛苦"

          =Chinese economy, politics, culture, language's 本征態, 静质量,惯性?

          4. now china is a 世界工厂

          but the Chinese culture is deeply in our blood system, and one of them is

          中央 vs everybody else, and 中央=伟光正, everybody else follows 中央

          I have written here before about the Chinese's 家文化, 中央=家長,家長 can 挣钱养家=great, big deal;

          家長 out outside with 貌美如花 little 2 or 3 younger ones=ok, no big deal;

          and in 中央's mind=we are the elite, no question asked, 天之骄子, 天 used to be universe,now 天=china, but sometimes tg dreaming about asia as well, when weather is nice

          5.

          if one wants to have a change in a system (a system with its known 本征態, 静质量,惯性,etc), one needs a great deal of energy with possibly 量子化条件, and to

          质變, we need to have 相对论高能条件, where and how?

          6.

          with great china fire wall further enhanced by tg's military power with 相对论高能 capabilities for the foreseeable futures, if not 4 ever:

          where and what will be the ”智能" of the Chinese nation and people as a whole?

          that is why I said 北京共识 model is a fake, the worst part of it being the waste of human capital

          what could be more valuable than human capital?

          how could china contribute to and possibly lead the humanity's civilization development?

          • 家园 天之骄子 super lucky

            1.

            first of all, tg as a super human organization=super smart, no questions about that;

            2

            past=history, going forward: white's old social, economic 測度 broke down (technological progress=high unemployment with low capacity utilization for almost every sector of the economy, and tg keeps making it worse, and now start suffering the result as well, the so-called tg's 后发优势 model, etc), new white 測度 model is still in thinking lab, if any; so qe 測度 for now;

            seeing that, tg is smiling from ear to ear..

            --------

            社会场 is a non "canonical (平衡正則) system" by definition: if nothing else, humanity needs to figure out an exit(from earth) strategy within next 1k years, where is the exit strategy? no, so all the social "canonical (平衡正則) system" basically=garbage, humanity crying for innovation, growth, hating entropy!

            物理学家 knows that too, but all their "AI", "么正性,因果关系, gauge, 測度, 度規" models are all pretty much based on all kinds of "canonical (平衡正則) system" and their various "wave" derivative forms, with no or weak interactions, they know very little about "full interaction model".

    • 家园 纽约时报的报道:很清楚看见脑的活动

      纽约时报的报道:

      外链出处

      有了这样的工具,就可以:

      Scientists at Stanford University reported on Wednesday that they have made a whole mouse brain, and part of a human brain, transparent so that networks of neurons that receive and send information can be highlighted in stunning color and viewed in all their three-dimensional complexity without slicing up the organ.

      然后,就可以实时地观察脑的活动,那样的话,很多秘密就解开了。奥巴马当局前段时间宣布的科技投资,正好这个技术出来了。

      看那个第二个视频,很有意思。这是用的那个荧光技术吧。

      • 家园 大脑CPU是平面二维的吗?(猜想)

        下面都是胡扯的。

        原始的神经细胞是从原始的表皮细胞转化来的(这是我胡扯的)。

        神经细胞其实是表皮细胞的一个特化。

        神经细胞的原始功能就是以层为单位进行联系的。虽然有时候看起来是“束”,其实还是个卷起来的层。

        大脑的最高级逻辑单位,是大脑皮层,其实是以二维平面方式来组织的。可能其他功能结构会分布在不同的层上。但本质上,一个层是一个功能逻辑单位。不同层负责不同的功能,相互之间可以互相索取信息,但一个层是一个逻辑完整单元。

        我们知道人的大脑是比动物的表面积增大,链接增密,而不是增大体积。(当然体积也增大,但其本质是表面积增大)

        大脑皮层是通过增加表面积来变得复杂强大,通过在本层之间建立更密集的链接来增加复杂的逻辑。也就是说,进行逻辑的时候,只在本层平面进行,而不是立体交叉进行的。就像是个表面积无穷大的硅片表面。

        假如这样的话,那么大脑比我们想象得要简单。

        ×××××××××××××××××××××××××××××××

        我们假设有个无限大的平面硅片。上面有无数的小开关。这些小开关的链接通断,就可以形成任何的逻辑和记忆。这些开关通断既可以形成逻辑也可以形成记忆。但不能同一块地方既是记忆又是逻辑。

        ×××××××××××××××××××××××××××××××××

        我们知道,生物学中的很多东西,都是反复折叠使用的。蛋白质过去以为是立体的。其实是一条一维的长链反复折叠形成的。DNA也可以看作是两条长链形成的结构。

        我猜测这种反复折叠以增加复杂度的方式,是生物是某种偏好。大脑皮层也是由一个单一的二维膜,反复折叠形成的。虽然看起来是个立体,逻辑上还是一层二维膜。

        ×××××××××××××××××××××××××××××××××××××××××××

        本初,原始的神经索的拓扑结构,是上皮细胞形成的一个像小肠一样的筒状膜。这个基本的拓扑结构我认为一直都没有变过。

      • 家园 你的 理解相反 。

        本篇文章的 目的 是 不需要做连续切片,然后重构大脑的三维结构。 而是另外一种技术, 完整的观察整个大脑的结构。

        这个时候 大脑也是固定的。 通过化学处理了。

        • 家园 一个很有趣的信息

          前几天听了一个讲座,是一些未公开的数据.使用双光子显微镜直接观察活体小鼠大脑皮层锥体第5层神经元的突触,发现fear conditioning所导致的learning and memory行为学,竟然与spine数量的减少正相关,而随后进行了fear的消除模型,发现某些消失的spine在原始位置(+-2um处)出现了复生。

          很有意思的现象。

分页树展主题 · 全看首页 上页
/ 31
下页 末页


有趣有益,互惠互利;开阔视野,博采众长。
虚拟的网络,真实的人。天南地北客,相逢皆朋友

Copyright © cchere 西西河