主题：【原创】围绕脑科学而发生的若干玄想 -- 鸿乾

1.

"How Particle Physics Can Improve Your Netflix Recommendations" ---see attached

2.老美疯子

http://www.ccthere.com/alist/3808130

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/hashing out", and sometimes in a possibly very bloody way, we may be able to have a clue/路徑 about the real phantoms (n>1, as a hedge), or 伟光正s, kind of the white's version

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

3. 永胜=决战千里之外 in Erik Verlinde 's holography world--Verlinde全息屏

a follow up on prof Verlinde's "holographic screens" (全息屏, Prof li Miao's translation) model, based on that model, Dr. Alexander Wissner-Gross did an AI app, a great one, and looks like more and more physicists are breaking into social sciences field now, with their physics models.

I was reading Verlinde's "On the origin of gravity and the laws of Newton"

http://link.springer.com/content/pdf/10.1007%2FJHEP04%282011%29029.pdf

basically, as I wrote in

http://www.ccthere.com/alist/3808130

Verlinde全息屏= 引力場=溫度場, 量子化=溫度梯度化

3.1

Verlinde全息屏= 引力場=溫度場

classic physics: 溫度 system's partition function is defined without 相互作用, without 引力, and this is where Verlinde made his smartness in modeling 引力場 as 溫度場, smarty as he is;

basically 引力場=信息場=溫度場, in the context of 第一性原理, Born-Oppenheimer approximation, etc:

"The universality of gravity suggests that its emergence should be understood from

general principles that are independent of the specic details of the underlying microscopic

theory. In this paper we will argue that the central notion needed to derive gravity is

information. More precisely, it is the amount of information associated with matter and

its location, in whatever form the microscopic theory likes to have it, measured in terms

of entropy. Changes in this entropy when matter is displaced leads to a reaction force.

Our aim is to show that this force, given certain reasonable assumptions, takes the form

of gravity.

The most important assumption will be that the information associated with a part

of space obeys the holographic principle [8, 9]."

3.2

量子化=量子化=溫度梯度化, entropy 梯度化, then you have 溫度梯度場強@時空點 , the so called entropy force=引力場場強@時空點, 引力 as 力, under 相对论高能条件, or non-相对论-newton 低能条件, so Anthony Wing Kosner AI software can model the those non-相对论-newton 低能 systems

"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;"

引力 as 局部惯性系(伽利略慣性系)加速=you feel 溫度heat locally,

3.3 科普

毛泽东的菩萨蛮·黄鹤楼"把酒酹滔滔，心潮逐浪高" 我失骄杨君失柳， 杨柳轻扬直上重霄九。 问讯吴刚何所有， 吴刚捧出桂花酒。 寂寞嫦娥舒广袖， 万里 ...

引力=生产关系, did his deputy Liu tell him to shut up in the politico bureau's meeting? Mao's 溫度很上火? it has to be.

looks like 毛, 很上火, being bothered by "引力 as 局部惯性系(伽利略慣性系)加速=you feel 溫度heat locally"

what did he do with his 火? beat the "f--- out" of those his counter parties in class struggle, and obviously and maybe most importantly, with the theoretical guidance of the great social 理论物理学家 and the great social technologist, 列寧, an another 天才, and 毛天才 is definitely at that level;

how? in and out class struggle 相空間 of 6k years of Chinese history, where all the important "bits" of those great stories have been recorded and written into Verlinde全息屏, where you could do "面積"積分 to get 測度, and with that 測度, you fight your battle/war in 位形空间, which is conjugate 共軛 to your 相空間 mathematically.

the way 毛泽东 figured out his theory about class struggle as we all know: he basically read all the history of Chinese 6k years of class struggle, all classic case studies of those most bloody ones;

that="引力场没有质量，应考虑无质量场最大的时空对称群———共形群"

=Verlinde全息屏=mapping class struggle into a phase space 相空間, where 么正性, gauge, 測度, 度規 or mathematically unitary group or 測度 can tell us how to beat up those class enemies;

"用规范场的观点来研究引力理论，国内开展得较早，这也与杨先生的影响有关&不过，杨先生所考虑的相当于齐次洛伦兹群，这是不够的&而且，别人也早有文章&后来，周先生提及，引力场没有质量，应考虑无质量场最大的时空对称群———共形群，探讨如何把引力场方程改写为与共形群相关的规范场形式，含义深刻&另一次交谈，涉及规范理论中的磁单极和瞬子&在谈到它们分别与第一与第二陈类有关时，周先生提出：第三陈类会有什么物理？要知道，第三陈类至少应定义在六维空间上，而物理时空只有四维&问题简单而又大胆！然而，这一“第三陈类”之指，恰恰指向几年后极其重要的、规范反常的拓扑起源问"

周先生=周光召, I am not sure how many mainland Chinese 理论物理学家 today can be even close to 周光召 level, not sure about Li Miao, anybody else even can read and understand Verlinde全息屏? I don't know

how can china can catch up with white in physics/math AI? how to 后发优势?

4.

4.1

your post about "人类永生现在还做不到，当然Kurzweil认为还有15年就可以做到"

basically, we're at bottle neck of qm:

so far, "半導體景深" stuff=经典电荷分布

Depth of Focus, DOF=半導體景深, to 光刻 半導體 silicon wafer (大腦皮層?), with clear and small 線寬 and 量產, not easy stuff;

according qm's uncertainty principle : 电子空间定位精度=Compton 波长 h/mc~R/α~10-12 米的量级, with α(精细结构常数) @about 1/137

semi folks have to work at 电子空间尺度 far about the above qm 尺度;

so is our brain with its potential capped/limited @经典尺度. and our brain is basically a piece of condensed matter messing around@常溫平衡態, with pre-installed OS or 聲子場方程(文化,意识形态), fooling around in today's 社会场, with most energy wasted or working with very little return if any, so physics/math oriented AI has a huge productivity potential for human society, in terms of human capital preservation and development.

4.2

human capital preservation and development:

what can be more important than that for any nation?

and that is where white is going to put Chinese way behind, with the way tg is managing china, 漁民,腦殘, and that is why fundamentally, as I said before, I am not sure what tg has been doing is really good or bad for the Chinese nation as a whole and in long term, history will know.

if we have a qm-AI breakthrough, we could potentially and theoretically feel, see and dance with "phantom of the opera", for at least 再活五百年?

we don't know exactly, due to qm's uncertainty principle, but there could be potentially a lot of fun ahead

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

Unlimited products are like bosons and restaurant reservations are like fermions.

By Rebecca BoylePosted 01.16.2013 at 10:00 am4 Comments

Standard Model

Standard Model Fermilab

From OpenTable to Amazon to your Netflix queue, algorithms sift through what we seem to like and offer future suggestions tailored to fit those trends. But the problem is they do this for everybody. So if everyone gets the same recommendations on OpenTable, everyone will try to reserve a table, and there won’t be any seats left. What's more, if everyone gets a movie recommendation and everyone decides to watch it, the movie gets more popular--creating biases in the system. To improve matters, some researchers in Switzerland took a cue from the master rules of physics.

In particle physics, a given boson or lepton tends to occupy the most favorable energy state. If it’s a force-carrying boson--like a photon, a W boson or a Higgs boson--there’s no limit to how many particles can share real estate in that state. But if it’s a fermion--like a quark, or an electron or proton--then only a certain number can be in the same place at the same time.

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Technology, Rebecca Boyle, algorithms, bayesian model averaging, netflix, recommendation, standard model of particle physicsAlgorithms should take this approach and function according to the rules of fermions rather than bosons, according to Stanislao Gualdi of the University of Fribourg and colleagues. After all, an object’s utility declines with an increase in the number of people using it, they argue. It’s like everyone buys the same guidebook and goes to the same quiet beach, meaning the beach is no longer quiet.

To study this concept, Gualdi and colleagues looked at DVD rentals. Using this model, a service like Netflix could limit the number of people who can have a single DVD at a time, forcing other DVDs to be recommended and chosen as secondary options. This limits biases that can happen when you give everyone unfettered access to the same thing, and this is good because it gives the whole recommendation engine some new fodder.

As Tech Review's arXiv blog points out, this is not necessarily a way to increase profits, so it's hard to see any recommendation service implementing the idea anytime soon. But it's an interesting concept.

“Crowd-avoidance can be applied to nd a good compromise between satisfying the preferences of users and distributing them among objects evenly,” the authors write. Their paper is posted to the arXiv preprint server.

[Technology Review]