1

THE SHAPE OF KNOWLEDGE

Vo Viet Anh, XPRIZE Vanguard, vovietanh@gmail.com

Abstract

This paper provides an in-depth description of the Singularity Pyramid (SP) concept for an

extensively organized online knowledge mapping system, also a futuristic version of Wikipedia

wherein each unit of knowledge is associated with a probability distribution of probabilities to

reflect the probabilistic nature of reality. Knowledge mapping wouldn't have any significance if

not for four well-defined abstract dimensions (Conceptual, Purposeful, Scopic, and “Language”)

that capture the collective body of knowledge in its entirety. With the Singularity placed at one

end of each dimension as the ultimate goal, these dimensions give you a sense of direction in

learning/creating knowledge towards that goal.

With knowledge mapping, the SP can provide Singularitarians with a bigger picture to realize the

roadmap towards the Singularity by addressing numerous problems that impede their progress—

lack of coherent knowledge structure for academic research, lack of strategic profiling, leader

discord, unawareness of long-term danger, negligence of macro-vulnerabilities, and “language”

barrier to pure knowledge. It is also a collaborative tool for planning, decision making, risk

management, and resource allocation. The “theory of weaknesses” based on the SP has the

potential to change your worldview forever.

Engineering the SP is an unprecedented and formidable task which I foresee rapid advances in

technology in the next year may fulfill. Also, the intuitive (easy to memorize, visualize, and

contribute) and functional (designed for practical use) structure of SP makes it a candidate for

the brain of the Singularity Superintelligence (SS). Note: there is no technical detail in this paper.

Keywords

Singularity, knowledge mapping, hierarchy, probability, futuristic Wikipedia, Ray Kurzweil

2

I. INTRODUCTION

The model of knowledge for the SP is the result of my lifelong attempts to make sense of all

knowledge I had accumulated and stumbled upon. It is the ultimate culmination of all of my

intellectual and emotional experiences to date, the answer to all of my questions[8]

, and the tool

to solve every future problem.

Four dimensions of the SP were defined for a singular purpose of reaching the Singularity:

(1) The 1st (Conceptual) dimension shows the conceptual hierarchy of knowledge. It places

the Singularity tentatively at the top as the goal to climb towards[11]

.

(2) The 2nd

(Purposeful) dimension draws the lines between three classes of knowledge based

on their relevance to our ultimate goal of survival. It forces you to ask yourself “What

good is this knowledge for?” when you’re about to learn something, and reminds you to

maximize resource efficiency by sticking to the Core[9]

knowledge.

(3) The 3rd

(Scopic) dimension manages groups of knowledge. It encourages you to combine

pieces of knowledge into more substantial knowledge[10]

such as sophisticated

technologies, and supply all knowledge with sufficient data and facts.

(4) The 4th

(Language) dimension presents different versions of the same knowledge. It

welcomes you to provide and translate knowledge into rawer, more machine-friendly

forms of language (than human language).

After mastering these dimensions, you will organize your thoughts and look at the world in

entirely different ways[1]

. With them, the SP seeks to address 6 mains problems:

1. Academic research: Web users can only look at one piece of knowledge at a time (at

Wikipedia or other Google search results) rather than the big picture containing that knowledge

from a single source. Personally, I grew dissatisfied with what I could find during online

research with Wikipedia[6]

and Google[7]

. It was not because there was too much knowledge on

the web but because a single coherent structure for all knowledge was nonexistent. It was easy

to get lost trying to figure out all foundations of a complex multidisciplinary knowledge (e.g.

cloud robotics) or all applications of a theory (e.g. general relativity), the highest level

conclusions of experts in a field (e.g. “silicon chip density increases can be extended into the

2020s”) or the deepest technical problems they had solved (e.g. measuring Levenshtein distance

between two strings), or which direction I should take in expanding my knowledge in order to

ultimately create new knowledge, i.e. original research or novel technology. To address this

problem, I envisioned a futuristic version of Wikipedia that surpasses conventional concepts of

all knowledge-bases[24]

in its suggestive power to make easier to navigate intellectually and come

up with something original or simply profitable.

2. Strategic profiling: There are too many credentialed people out there to decide who to listen to,

partner with, or hire. Every person is represented by a long list of achievements, companies,

publications, public profiles, questions and answers, social network status messages scattered

across multiple sources on the web, which take too long to research. On the other hand, what we

are concerned the most with when gauging someone’s skill depth, wisdom, and mindset/logic,

are (1) his deepest technical solutions, (2) highest level conclusions, and (3) how he jumped from

assumptions to conclusions (in an extreme case, Deepak Chopra’s logic was so flawed he made

long shots to inane conclusions outside of his fields). By treating each user as an object on the 3rd

3

dimension (together with other group objects such as disciplines) comprised of pointers to all

pieces of knowledge he has created, endorsed, or learned, and connections he has drawn between

these pieces, the SP allows each user to maintain a singular profile on the web including the

most meaningful insights about that person’s mind—basically what matters most to find or be

found by like-minded partners, employers, or benefactors.

3. Leader discord: It’s very common to find experts in the same field with glaringly contrasting

positions[18]

and there’s no way to verify their conclusions in order to decide which one is

correct1. For example, Dr. Kurzweil complained in [Kurzweil 2012] about Paul Allen’s lack of

point-to-point critique that preluded any constructive argument. In my experience, I often

encountered intellectual leaders who were apparently smart and experts in their respective fields

but somehow naïve or even ignorant regarding worldly matters[22]

. Some were too clouded by

their ego and emotion to reason beyond their jelled assumptions, to unlearn and relearn. A

constant question in my mind was “What exactly made this person think that? Does he know a

crucial piece of knowledge that may change my mind, or simply have ridiculous DC-esque

logic? Where is he stuck?” Since then, I had been thinking of a platform to help mitigate bias and

close the gap between subjectivity and objectivity[2]

—where they can exhaustively trace their

current positions back to assumptions that constitute their fundamental differences, in order to

together reason beyond these differences and reach a consensus.

4. Unawareness of danger: A level of awareness high enough to perceive existential risks

requires a high amount of the right knowledge. Since any knowledge has a price-tag, there is just

not enough resource to pursue all kinds of knowledge. However, only a limited number of people

at this level of awareness (e.g. those at CSER2 and FLI

3) are concentrating their resources on

acquiring the core body of scientific and technological knowledge that may help us avert these

risks, while the majority of the world (even smart people) is ignorantly squandering resources

(including their brainpower) on knowledge that doesn’t directly translate to our long-term

survival4. A series of frustration had led me to the conception of the SP: When I became

conscious of climate change and other environmental issues, my peers in university hadn’t, so I

joined the environmental movement alone. When I became conscious of the limitations of purely

environmental solutions and approaches, my fellow activists and scientists hadn’t, so I pursued

multidisciplinary knowledge alone. When I became conscious of the problems beyond

technology that hindered our progress towards the Singularity, Singularitarians didn’t seem to

heed, so I’m writing this.

5. Negligence of weaknesses: Everyone in the computer sciences knows how much damage bugs

or deep-level technical vulnerabilities may cause to rapidly expanding information systems.

However, very few are aware of how much threat larger scale vulnerabilities may pose to our

survival against the odds of existential risks from the exponential technological revolution and

Nature, which may affect our Singularity timeline. To ensure our survival and the Singularity

timeline, we must be able to identify vulnerabilities (called “weaknesses” in this paper) from the

smallest to the largest scale—every bit and piece of information we miss, any possibility we fail

to take into account in our plan/theory/algorithm (global weaknesses), or any failure to

1 http://www.iflscience.com/health-and-medicine/how-reliable-are-tv-doctors

2 Centre For The Study of Existential Risk http://cser.org/about/who-we-are/

3 The Future of Life Institute http://thefutureoflife.org/who/

4 Having a bunch of best thinkers become lawyers is waste of human capital http://qr.ae/qW6rp

4

acknowledge and insulate our own biological limitations, and the very population of people that

carry such weaknesses (local weaknesses). With a knowledge map, it would be possible to circle

where weaknesses might be most damaging if exploited in order to contain them with layers of

high-level security plan, or concentrate resources to eliminate them once and for all.

6. Language barrier: Wikipedia is written in the most human-friendly language—human

language, which is not optimal for knowledge representation. IBM’s Watson and most AIs have

to derive knowledge through crawling and parsing countless data in this language, which might

take too long to achieve human-level intelligence. So, why is there no Wikipedia for AIs, written

in more machine-friendly languages? Humans expect machines to understand them and yet so

few (only programmers) can make their thoughts clear-cut enough to be understood. There are

coding crowdsourcing websites such as Stack Overflow, TopCoder, and Kaggle but their

solutions are disconnected and limited to very deep technical solutions, while there is an

enormous amount of high-level knowledge that can be translated to more machine-friendly

languages by just anyone (not just programmers). If there is platform to crowdsource systematic

codification of hierarchical knowledge, we can accelerate machine learning, all while teaching

users algorithmic thinking to form more logical thoughts and rigorously define actionable high-

level knowledge, e.g. an algorithm to allocate resources and determine actions taken against

specific populations within a time frame that guarantees existential risks lower than a threshold.

The 4th

dimension of the SP is a future project to upgrade the SP into such a platform.

At first, this model had many names—the Pyramid of Knowledge, Symmetry, Wisdom, to name

a few. In 2012, I learned about the Technological Singularity and realized that this model could

become a powerful tool to achieve it faster, if not in time. Hence the name Singularity Pyramid

to align my goal with the Singularitarian community’s.

5

The SP’s knowledge mapping system offers a wide range of applications in everyday, profit-

driven, or high-level activities[12]

.

Compared to Wikipedia, the SP also takes time to crowdsource knowledge, but it is more

functional and thus promises benefits for contributors and ROI[16]

for investors.

Table of Content

II. The rooms 5

III. The 1st dimension 6

IV. The 2nd

dimension 8

V. The 3rd

dimension 11

VI. Secondary dimensions 13

VII. Terminology and abbreviation 14

VIII. Building the pyramid 15

IX. Application 20

X. Theory of weaknesses 21

XI. My next step 24

XII. Interpretation and notes 25

XIII. Example 32

XIV. Reference 43

XV. Vitae 44

XVI. Dark 44

II. THE ROOMS

A unit of knowledge mapped on the SP is not limited to academic knowledge but refers to the

broadest possible definition of knowledge—anything that can be known, which is as infinite as

the universe. It can be anything conceivable: a qubit, a datum, a fact, an opinion, a citation, an

object, an idea, an action, a thought, an event, a phenomenon, a theory, a plan, a conspiracy, or

virtually any information to predict exactly anything that may happen the next moment, etc.

Metaphorically speaking, the SP is a structure with countless rooms on each floor, each room

representing a unit of knowledge. False knowledge doesn’t exist on the SP, e.g. “the US

government is run by lizard men,” but can be brought onto the SP through factualization, e.g.

6

“Barack Obama said the US government is run by lizard men.” Lit rooms are acquired

knowledge, and dark rooms uncharted knowledge. Once a room is lit, it’s globally lit, but locally

dark to those who haven’t lit it. Since human knowledge is built mostly bottom up, the top of the

SP is dark to almost everyone.

When you try to discover new knowledge, you launch yourself into the dark. Then you either

land into a dark room (come up with something right) or outside of the SP (come up with

something wrong). If the room you land into is globally dark (a discovery), you’re free to

command benefit from it, and choose to let it be globally or locally lit. But if that room is locally

dark (a secret), which means someone has been there before, you may be pushed out of the SP to

death. For insights into the dark top of the Pyramid, please refer to the Dark section after going

through this whole paper.

Each room is associated with a probability distribution of probability values, which indicates the

percentage of users who have rated each probability value. I decided to use the probability

distribution of probabilities because it reflects the probabilistic nature of reality, tells you more

information than a probability[47]

, and is the closest expression to a wave function, which has

later implications for the SP.

III. THE 1ST

DIMENSION

It all started when I realized an apparent hierarchy between the conscious levels of a naïve

physicist and a wise politician (both are smart). What did the physicist know? Complex technical

concepts in physics and engineering. What did the politician know? Economic insights and

political secrets. What was perceived at the level of the latter’s understanding (e.g. the unified

axis of government and corporate power) might supersede the effects of both the former’s works

in physics and the very physical systems the former was studying or building (e.g. by slashing

state funding to his research). Conversely, a breakthrough in the former’s field (e.g. E=mc2,

atomic bomb; hydraulic franking; any disruptive/transformational technology such as

biomanufacturing, mass production Kill Bot, robotic soldier, directed-energy weapon, and

portable fusion reactor) might turn the whole political system that the later knew upside down.

Thus they seemed to be situated at two extremities of equal importance. If the physicist was

“deep,” then the politician should be “high.”

This hierarchy reappeared during my academic research when I realized that biological processes

emerge from chemical reactions, which can be derived from physical laws, which are described

and predicted by mathematical models, which are deduced from logics and founded on proofs,

which can be traced back to self-evident or assumed statements known as axioms. Economic

activities, political policies, and life principles are all based on these academic concepts to some

degree, albeit unfathomably remotely. In this hierarchy of concepts, one is founded upon others.

This is basically the same hierarchy of the brain’s pattern recognition modules described in

[Kurzweil 2012] as functional units to recognize components of human languages—from

phonemes down to frequency bands of sound (perceived as pitches), up to words, phrases,

sentences, contexts, to abstractions such as attractiveness, irony, happiness, frustration, envy,

sarcasm, humor, nuance, metaphors, similes, implications, secret code, and so on.

7

Therefore, I have unified these compatible hierarchies into the 1st (Conceptual) dimension. It’s

worth pointing out that we humans do not start at the top digging down or at the bottom climbing

up. We are “born into the knowledge” somewhere in the middle of the SP, where I call the Free-

lunch Zone[21]

, before embarking in two opposite directions simultaneously. The knowledge in

this Zone is the easiest for humans to acquire, and thus can be described as either Low or

Shallow. From the bottom to the top of the SP, the relative position of a room can be described in

order as Deep, Shallow, Low, and High.

Most of the time when someone asked me “Are you in deep thoughts?” I usually responded “No,

I’m in High thoughts.”

Skip to The 2nd

dimension[32]

Basic rules

1. Higher rooms are founded upon Lower rooms. A Lower room would prop up (be part

of/produce a subset of solutions of/contribute to/prove/deduce) a Higher room, while the Higher

room could backprop (predict/contain/incorporate/dictate) a Lower room. The direct relationship

between a pair of rooms is either a prop or backprop, which indicates their relative position along

the 1st dimension. For example, computing technologies for a speed of 10

19 cps and

nondestructive brain scanning technologies are required props for the “mind uploading”

technology; advanced technologies in propellant, engine, materials, design, pilot safety, tires,

sensors, space, etc. are required to prop the blueprint of a recyclable private space aircraft.

2. Between two rooms with no direct relationship on different floors, the Higher room often

supersede/happens regardless of the Lower room, while the Lower room makes happen/possible

the concept of the Higher room[37]

.

3. A Higher room must be built upon Lower rooms. However, in fact, Nature has gotten ahead of

humans since the birth of Earth and lit High rooms long before we could reach them

methodologically bottom-up. These “Hints” provide suboptimal but effective solutions from

which principles to develop optimal solutions can be derived[53]

. Taking advantages of Hints thus

accelerates humans’ exploration of knowledge. Reverse-engineering the brain to model its

interactions at the molecular level (or even quantum level) and search for the “secrets of the

human brain” is a prime example of acquiring Hints.

4. Rooms from High to Deep correspond to a decreasing level of generalization, abstraction,

“simplification”[27]

; an increasing level of specialization, specificity, precision[26]

. For example,

there are many theories for the brain with resolutions ranging from the whole cortex (High), to

modules consisting of neurons, to neurons, to very detailed level of molecules in a neuron, to the

quantum phenomena in the brain (Deep).

5. Rooms from Low to High and from Shallow to Deep correspond to increasing difficulty and

level of energy. A higher “level of energy” means either more energy/matter (higher number of

molecules studied, higher temperature, or higher speed), more energy density (e.g. from a white

dwarf to a neutron star to a black hole), or more energy/time/resource/brainpower consumption.

In fact, the upper limit energies of particle colliders dictate whatever final resolution humans are

able to deliver in terms of experimental results. Every time the Large Hadron Collider raises its

8

energy limit, a barrage of discoveries will follow, with Theory of Everything as the likely final

destination.

6. The Higher room A is to room B, the more probable it is that room A can supersede/obsolete

room B[52]

. There are two notable degrees of High-ness:

[37] a) Paradigm-High: Room A is paradigm-Higher than room B if they have no direct

relationship but room A still supersede/obsolete room B. For example, technological paradigms

were characterized by these technologies—electromechanical computers, relays, vacuum tubes,

transistors, integrated circuits—and next comes the self-configuring 3D molecular circuits (and

then my speculated nonlocal circuits). In another example, Israel Intel shifted the computer chip

paradigms twice when upgrading the 486 chips to Pentium M chips, and then to Core 2 Duo

chips. Previous technologies don’t direct prop later technologies which are smaller, faster,

cheaper, more efficient, and based on whole classes of Deeper concepts (e.g. quantum

entanglement), but they made POSSIBLE the conception of the next paradigms’ technologies.

For example, without transistors to run a transitional generation of computers and create a wide

range of tools to build tools, humans could never have invented integrated circuits.

(b) Meta-High: Normally a Higher room A can supersede room B, but not for 100% of all

possibilities. It may reach 100% (meta-High) only if room A COMPLETELY contains room

B[59]

. A High physical theory may apply to a highly energetic system, but a meta-High one

should apply to all systems with lower energy levels. In life, a High dictator can dictate a Low

farmer but there’s a small chance the farmer can backstab the dictator, unless the dictator is High

enough to predict and counter ALL possibilities regarding the farmer’s actions (including his

interactions with the environment). This has profound implications in the theory of

weaknesses[63]

.

7. Deepest rooms are the foundations for Highest rooms. A commonly observed phenomenon—

and also a knowledge acquisition strategy—is the bouncing between the Deep and the High[36]

.,

which means discovery of High knowledge would enable discovery of Deep knowledge, and

vice versa, and so on.

8. A High theory is a Symmetry of one or many approximation theories (Approxes) if that theory

unifies all the Approxes[54]

. For example, M-theory is a theory in physics that unifies all

consistent versions of superstring theory, which arise as special limiting cases of M-theory.

For further understanding, please refer to an incomplete list of related topics on the 1st

(Conceptual) dimension5.

[32]IV. THE 2

nd DIMENSION

“You are too SOFT” was what my best friend told me whenever I immersed myself in romantic

literature, popular fiction, songwriting, poem, fashion6, learned dancing, basketball, pick-up lines,

love songs, watched dramas, football, etc. just to impress and conquer the girls who had such

5 Related topics on the 1

st (Conceptual) dimension http://qr.ae/qWJCq

6 Almost everything to know about wearing suits http://qr.ae/q9UQn

9

interests. He didn’t say so to make me less human. He said so because he knew me so well, that

such activities would largely not serve my purposes in life, distract me and waste my time.

But what if my actions HAD purposes? What if I KNEW that those girls were either very rich or

somehow a specific link in my grand plan? What if I lived my life only to please everyone and

do everything needed (even laugh and cry) for the sole purpose of long-to-infinite-term survival

and evolution? That reminds me of the notion of HARD scientists, who are the practical and not

concerned with whether the Singularity is near or not, an AI is “strong” or “weak,” or what the

heck “consciousness” is.

So, can I be even Harder? What if I could invent all Deep mathematics, all High theories and

algorithms, build a machine to run them, dominate the world, and then merge with that machine,

survive cosmic catastrophes, exponentially evolve, and eventually dominate the universe

(absorbing all matter and energy and know everything that can be known in this universe and all

parallel universes if there be). If that happened, then at some point, there would be no distinction

between me and the machine—no human touch. That’d be beyond Hard—SUPER HARD, which

reverberates the concept of the Singularity Superintelligence.

Therefore, I have divided the 2nd

dimension into three levels of purposefulness—a Soft shell, a

Hard shell, and a Super-Hard (S-Hard) Core. It’s not meaningful to divide any further.

Skip to The 3rd

dimension[33]

Basic concepts

Soft Hard S-Hard

Knowledge for the sake of

psychologically keeping humans

alive by enriching our mental life

and allowing “meaningful”

human interactions7

Knowledge for the sake of

deriving S-Hard

knowledge

Knowledge for the sake of

survival and evolution

Limitless knowledge created by

humans but not contradicting

Hard and S-Hard knowledge

Minimum amount of

knowledge for humans to

achieve Singularity

Minimum amount of

knowledge for a computer to

achieve Singularity

The practically limitless realm of

knowledge inherent to humans;

basically a collective body of

virtually any possible random

knowledge[51]

which humans who

can see beauty in every trivial

detail would create if given

unlimited lifespan, time, and

All knowledge a machine

needs in the context of

human existence, to serve

humans, pass the Turing

test, act like a human, gain

humans’ trust, so that

humans can help the

machine become even

All knowledge that a machine

needs to survive, evolve in any

environment, “maximize the

diversity of possible futures”8

or simply “dominate the

universe”

7 Why do people care about and remember all imaginary details http://qr.ae/qWJCN

8 http://www.ted.com/talks/alex_wissner_gross_a_new_equation_for_intelligence

10

resources; appeal to humans

senses; including every single

slightly different piece of creative

work

smarter, until the machine

can take over the process

of improving itself

Has human touch No human touch

For mental survival For physical survival

Examples of Soft knowledge vs. Hard knowledge:

Photography vs. imaging, love vs. brain on love, winning Olympic

Gold medal vs. sports, fine dining vs. nutrition, fashion vs. armor,

sex vs. cloning, makeup vs. cognitive augmentation, music

composing vs. sound engineering, virtual sex vs. virtual doctor, slice

of life vs. science fiction, leisure chatbot vs. expert system, emotional

robots[68]

vs. security robots, contemporary art vs. classical art,

recreational drugs vs. medicine, recreational mathematics vs.

competitive programming, graphic-intensive video games vs.

classical strategy games (scrabble, chess, backgammon, Go, Bridge),

Victoria’s Secret diamond-laced bra vs. diamond drill.

Knowledge that any

species would need to

survive, without any

regard to human: logic,

mathematics, algorithms,

physics, chemistry,

robotics, AI, energy,

weapon, transportation,

rocket, metamaterials,

computation, etc.

Soft climbing: the act of acquiring

Higher and Higher Soft knowledge.

Pros: humans believe that they can

discover grains of wisdom in epic

fantasy novels, technological

inspirations in science fiction, the

universe’s mysteries while

traveling the world, or Nature’s

laws in this paper.

Cons: knowledge acquired is low-

prob, incomprehensible to AIs.

Hard climbing: the act of of acquiring Higher and Higher

Hard/S-Hard knowledge, including two processes:

(1) Fast top-down process of acquiring Hard knowledge

thanks to a large amount of Hints provided by Nature[69]

.

S-Hard knowledge is then derived from Hard knowledge.

(2) Slow bottom-up process of acquiring S-Hard

knowledge (mostly in logic, mathematics, physics, and

engineering), analogous to a walk into the darkness

because of a low amount of Hints and insufficiently

resource allocation (i.e. time, capital, material, brainpower)

due to “Soft drifting.”

Soft drifting: the

tendency and preference

of humans to acquire

Soft knowledge.

Reasons: the majority of

the world is enjoying

peace and resource

abundance; Hard

climbing is boring,

difficult, and risky (i.e.

invest too much time and

Hard rushing: is accelerated Hard climbing under extraordinary

circumstances. Normally people acquire knowledge in all directions.

Only in extreme/life-or-death situations such as war9 or a startup

under resource constraints10

would the human instinct remind us of

the ultimate Hint on top of the SP—“I must survive.”

At such times, humans did everything it took with their health and

life at stake to survive, namely taking the direct course up the Core,

and consistently achieved paradigm-High breakthroughs[30]

, which

are later adapted for a wide range of civil (Soft/Hard) uses, e.g.

chemotherapies are offshoots of chemical-warfare agents.

9 http://www.spacenews.com/article/opinion/37245end-of-wwii-model-shakes-up-aerospace-industry

10 SpaceX on the verge of failure http://qr.ae/qW30W

11

money in the wrong

idea); Soft learners are

driven by joy, happiness,

and freedom.

Driven by instinct, fear and hope. Often resulted in casualties.

Consumed less physical resources and time but more human

resources (human sacrifice) because in war smart people on both

sides died. If during peace time academics may undertake researches

in all kinds of directions, during wartime they all had to focus mostly

on physics and engineering.

Soft appeal: Anything Soft always appeals more to

humans because our biological systems are not

optimized for continuous Hard-working. Imaginative

technologies and science in sci-fi/superhero

novels/movies11

are more enjoyable to kids and

humans in general12

. Soft things activate our brains’

reward system, trigger positive emotions, signaling

that there’s no resource constraint endangering our

existence, making us forget all purposes. Honestly, if

I had been born in a rich family with enough money

to learn anything I ever wanted, I doubt I would be

writing this paper right now.

Hard-hitting: When a technology has

touched the boundary between Hard and

Soft then any further development would

only make the technology less efficient

due to the presence of paradigm-Higher

technologies. Whenever this happens,

humans have officially advanced into the

next technological paradigm. Any further

development of older technologies would

be for aesthetic purposes (e.g.

steampunk, antiques, and pixel art) or

other irrational human reasons.

Rooms from S-Hard to Soft correspond to an increasing disorder/entropy (rooms with minor

differences become increasingly undistinguishable), an increasing redundancy (vast amount of

variations of the same knowledge), a decreasing “density” (more dark rooms as a result of

redundancy), and a decreasing resource-efficiency.

The purposefulness of Soft and Hard knowledge can be subjective (varies from person to person)

and constantly changing (depending on the context including resource availability). An otherwise

Soft knowledge such as fashion knowledge may become Hard when you need it to approach a

powerful person who is a fashionista. However, if there’s not enough time for Soft knowledge,

you might have to utilize your Hard knowledge to kidnap that person and force him to do what

you want, all while taking huge risks.

In times of resource crises or foreseeable disasters, humans would automatically focus on

Hard/S-Hard knowledge for survival’s sake. However, in most cases, the majority of the world

wouldn’t reach the Conceptual level High enough to realize the crises or disasters they are facing

and fail to act accordingly. Despite the seemingly more important nature of Hard/S-Hard

knowledge, given the current mental state of humans, it is necessary to pursue all three kinds of

knowledge simultaneously[43]

. For more examples, please refer to the Example section[39]

.

11

http://www.wired.com/2014/11/can-hulk-lift-thors-hammer/ 12

DARPA’s project to teach STEM https://www.topcoder.com/case-studies/darpa/

12

[33]V. THE 3

rd DIMENSION

The Scopic dimension is the easiest to understand because it only tells you which groups a room

belongs to, for example arithmetic belongs to mathematics. For simplicity, it is like a supply

chain—raw numerical data supply facts; these data and facts supply disciplinary knowledge,

which in turn supplies all kinds of group objects such as disciplines, technologies, and users’

Pyrofiles.

We adopt both a fixed disciplinary taxonomy (each group called taxon, plural taxa, has a well-

defined taxonomic rank) represented by a Taxonomic Tree, and user-generated arbitrary

groupings (each group called scopon, plural scopa, has a floating Scopic rank) represented by a

Scopic Tree. A scopon may contain taxa but not vice versa. The Scopic rank of a scopon

indicates its relative scope/scale/size (the number of rooms it contains) and the highest rank of

the scopa it contains. The hierarchy in this dimension is very simple—higher ranked scopa

contain lower ranked scopa. The first four ranks—(1) data[41]

, (2) facts, (3) disciplinary

knowledge, and (4) disciplines—are fixed while higher ranks float.

Rank-1 rooms (data) are stored in form of a description text, coupled with numbers, arrays,

matrixes or other mathematical constructs. Rank-2 rooms (facts) are stored in form of free texts,

photos, videos, blueprints, or other forms of media. Rank-3 rooms (disciplinary knowledge) are

stored in form of free text and LaTeX. Future development of the 4th

(Language) dimension will

host other versions of these rooms in rawer, machine-friendly languages.

Each room is linked to and fro only one node on the Taxonomic Tree, but can be linked to and

fro many nodes on the Scopic Tree. Each node on either tree stores (1) a free text, (2) a pointer to

a definition room (e.g. “Physics” room which stores a broad definition of physics), and (3)

pointers to all grouped rooms (e.g. all physics-related knowledge). Each node on the Scopic Tree

can be a technology, an academic paper, a solution to a problem, a submission to a competition,

etc. linked to all of its related knowledge. For example, a “2018 Bomber” Scopic node links to

and fro a description text and all scientific knowledge employed in the Bomber such as

metamaterials, explosives, and computational algorithms. Philosophy and religion are two

interesting group objects13

.

The purpose of this dimension is to encourage users to (1) group distant knowledge to create new

(and Higher) knowledge[40]

or identify problems in one field that have solution in another field

(e.g. by running a search for rooms that share a majority of props from data and facts), and (2)

support existing knowledge and facts with numerical data in order to calibrate their probabilities.

In other words, by mapping all knowledge on the SP, we can (1) systematically explore all of the

overlapping boundaries between our exponentially expanding frontiers of knowledge, and (2)

hook up experts in different industries, enable them to look beyond just their narrow discipline,

juxtapose their knowledge next to each other, and identify the same concepts being described in

different terminology. This is important because one (sub)-field may have actually solved a

problem that another (sub)-field14

was attempting to solve but it is not realized because these

fields use different terminology. Similar processes are known in mathematics as “abstraction”[42]

.

13

http://spyramid.quora.com/Philosophy-and-religion 14

Problems in one field solved by solutions in another field http://qr.ae/q9BMK

13

VI. SECONDARY DIMENSIONS

Knowledge bases employ only ontology and/or taxonomy; Kurzweil’s hierarchical model of

mind has only a Conceptual dimension; none gives you a sense of direction. Never before have

the vague concepts of knowledge dimensions been redefined, refined and put together into a

single coherent picture like the SP. Yet, I still want to make this picture more complete. There

are some dimensions I want to add to or combine with the three primary ones—the 4th

(Language) dimension, the 5th

(Technical) dimension, the 6th

(Applied) dimension, which are all

slightly parallel to the 1st and 2

nd dimensions.

1. The Language dimension:

[73]With this dimension, I want to introduce a completely new notion of “language”: If human

language is a collective of languages humans use to communicate with each other, then a

molecular language should be a language molecules use to communicate with each other.

Examples of languages in order of decreasing human-friendliness are human language (between

humans), programming language (between humans and machines), machine language (the lowest

level programming language with op codes and operand numbers), electronic/digital/binary

language (between electrons and electronic components), neuronal/electrochemical language

(“language of though” between neurons or the hypothetical neocortical patterns[45]

),

DNA/molecular language (between molecules), and the futuristic computronium/quantum

language (between computronium)[44]

.

Languages can exist in any arbitrary form depending on the structure and substrate of the

communicating entities. For example, whenever a genetic algorithm (GA) successfully generates

a set of parameters which constitute a solution that can magically solve all problems at hand

perfectly (e.g. speech recognition), these parameters embody High and Deep knowledge in an

entirely new language, which is incomprehensible to humans, has to be studied to translate into

whatever secrets they are holding regarding perfect speech recognition. The number and physical

relationships of these parameters are dependent of the substrate of the hardware. As exotic

computing architecture with smaller substrates or substrates with more accessible states become

available, down to a maximum at quantum level, rawer forms of language will be invented by the

GA, embodying Higher and Deeper knowledge acquired through the interaction between the

machine and its environment. Eventually, following this pattern, the SS will invent the rawest

possible form of language that only it can understand.

When this dimension is introduced, users will be compelled to translate knowledge into more

machine-friendly languages (programming code, pseudo-code, or mathematical symbols) and, in

that process, identify inconsistencies in their own thinking. With this dimension, I also want to

raise an issue that humans’ instinctual attachment to human language might turn out to be a

barrier to pure knowledge or “true understanding” of knowledge, which is largely formless and

not intuitive. In fact, my neurons have their own language that only they can understand.

Evidently, even though my ideas for the SP are so fluid in my mind, I’m having a hard time

trying to put them down in this paper.

2. The Insightful-Technical dimension: is important for new learners who want to start learning

the most readable, insightful texts of a concept before diving into less comprehensible, more

14

technical details. When studying a theory, you will be able to choose between reading texts

explaining it in an insightful manner and those explaining it in technical details.

3. The Theoretical-Applied (or Global-Local) dimension: Knowledge should also be arranged

according to the degree of relevance to the environment of the users.

4. Correlation with the 1st and 2

nd dimensions: The closer to the Core and the bottom, the more

disciplines become more computational (e.g. computational social sciences), more quantitative,

Deeper, more universal or “global,” harder to express in human language and easier to express in

rawer languages.

Skip to Building the Pyramid[65]

VII. TERMINOLOGY AND ABBREVIATION

1. Dimension: can be understood as one of the three axes of the triaxial spectrum of knowledge

in the SP.

2. Room: a unit of knowledge, which can be anything that can be known—a qubit, a datum, a

fact, an opinion, a citation, an object, an idea, an action, a thought, an event, a phenomenon, a

theory, a plan, a conspiracy, or virtually any information to predict exactly anything that may

happen the next moment, etc.

3. Low-prob and high-prob: short for low probability (<70%) and high probability (>=70%).

4. Conceptual floor or floor: a level in the 1st dimension.

5. Hard shell and Soft shell: two outermost levels in the 2nd

dimension.

6. [9]

Super-Hard Core, S-Hard Core or Core: the innermost level in the 2nd

dimension. The Core

is not called the “Core” for nothing. It’s filled up with the least possible amount of knowledge

required to reach the top. In other words, it’s the shortest path to the top.

7. Scope rank or rank: a level in the 3rd

dimension.

8. SP: Singularity Pyramid.

9. SS: Singularity Superintelligence.

10. Hints: provide suboptimal yet effective solutions (e.g. brain-inspired computer architecture)

from which principles to develop optimal solutions can be derived. Fields that study or take

advantage of Hints include biomimetics, bionics, swarm technologies and communications, bio-

inspired computing, human-inspired Big Data Access Strategies, etc.

11. Insight: a High, usually low-prob, room lit based on a large amount of Low rooms. In other

words, an Insight is a loosely founded speculative knowledge which, if turning out to be correct,

can be refined and developed into a complete theory. Very smart people have a propensity for

15

very High low-prob fringe scientific theory15

. Insights and Hints together often led to very

popular but scientifically unfounded theories and concepts, e.g. Feng Shui, Chakra, Ki, Yin Yang,

Chinese/papal/shamanic exoteric knowledge, parapsychology, and alternative medicine.

12.[3]

Consciousness: is defined, in this paper, as the brain’s equivalent of a computer’s random

access memory. It doesn’t colloquially refer to self-consciousness, metacognition, the ability to

think about one’s own thinking or other misleading, unfounded, and pseudoscientific notions of

“consciousness.” Knowing how oft-abused the word “consciousness” is, please strip your mind

of all definitions you have ever come across until now.

13. A person’s consciousness: a subset of one’s own knowledge (as humans cannot recall

everything we know at once and that’s why we often make the same mistakes all over gain);

one’s perspective is a chosen subset of her consciousness (e.g. “Let’s take a perspective of a

mathematician and then that of a computer scientist to approach this problem.”).

14. Conscious level: is the level of the Highest room of a person’s consciousness. A High person

is someone with relatively High conscious level.

15. Symmetry: a High theory that unifies several approximation theories (Approxes).

16. Approx (short of approximation): is one of the approximation theories of a Symmetry, often

a theory that is only accurate and useful within certain boundaries. For example, the Albert-and-

Rex model of the brain16

is a fun inspirational read (the most upvoted Quora post) and can be

somehow applied in everyday activities until you can acquire a degree in neuroscience to

develop more accurate theories.

17. Cred (short for credentials): indicates the weight of a user’s rating for a taxon. A High cred in

one field doesn’t correspond to a High cred in another field. High-profile people may have

credentials in certain areas but not in other areas. For example, Deepak Chopra can have a great

voice in heart surgery matters, but be banned from any conference on philosophy or physics.

18. Logic-set: If you prospective employers/lovers check out your Pyrofile, they will be most

concerned with not only your Highest and Deepest rooms but how you connect rooms. Each

prop/backprop you draw between rooms reflects your unique logic. In the future, one’s logic-set

(in form of a webgraph) may matter much more than one’s “mindset” or skillset.

19. Mini-SP with respect to room A: is a subset of the SP with room A as its local top. It includes

all rooms upon which the top is founded.

[65]VIII. BUILDING THE PYRAMID

Guidelines

[Suh 2009] has observed that Wikipedia growth has essentially plateaued, hence unsolicited

contributions from human volunteers may yield a limited amount of knowledge going forward.

15

https://www.quora.com/What-is-it-like-to-have-an-extremely-high-IQ/answers/8485223 16

http://www.quora.com/How-do-I-get-over-my-bad-habit-of-procrastinating/answer/Oliver-Emberton

16

However, I believe that such a limit was largely attributable to the two words “unsolicited” and

“volunteer.” What if we present contributors with a mission and benefits? It’d be very likely that

we can harness the full human potential.

The Mission is to push the frontiers of knowledge towards the Singularity in each dimension;

benefits are the SP’s applications, along with access to crowdsourced and licensed tools, e.g.

suggestions of prop/backprop as you type/click on a room, and analytic/predictive tools

described later in this paper. I wish we could rely on machine learning to rush up the Core but

have to admit that we still don’t have what it takes go full S-Hard and thus still have to depend

much on human curation.

The SP’s initial objective is NOT to amass information (like most knowledge bases did) but to

encourage people to first post their Insights[46]

(assumptions, “pearls of wisdom”) and then

exhaustively and logically validate them (the way most people in logical professions such

lawyers, scientists, and engineers do on a regular basis) by gathering all information and

knowledge to support them. That way, they will light all the rooms they have skipped on their

way rushing up, in order to get rid of unfounded thoughts, make unexpected discoveries, expand

their Insights into full theories, and create a strong foundation to go even Higher than where they

are standing.

[2]Most people don't have the resolution to verify their own assumptions, which are usually High

Insights derived from disparate memories throughout their life and suddenly put together

precariously through a mysterious process inside your brain often called the “intuition.” It's

troublesome to dig out the specific memories that led to these assumptions. Even when they have

successfully dug them out, these memories may turn out to be so remotely/vaguely connected to

the assumptions at hand that they would feel too embarrassed to admit. It’s important to

overcome this mental inertia in order to accelerate towards the Singularity.

Skip to Application[48]

Data types and visualization

The main information in each room is stored in form of free text (for the most part of the SP),

mathematical symbols, programming code and, in the future, other data types to accommodate

even rawer languages which I have not imagined yet. In addition, each room is associated with a

probability distribution of integer probabilities and a representative probability in percentage.

Since the SP’s focus is different from that of most knowledge bases (Wikipedia, Freebase,

Knowledge Grapth, DBpedia, Knowledge Vault, etc.), facts such as Obama’s birthplace, music

albums, or anything not in English are the LEAST of our concern. Rooms on rank 1 and 2 (data

and facts) should be filled up with mostly statistics, measurements, or free texts describing

events, e.g. “On December 21, 2012, Barack Obama walked into a bar.”

The initial value of each room’s probability needs to be set by deep evidence-based probability

rating algorithms, with reference to Watson’s Deep Q&A. This initial rating is multiplied with a

cred of 100% in the equation of the room’s representative probability, which at first will

overshadow most users’ ratings.

17

A data visualization tool can be built with Three.js, a comprehensive WebGL library. Only three

primary dimensions are visualized in form of a 3D pyramid. The user interface (which resembles

Google Earth) includes basic operations like add, edit, remove, prop, backprop, endorse, suggest

edit, search, etc. on the top and advanced, licensed analytic/predictive tools at the bottom. Rooms

can be opened in multiple resizable, movable windows for reading or editing.

Human involvement

1. Question attachment: Users can attach questions or links to questions at Q&A sites, such as

Quora and Stack Overflow, to and fro a room in order to facilitate knowledge validation (down),

exploration of same-level knowledge (horizontal), to development of Higher theories (up)[4]

. For

example, lists of unsolved problems in mathematics17

and computer science18

represent locked

doors to access the Deepest floors (and, next, the Highest floors).

2. Conflict flagging: For each theories/facts/events, there always exist several conflicting

counterparts. By flagging these rooms in conflict, we can draw other users’ attention to resolve

the conflict, by proving that most, if not all, of them are low-prob, or by coming up with a

unifying theory/Insight if all of them are high-prob. Dr. Kurzweil did it too[49]

.

3. SP backup: Only one state of the SP needs to be backed up because users can add or adjust

content but cannot remove anything. If you think a room has something wrong, repost that room

with the wrong thing omitted and suggest users related to the original room to endorse the new

room. Rapid changes of rooms related to topics on the news can be recorded with considerably

more temporal resolution for research purposes.

4. Actions: The role of the SP is to help you or a machine know what actions to perform, not to

sit idly thinking forever. Therefore, the knowledge in each room is prioritized to present a part of

or this whole sequence: conditions concepts definitions actions results. At

programming language level, they should be in form of functions or procedures.

5. Users have to avoid and improve absolute, incomplete, or excessive statements. For example,

“The less government intervention the better” and “To succeed, you must be merciless” are

absolute and incomplete. You should improve and replace them with “In fast growing markets or

where leaders are incompetent, the less government intervention the better; otherwise,

government tend to play in important role” and “To succeed, when mercy is valued by people

who are valuable to you more than your gain from being merciless, be merciful; otherwise, be

merciless.” The more what-ifs and details, the better. You may add statistics, thresholds,

mathematical models, etc. but they have to relate to the core point of the room; otherwise it will

become excessive and needs to be divided.

Computation

1. Pyrofile and credentials (cred): “You’re rooms19

; everything is just rooms.”

17

http://en.wikipedia.org/wiki/Millennium_Prize_Problems 18

http://en.wikipedia.org/wiki/List_of_unsolved_problems_in_computer_science 19

How many rooms are you? http://qr.ae/qSkVI

18

In the SP, you are your knowledge, either self-sourced or externally-sourced. Cred is a measure

of your credentials for a taxon (not scopon) in percentage (0% to 100%). It is calculated as the

average of all of your learn-rates (also in percentage) for each accounted room in that taxon. A

user’s learn-rate for a room is accounted in the calculation of that user’s cred for all taxa that

contain that room. For example, someone who has learned 90% of everything there is in

theoretical physics can have a cred in physics as high as 75%.

There are three ways you can raise your cred for a taxon (tentatively equally disttributed): (1)

earn learn-rate for any room in that taxon or the whole taxon by taking courses of SP-affiliate

institutions or by submitting evidence of your knowledge, (2) be endorsed by high-cred users, or

(3) have your contributed content endorsed by high-cred users.

Cred(user X, taxon Y) = ∑

∑

∑

∑

Learnpoint: user X’s learn-rate for each room in taxon Y, in %

Roomcount1: the number of accounted rooms in taxon Y

EndorserY: the endorser’s cred under taxon Y, in %

EndorsedY (input): the value of cred endorsed by that endorser for taxon Y, in %

RP: the representative probability of each room in taxon Y, in %

Roomcount2: the number of accounted rooms submitted by user X in taxon Y

When a user earns a cred value of x% for a taxon X from another user, the learn-rates of all

rooms under taxon X are set to the highest value between their current values and x%.

Accounted rooms of user X are rooms with a representative probability that exceeds a certain

threshold (tentatively 70%). Only the learn-rates of accounted rooms of user X will be accounted

in that user’s cred for all taxa containing those rooms.

2. Room and representative probability (RP):

Each room is represented by a probability distribution of integer probability values from 0 to 100

(telling you the percentage of users who rated each value) and an RP. The RP of a room is

increased in two ways (tentatively, 50-50)—direct probability voting (users input a percentage

for the room’s probability) and weighted probabilities transferred from (back)propping rooms

(users input a percentage for how much they think room A is important/relevant to room B).

RP(room A) = ∑

∑

∑ ⁄

∑

Userprob (input): the probability rated by a user X for room A, in %

Usercred: the cred of a user X for the nearest taxon of room A, in %

RP(room B): the representative probability of a (back)propping room B, in %

Userweight (input): the user-rated importance of a (back)propping room B to room A, in %

Cred1, cred2: the cred(s) of a user X for the nearest taxon of room A and the nearest taxon of

room B, respectively, in %

19

3. Order of computation:

There are many objects (rooms, users, taxa, scopa) and the values (RP, learn-rate, cred)

associated with these objects are highly interconnected. They are computed using a simple

iterative algorithm. Each iteration calculates the next set of values based on the resulting set of

values of the last iteration. To avoid a feedback loop, this continues until the values converge.

If a RP exceeds a certain threshold, its room becomes an accounted room, and the RP will be

accounted in the computation of all related rooms’ RPs and all related users’ learn-rates.

Only learn-rates are stored in the database; creds are not. A cred of user X for taxon Y will be

computed when user X endorses a room, user, or prop/backprop a room in that taxon.

Therefore, the order is as follows:

Each room’s RP is computed from RPs of all accounted rooms related to it, and the creds of

the nearest taxa of all related raters.

A cred of user X for taxon Y, when called, will be computed from the learn-rates of all

accounted rooms user X has in in taxon Y.

4. Cost factor: The path to the Singularity is not smooth. It’s not to choose simply the most

obvious routes but routes we can afford. That’s why we have to keep a good check on alternate

routes’ resource consumption in order to allocate resources accordingly. Thus I’m looking into

how to associate a cost factor with each room.

[13]And then come the AIs

In the future, AIs must be heavily developed to learn from humans’ interaction with the SP to

perform a variety of complicated tasks.

1. Translating AI: translates knowledge along the Language dimension from human language to

more machine-friendly languages, at least programming language.

2. Validating AI: automatically prop or backprop knowledge to calibrate its probability.

3. Critical-thinking AI: performs a continual background scan of all of the existing rooms,

flagging those in conflict.

4. Leveling-up AI: Upon identifying contradicting rooms, this AI would chain them together, and

attempt to create a room at a Higher floor that resolves the apparent contradiction by providing a

perspective that explains both ideas.

5. Questioning AI: If the AI failed to create a unifying room, it would generate open questions

over the chained rooms, or search for current questions on Q&A websites such as Quora and

Stack Overflow. Humans would then attempt to answer these questions or extract knowledge

from current answers on Q&A websites.

6. Crossing AI: An AI will identify open questions in every discipline and search for solutions in

other disparate areas of knowledge, or provide an Insight from an apparently disconnected field.

20

7. Stitching AI: Most of the time, users would prefer reading knowledge in Wikipedia-article

style rather than browsing rooms endlessly in a 3D pyramid. They need a software to stitch

knowledge together in meaningful ways according to a wide range of criteria (e.g. probability >=

70%, within 10 floors of room A, Hard & S-Hard, rank 3) into well-organized 2D articles.

8. Analytic/predictive AI: This will be the main source of revenue. Refer to Application section.

For more understanding about the role of AIs20

to the SP, and their implications for the SS21

,

please refer to the footnote links.

[12]IX. APPLICATION

a. Phase 1: Prototype

(1) A comprehensive hierarchical knowledge map to support systematic academic research.

(2) A platform to validate problem statements, explore existing solutions to similar problems,

map all knowledge required to solve the problems, predict and map must-have features of the

solution, generate hypotheses, gather academic materials or experimental data to support each

hypothesis, etc. in preparing academic paper, project proposal, or solution to grand challenges.

(3) A platform to verify intellectual leaders’ insights, and for intellectual point-to-point critique

where each opponent can lay out assumptions, counter the other’s assumptions, back own

assumptions with further assumptions or facts or data, trace these assumptions to the deepest

level possible, and so on. Opponents may adjust their assumptions according to new information

provided be each other, split the difference, and resolve the argument; or arrive at assumptions

which either side cannot or refuse to reason beyond for subjective reasons. This platform can be

used to resolve any argument between you and your opponents simply by using a tool to overlap

your Pyrofile and theirs to see where they meet.

b. Phase 2: Full version

(4) An educational hub for users to map knowledge, keep track of their learning, follow SP-

derived principles to produce original knowledge, acquire certified knowledge from SP-affiliate

education partners and build their comprehensive online credentials (Pyrofile). A selective Board

of Experts will rate (assign a cred value of x% to each taxon covered by) massive open online

courses (provided by Coursera, Udacity, edX, etc.), programs of educational institutions or

organizations. When a user graduates, her learn-rate for all rooms in each covered and rated

taxon will be set to the higher value between their current values and x% times the user’s grade

in percentage, e.g 100% for A, 80% for B, 0% for F and so on. This will be a major application

because, in no time, all of education will be online[15]

.

(5) A tool to verify and address long-term danger/existential risks to regulate knowledge

acquisition (e.g. encourage people to study engineering rather than literature).

20

Roles of AIs to the SP http://qr.ae/qeQcw 21

From the SP to the SS http://qr.ae/qeQ6r

21

(6) Provider of a distributed platform (“Home SP”) to privately organize personal knowledge;

crowdsource/groupsource personal, military, or political planning assistance; identify

weaknesses and plan courses of actions to contain these weaknesses. For example, you can post

“I should work for Google” and “I should work for Facebook” and have your friends prop these

two options with their knowledge. In military, we can map weapons, countermeasures, counter-

countermeasures, human resources, psychological weakness, geographical advantages, public

ignorance, etc. (our own weaknesses and the enemies’).

(7) A platform to crowdsource systematic codification of hierarchical knowledge. Users can post

knowledge in rawer, more machine-friendly languages than human language, such as

mathematical language, pseudo-code, programming language, or even rawer forms. These

versions of knowledge are used to accelerate machine learning.

(8) In the face of the a paralyzing speed of academic publications worldwide (5 publications per

minute by 2013), the SP can serve as a template for academic publications so that we easily

identify the relationships between ideas, terminology, and data within a publication, between

different publications, and verify even the most technical details in these publications ourselves.

I also envision a similar template for solution submission to science competitions, so that voters

can visually investigate and compare technical advantages between solutions rather than watch

videos that tell nothing and depend heavily on production values22

.

(9) A platform for AI experiments[13]

on hierarchical and machine-friendly knowledge, which

opens the door to profitable analytic/predictive tools; also a source of problems for competitive

programming sites such as TopCoder and Kaggle. For example, a tool can monitor the collective

knowledge of a market to identify market gaps; if there is a gap between the standard of

appreciation for food, hygiene, movie, etc. of Vietnam and that of the rest of the world, you can

provide products at just above their current standards and charge as much as you want; in my

country, people love paying for crap. That tool can be applied to the business of art23

. At some

point, the SP will spawn a new breed of ultra-high-tech analysts called “Paralysts.”

(10) A complete understanding of the SP opens your mind to a wide range of everyday mental

applications24

.

[64][63]X. THEORY OF WEAKNESSES

The SP is scary, because there are countless rooms to light. If someone lights a room you haven’t,

it becomes your relative weakness to that person. No matter how High you are, you can’t always

rely on your Highest knowledge which supersede most Lower knowledge to solve every Lower

problem. You plan/tool based on such knowledge may help you succeed most of time but, in

some cases, bugs (analogous to a literal bug in a High-tech computer) will appear and you may

fail. Even the most advanced systems these days have to be regularly debugged lest being

hacked[60]

. You can be considered invincible if you own the only gun in the town, but anyone can

defeat you with as easy as a kick in the crotch unless you have expected that and trained properly.

22

Nokia Sensing XChallenge Finalists https://www.nokiasensingxchallengevoting.org/ 23

The business of art http://qr.ae/qefSR 24

A list of random everyday applications http://qr.ae/qZ7nW

22

Theoretically, a weakness has the potential to affect ALL rooms above it. In other words, it can

cause damage to all people who have lit any room above it. The relatively Deeper the weakness

is, the more damage it may cause, e.g. the Heartbleed bug that unfolded early this year25

. The one

who lit the room has the option to share it for little recognition and reward, or exploit it for more.

It’s easiest to think of weaknesses as vulnerabilities in computer sciences, which are most

documented. In the future, weaknesses in life sciences26

will be much more debilitating.

Exclusively-lit relatively-Deep room, bug, hole, loophole, gap, vulnerability, shortcoming, blind

spot, weakness—the lingo is endless, but the concept is universal. Let’s call it “weakness.”

Weaknesses everywhere

Weaknesses are mostly exposed for exploitation/fixing under extreme/life-or-death conditions

such as war[61]

. Nevertheless, they can be every bit and piece of information you miss when you

“let your guard down.” [62]

If you overestimated your security and didn't buy a good door, a thief

can break in. If you miss a piece of news about the company whose stocks you own due to lack

of connections, you lose money. If you find a hole in the law system, exploit it and make sure not

to be discovered, you can beat the system and get rich. If your neighbor is good at electrical

engineering, he can steal your electricity. If you don't check your children's DNA, you may end

up raising someone else's kids. If your IT system is imperfect, a hacker will find and exploit it or

extort you. If you are not good-looking and careless about your appearance, you can lose a job or

be bullied. If a person hates you and you don’t know, when a situation arises, he will do

everything within his abilities to harm you. If you depend on someone, your dependence is a

weakness. When I was an environmentalist, whenever one of my fellows vandalized or swore

before the press camera like an illiterate dropout, I would look worse in the public eyes. Such

person was my weakness. Every time a Vietnamese steals from a local grocery in a foreign

country, I would look worse in that country so they count as my weakness. If one of your

teammates is not good enough, greedy, emotional, has a habit, someone to die for, or any

weakness, that person’s weaknesses become your weaknesses that other teams will exploit.

The State of Israel is a perfect example of a brilliant people having their weaknesses exposed

continuously and having what it takes to fix them all. [Senor 2011] has all the examples. The

Yom Kippur war that happened on Yom Kippur, the holiest day in Judaism, reminded Israelis of

what’s more important to survival than praying, and led to the institution of the Talpiot program

to recruit the best of the best humans in all faculties in Israel to defend the nation and more. They

fixed their weaknesses (the holy day); their scientific and technological breakthroughs achieved

while Hard-rushing (in war) fluidly found their way into the global markets since no country

could have all conditions met to get that High. With those breakthroughs, their alumni and those

of Unit 8200—another Israeli miracle—found leading companies in the world such as NICE and

Check Point. US Army recently bought the Iron Dome from Israel27

—a technology that only a

country showered with rockets on a daily basis could develop. Besides war, it used to be a matter

of life-or-death for this nation to grow food on dessert. Now one of their leading companies

Netafim is exporting their agricultural technology to the whole world, their wastewater recycling

rate of 72% being the highest in the world.

25

Heartbleed https://en.wikipedia.org/wiki/Heartbleed 26

Hacking DNA http://www.theatlantic.com/magazine/archive/2012/11/hacking-the-presidents-dna/309147/ 27

US Army bought Iron Dome http://www.israelnationalnews.com/News/News.aspx/186951

23

Inherent weaknesses

However, how about inherent weaknesses? What if I’m smart and rich, but short and weak? Just

knowing that doesn’t improve anything. Doesn’t that mean there’s a permanent, no matter how

small, chance that one day I can be toyed around and killed in humiliation by a brainless brawny

thug? In order to ensure my absolute survival, I must become meta-High—mastering all

knowledge on all floors below my conscious level—to be smart and rich enough to make myself

big and strong. However, the meta-High concept should always be regarded as a goal rather than

a realistic description of any entity that may exist at all. Turning into an elite fighter capable of

dodging bullets or warding off whoever attempts on my life is not inefficient, considering how

limited my resources are and how many floors I have to master to be truly meta-High.

However, there’s no need to be desperate. Most powerful elites in world raise enough layers of

High protection around themselves to seal off their weakness which is their fragile biology. To

defeat them and survive, attackers must also master High floors to break away from the grasp of

their High protection, which diminished the attackers’ incentives to perform the attack at all. In

case of network vulnerabilities, the one to exploit weaknesses of the systems must be High

enough to succeed while maintain his anonymity. However, the High people in the society have

contained the risks of these potential weaknesses so well with their High knowledge that no one

who had the relatively Deep skills to exploit the weakness also had the High skills to escape

justice. There were countless instances of hackers, including members of the Anonymous

group28

, getting caught for their miscalculations.

To further understand inherent weaknesses, refer to the Robocop (2014) case study29

.

The Inevitable

What we have discussed above is not to zero in on apparent solutions, but to encourage you to

acknowledge and accept natural laws of knowledge and the inevitable future resulting from them.

Any knowledge/technology WILL be weaponized and put in bad use30

by criminals, terrorists,

and hackers as long as the weaknesses inherent to us as a species (emerging from both our brains

and biological bodies) exist as targets for entities with fewer weaknesses to exploit and benefit

from. It is ineffective to encourage people to develop technologies “responsibly.”31

Exponential technologies will entail exponential weaknesses as they guarantee exponentially

widening gaps and holes in our knowledge for criminals to exploit, just like a fast growing IT

system harboring more and more vulnerabilities for hackers to exploit32

. Developing Higher

power (authority, money), technology (Internet of Things, synbio), and conscious level

(realization of profit from destruction) will only add more dark floors below—weaknesses.

28

Arrests of the Anonymous https://en.wikipedia.org/wiki/Anonymous_(group)#Arrests_and_trials 29

Robocop (2014) case study http://qr.ae/qZ8e7 30

Exponential crime http://www.ted.com/talks/marc_goodman_a_vision_of_crimes_in_the_future 31

Build the future “responsibly” http://singularityhub.com/2014/11/20/summit-europe-artificial-intelligence-

evolving-from-disappointing-to-disruptive/ 32

Massive bank attack http://money.cnn.com/2014/08/28/technology/security/bank-hack/index.html

24

Only with a powerful information tool such as the SP can we ascend High enough to come up

with not just strategies to address each threat separately, but even much Higher plan to seal off

our weaknesses completely.

The SP as a game

Why do I have to play the SP? Can’t I just learn instead of competing? It’s up to you. However,

over time, the SP will resemble a virtual reality rather than an “online knowledge mapping

system.” Like in any reality, competition is inevitable, as implied above.

The bottom line is: inside the SP, it contains an incomplete theory about itself.33

So, if you use

the SP but there're still things you do not know about it, they will become your weaknesses. This

will remind you forever that you reek of weaknesses and had better hurry up get High!

The Higher you get, the more you will feel like playing a game with your everything at stakes.

You interactions with knowledge at such levels will bring about enormous consequences. And

your Pyrofile will be one of your primary weapons when we introduce a feature that lets you set

the “conditional visibility” of separate parts of your Pyrofile. It means only users who meet

certain conditions can see the parts you want to hide.

Also, it’s worth noting that the moment High dark rooms (dark secret of the government,

military, and corporations) are open to you and the public, their first explorers—the Highest

masterminds will have moved up to the next floors. So it is an endless race.

But don’t worry! My goal in proposing the SP is to leverage the power of knowing and empower

you, giving you another tool to close the gap between yourself and those near the top. So the

bottom line is the SP will provide a paradigm-High knowledge service and learning experience

compared to Wikipedia. The chance is for everyone, but the reward is not.

XI. MY NEXT STEP

Honestly, right now I do not have enough technical expertise to build the SP. I have started

learning to code again but I still need your help. I believe if the SP concept is powerful enough

and its implications profound enough, people with complementary skills will join me. My plan is

to seek feedback on the concept, gather like-minded fellows, seek technical advices and

endorsement, apply to certain incubators (which I have chosen since 2012), acquire must-have

technical skills and knowledge as fast as possible through MOOCs and programming books

(which I have bought since last year), go to an incubator next year, meet technical partners and

work on this project full-time with the intention of a building startup in mind.

I have envisaged a prototype for when I can go to my dream incubator, where I will ask all

project teams to put their projects on the SP—map their Insights to find like-minded partners,

verify their problem statements with facts and data, their Insights about possible solutions, lay

out all knowledge required for their solutions (neuroscience, nanotech, synbio, AI, etc.), predict

Higher problems to solve next so that the effects of their current solutions will not be soon

33

The consciousness of the SP http://qr.ae/qSmOI

25

obsolete, identify which parallel efforts are needed, how the processes and outputs of all projects

incubated there overlap, etc. This would be a win-win for both me and those teams.

This project and another one are my life. Except for technical knowledge, I have a firm grasp of

the concept, its implications, and its “real” plan for the future—the future that I want to live in. If

not for that, I wouldn’t live another second. To borrow Eric Schmidt’s and Jonathan Rosenberg’s

words in “How Google Works,” I want to bet on an unimaginable future, because such big bets

can sometimes be easier to achieve than small ones, since they attract the best people.

XII. INTERPRETATIONS & NOTES

[6]Limitations of Wikipedia: users’ ratings are equally weighted; information is linearly sorted

with no meaningful order; has semantic structures but presents no big picture. Solutions: take

user credentials into account, and add three dimensions.

[7]Limitations of Google: ratings are based on the page’s quality rather than the knowledge’s

probability; information is linearly sorted with no meaningful order; has the Knowledge Graph

but no big picture. Solutions: add three dimensions.

[11]The Singularity is expected to be near the Top, but not literally at the Top. The Theory of

Everything should be comparatively closer to the Top. I doubt humans will survive to witness

what lies at the Top.

[15]Opportunities in education:

Over the next five years or so, all of education—K-12, college, and graduate school—will be

online, in every major language. Companies like Google and others are working to bring very

low cost, or no cost, Internet to everyone in the world. In the future, we will see very high quality

education, both in terms of online education with human thinkers, as well as computer-assisted

instruction by artificial intelligence, thus providing higher quality education to everyone. There

will need an educational hut to arrange that huge amount of high quality education in one place

so that users can record and share their life of learning in a single place34

.

[8]An incomplete list of my questions in life in four main sets:

1. The structure of knowledge: How can I put all knowledge in the same picture? The whole

picture comprises of all fields. People are going up and down without anticipating where to

meet halfway in order to hold hands and walk up to the Top together. Why didn’t high school

34

A Q&A with Ray Kurzweil http://roi.ted.com/2014/10/15/singularity-university-the-future-of-education-and-the-

evolution-of-search-a-qa-with-ray-kurzweil

26

teachers teach mathematics, physics, chemistry, and biology as a seamless body of science

where biology emerges from chemistry, which in turn emerges from physics, while

mathematics is the seed of science that describes everything? In theoretical physics, why

didn’t scientists from two camps (string theorists who go bottom up and model builders who

go top down) work hand in hand trying to meet somewhere in the middle? If scattered in the

body of religious knowledge to date are tiny pearls of truth/real knowledge then how should

they be positioned compared to scientific knowledge? Should scientists take leaps of faith for

unlikely breakthroughs? What does it take to draw a roadmap to the Singularity?

2. The map of a humans’ consciousness:[3]

Why can’t big minds agree on everything with each

other? Why are some of the most intelligent people I know in their fields so naïve and

ignorant in worldly matters, and not conscious at all of the hidden danger threatening our

lives every second? How can I convince very intelligent people who have huge ego to sit

down and point out their elusive deficiencies in order to work out real solutions together?

How can I convince people who love or hate Hitler or other monstrous historical figures that

they were inevitable existence born out of the context of history rather than good or bad

people? How can I prove the relative and probabilistic nature of the reality (nothing is

absolutely true and everything is governed by a probabilistic distribution)? Do levels of

consciousness exist (People of higher level of consciousness are exposed to certain

knowledge that enables them to realize things closer to truth or on a larger physical scale.)

and how can I visualize someone’s consciousness? How can I really put myself in someone’s

shoes to understand why that person’s view is so glaringly contrasting to mine?

3. The reason for variety: Why are people still enjoying 2D games (Flappy Bird) while there are

so many awesome 3D games? Why not create the best thing but the best things? Why can’t I

have a one-size-fits-all all-time strategy? Why do people suddenly fall in love with retro-

styled music or fashion? Why do we still have martial arts while we have weapons? What

exactly do the arts of gardening, dancing, gourmet cooking, fine dining, fashion, photography,

poetry, etc. contribute to the humans’ progress towards the Singularity? Why are there

always people who over-appreciate particular inane forms of art (Mark Rothko’s black-on-

black—abstract expressionism—or Kasimir Malevich’s white-on-white—suprematism) and

junk teen bestsellers (Beth Reekles’s The Kissing Booth and Maya Van Wagenen’s Vintage

Wisdom for a Modern Geek)? Why did junk teen novelists like Beth Reekles and Maya Van

Wagenen become two among The 16 Most Influential Teens of 2013? How could Nikita

Singh become such a best-selling Indian novelist if her best known works were named

“Love@Facebook” (2011), “Accidentally in Love…With Him? Again?” (2011), “If It's Not

Forever...It's Not Love” (2012), “The Promise” (2012), “Someone Like You” (2013), “The

Unreasonable Fellows” (2013), “Right Here Right Now” (2014)?

4. The nature of war and peace: Why does war exist? Does absolute peace exist? Why do

people fight? Are all kinds of violence and crime (robbery, murder, protest, IT hacking, etc.)

during peace time just another manifestation of war? Why do we need red team exercises in

computer science and life sciences? As long as there is profit in war, can there really be no

more war? Why were there many scientific breakthroughs in war that lead to the invention of

the computer and the Internet? What are the benefits of war? What exactly did wars

contribute to the collective sum of human knowledge? How did the process of developing

27

weapons and defense systems against certain weapons and uncertainty contribute to the

collective sum of human knowledge? Isn’t it true that every time a hacker found and

exploited a vulnerability for profit, the vulnerability will be fixed and the IT system will get

one step closer to perfection? Are all kinds of damage and losses the costs of collective

improvement and perfection?

[16]Business model:

Free services: research activities (able to keep track of frequent content updates), data mining, AI

testing (pay if discontinued due to low content endorsement rate), and Home SP for

personal/organizational uses.

Paid services: advanced analytic/predictive tools (document parsing, market niche brute force

search, like-minded partner search), result sharing from AI developers, education (affiliate

institution rating), assess to hidden Pyrofiles (pay to Pyrofiles’ owners who are willing to sell

their content), headhunting (candidate search, assessment), job requirement analysis (based on

current employees), media (paid by journalists and news outlets who use SP format), etc.

[22]Wisdom and Intelligence:

One thing in RPG games that I think reflects real life is the separation of a character's two

attributes Intelligence and Wisdom. I have met very intelligent people who are experts in their

fields but naive and ignorant in most worldly matter. They could make instant calculation or

draw very complicated blueprints of buildings and machineries but couldn't understand why the

Titanic sank or why 11/9 happened or how disaster capitalism worked.

Many intellectual elders in my country think that Americans simply waged wars in our country

out of monetary greed. In most cases, high Wisdom requires high Intelligence, but not vice versa.

It’s easier to imagine an entity with extreme intelligent rather than on with extreme wisdom. For

example, the “ultra-intelligent” character Schön in Macroscope (1969) could play games and do

almost everything perfectly but never thought of living forever or dominating the universe. On

the other hand, the evil genius in Oliver Emberton’s to-be-published novel35

is comparably wiser

to advance his agenda and dominate the world, laying the foundation for his descendants to

achieve even more.

Deriving from important concepts in the SP, I have attempted to redefine Wisdom (which is

largely based on the Highest floor level one has reached) and Intelligence[23]

.

[24]The SP in comparison with Google Knowledge Vault: People as users are evolving/interactive

part of the picture rather than just static objects; presents a big picture; seek High human

subjective Insights rather than just objective knowledge; the purpose is not “ask me anything”;

35

Evil genius takes over the world http://qr.ae/qSLHD

28

knowledge creation is guided. If Google's mission is to organize the world's information, the

SP’s mission is to organize the collective body of knowledge.

[26]The Deeper, the scarier:

American scientist Herbert A. Simon, in describing an AI program called EPAM, wrote in 1973

that to understand the mysterious EPAM program, he would provide us with three versions of the

explanation. One would be the form in which it was actually written (programming language)

with its whole structure of routines and subroutines. Alternatively, he could provide us with a

machine-language version of EPAM after the whole translation had been carried out. The third

would be the electromagnetic equations and boundary conditions that the computer, viewed as a

physical system, would have to obey while behaving as EPAM. That would be an acme of

reduction and incomprehensibility. [Kurzweil 2012]

[29]The expert manager was itself a software program that was programmed to learn the strengths

and weaknesses of these different systems by examining their performance in real-world

situations. It was based on the notion that these strengths were orthogonal; that is, one system

would tend to be strong where another was weak. Indeed, the overall performance of the

combined systems with the trained expert manager in charge was far better than any of the

individual systems.

[36]Bouncing between the Deep and the High:

High applications of mathematics in engineering and theoretical physics have driven much

development in Deep mathematics. Conversely, a Deep achievement36

in mathematics, logic, or

algorithm can usher a cascade of High technological wonders. In fact, the Highest theories

mostly depended on invention of more mathematics37

and more mathematics is always needed to

develop Higher theories38

. Computer scientists regularly bounce between developing Deep

algorithms (for the software) and building faster computers/networks based on High technologies

(for the hardware). In far future, the development of Deep computronium language will optimize

calculations of High ToE equations.

One of my favorite bounce happened when I learned about the probabilistic nature of reality

through the equations of wave functions and Schrödinger's equation (Deep). Thereafter, I only

describe things as “probable” rather than “accurate.” I also realized that if wave functions really

never collapse then the reality that we perceive is merely the interference between all the wave of

every quantum in our brain and body with that of every quantum in the universe. I found an

allegory in Young’s double-lid experiment with photons, where the visible light bands are the

reality while the waves of the photons are always present but invisible. That means everything is

36

Take over the world after proving P=NP http://qr.ae/qSLiG 37

Inventing mathematics http://qr.ae/qSLJe 38

Need more mathematics http://qr.ae/qS0NW

29

predetermined, which resonates Einstein’s quote “God doesn’t play dice.” Yes, he doesn’t play

dice because he has known the dice’s wave function and all of its possibilities! Hence my

original expansion of Einstein’s quote “God doesn’t play dice, because He sees all sides at once”

and the huge dice showing three sides with a dark top on the 1st page of this paper.

[42]Abstraction in mathematics is the process of extracting the underlying essence of a

mathematical concept, removing any dependence on real world objects with which it might

originally have been connected, and generalizing it so that it has wider applications or matching

among other abstract descriptions of equivalent phenomena. Two of the most highly abstract

areas of modern mathematics are category theory and model theory. One of the advantages of

abstraction is: It reveals deep connections between different areas of mathematics. Known results

in one area can suggest conjectures in a related area. Techniques and methods from one area can

be applied to prove results in a related area.

[43]Why we need Soft, Hard, and S-Hard while S-Hard is all we needs to reach the top?

If a perfect AI magically sprang into existence, in no presence of humans, it would gather only

knowledge at the Core, which is all it needs to reach the top of the pyramid. Unfortunately, it has

to be created by humans, so it needs Hard knowledge to co-exist with humans. On the other hand,

humans are living organisms so, in order to stay alive and productive, we need all sorts of Soft

knowledge—entertainment, tasty food, fun, joy, love, fashion, touch, art, photography, fiction,

sex, reward, music, flower, bar, club, firework, emotion, party, movies/books that elaborate

trivial life philosophies (Mr. Nobody39

, Cloud Atlas40

), etc. As a result, humans have to fill up

Soft, Hard, and S-Hard knowledge simultaneously until the Core has filled up enough for an AI

to use it to fill up the rest of the Core.

[44]Computronium:

“According to the law of accelerating returns, by the end of this century we will be able to create

computation at the limits of what is possible, based on the laws of physics as applied to

computation. We call matter and every organized in this way “computronium,” which is vastly

more powerful pound per pound than the human brain. It will not just be raw computation but

will be infused with intelligent algorithms…. The potential of matter to compute is also governed

by a very small number, Planck’s constant 6.6x10-34

joule-seconds. This is the smallest scale at

which we can apply energy for computation. We obtain the theoretical limit of an object to

perform computation by dividing the total energy by Planck’s constant. Lloyd shows how the

potential computing capacity of a kilogram of matter equals pi times energy divided by Planck’s

constant. Since the energy is such a large number and Planck’s constant is so small, this equation

generates an extremely large number: about 5x1050

operations per second.” [Kurzweil 2012]

39

Mr. Nobody http://www.imdb.com/title/tt0485947/ 40

Cloud Atlas http://www.imdb.com/title/tt1371111/

30

[45]Quotes on the language of thought:

“I very rarely think words at all. A thought comes, and I may try to express it in words

afterwards.” – Albert Einstein.

“As we experience our own thoughts and memories, we “know” what they mean, but they do not

exist as readily explainable thoughts and recollections. If we want to share them with others, we

need to translate them in to language.” [Kurzweil 2012]

[47]Why a probability distribution of probabilities (PDP) but not simply a probability distribution

or probability or just a Boolean value of true and false?

It’s simple—to provide more information. We could have used a probability distribution of

probability distributions of probability distributions of… Unfortunately, I don’t think most

people would find such level of complexity meaningful and useful. If a room has a tentative

representative probability of 50%, a PDP would suffice to help you distinguish between these

different cases: (1) everyone has the some opinions, e.g. everyone rated 50%, (2) everyone has a

different opinion, e.g. ratings are evenly distributed from 0% to 100%, and (3) there are two

opposite camps, e.g. half of the ratings are 0% and half 100%.

[59]Why are all Conceptual levels needed (not just the Highest)?

“It would be extremely difficult to interpret what these higher level patterns meant without

actually copying all of the information at every level into our own cortex. Thus each pattern in

our neocortex is meaningful only in light of all the information carried in the levels below it…. if

we were able to detect the pattern activations in someone’s neocortex, we would still have little

idea what those pattern activations meant without also having access to the entire hierarchy of

patterns… below each activated pattern. That would pretty much require access to that person’s

entire neocortex.” [Kurzweil 2012]

[61]Those who can't fix their weaknesses in war either perish or have to compensate for them with

more strengths. There are three common types of war:

1. Violent war: armed conflict between countries, colloquially referred to as "war". [70]

All kinds

of weaknesses in strategy, intelligence, discipline, mental toughness, technologies, risk

management, etc. are exposed on the battlefield. If you can't defend against just a single type of

projectile, it's a weakness. If your bullets can't pierce through enemy's walls, it's a weakness.

They are exploited by one side and fixed by the other. That's how warfare knowledge evolves.

But this type of war is the most costly and thus the last resort a country has to employ after all

other types of war have failed.

This may sound ridiculous but have you ever imagined what happens if we are attacked by aliens,

literally? That's when we need flawless "weapons" and flawless "armors." And the only way to

31

achieve anything "flawless" is to constantly searching for and fixing flaws or weaknesses. As a

result, humans always fight among ourselves, because no one would simply point out others'

weaknesses for no reward while such weaknesses can instead be exploited and benefited from.

Since human beings are eternally at war with nature/uncertainties, we never who what may come

at us. That's why we are subconsciously developing the best "weapons" and "armors" in

preparation for existential threats by fighting among ourselves.

2. Political war: boycott, assassination, and any kind of political pressure. If someone can

pressure you in any way, it's your weakness. One only resorts to violent war if one has failed the

political war.

3. Economic war: by financial, monetary, or competitive means. After failing the Vietnam

(violent) war, the US reverted to fighting the economic (and political) war by impoverishing the

country in the most subtle way, exploiting the incompetence and ignorance of its people. Luxury

brands open branch offices to drain this country's capital through government officials who

lavish on Ferrari, Bentley, LV, etc. People here also can't create good enough businesses to

compete with US companies (just good enough to drain their own ignorant people). These are all

weaknesses. The Israelis had an even lower starting point but they were evolutionary masters

who could fix all of their weaknesses to climb to the top. In Start-up Nation41

you can find how

all sorts of war (especially violent war) continuously expose the Israelis' weaknesses and forced

them to fix them or perish.

4. My definition of war extends beyond the common scope to include a 4th

type of war—the

most fundamental and most subtle one: the "war in all aspects of life", involving any invisible

transfer of resources that takes place every heartbeat[62]

. This type of war shares many

characteristics with economic war (each type of war shares characteristics with adjacent ones, e.g.

political war can be both violent and economic). The victims of this type of war are not killed.

They are only ripped of something (mostly financial resources), forced down the bottom of the

society, and occasionally driven to optionally suicide.

[21]The Free-lunch Zone emerges from virtually every molecule making up the human body and

their particular arrangement, especially the brain. This set of knowledge does not exactly

resemble a “zone” but is scattered across the SP. They can obtained effortlessly, early, intuitively,

unconsciously by humans thanks to the information encoded in the human genome, aimlessly

refined over millions of years of evolution, including reflexes and instincts. Evidently, [Kurzweil

2012] stated that the wiring and synaptic strengths within each physical pattern recognition

module of the brain are determined genetically—that is, the organization within each pattern

recognition module is determined by genetic design. The amount of unique information after

lossless compression as applied to the brain is about 25 million bytes.

While humans are born with the biggest Free-lunch[34]

(25 million bytes), other animals also

enjoy it to some extent[19]

. All knowledge in Free-lunch Zone provides Hints to refine current

theories or inspire new theories. Most humans are not conscious of their Free-lunch (unconscious

knowledge) because such consciousness requires a Higher conceptual level.

41

http://www.amazon.com/Start-up-Nation-Israels-Economic-Miracle/dp/0446541478

32

XIII. EXAMPLE

[4]Attaching questions to rooms facilitate verification:

Questions in chemistry: What do we get from a reaction between an acid and a base? What may

happen at low or high temperature, low or high pressure, with one catalyst or more, or in other

exotic conditions?

Broader questions: What is our mission? Is it to survive by expanding and improving our

habitat? We can achieve that with technology. Technology is converging at exponential rate but

it’s not made happened by Moore or God. It only happens if we prepare the ground for it. How

can we that? Do we have enough money and people to work on it? What prevents us from having

enough? Are the risks political, economic, social, or physical? How can we minimize them?

Why not attract even more investment and brainpower? Where are people investing the most in?

What are the brightest people working on? Why are they doing that? What are their incentives?

Which sectors do the demands come from? Who are demanding what? Why are they demanding

those but not these? Are they aware of the problems we are trying to solve? Are they not aware

of the existential danger we are aware of? Why can’t they be? How can we make them be? What

are the costs of doing so? By the way, what are we trying to solve? Who are we trying to help?

Why are we helping them? Are they the same? What are the costs? Can we afford the costs?

How much do the costs vary according to who and how many we help? What are the risks

involved in high costs? Can we take the risks? How can we reduce the costs? What and who are

hindering our progress? How can we stop them from hindering us? What are the options? What

are the costs of each option? Which one can we afford? How much do we need? Who do we

need? How can we get that much money and the people we need? Whom should we be honest to

and whom should we hide things from? Why should we be honest? What are other criteria and

standards besides honesty must we abide by? Why do we have to abide by them? What are the

costs of abiding by them? Can we afford them? Do they matter more than our survival? Is it OK

to be extinct?

[18]Leading intellectuals with contrasting views:

There are many examples of disagreement/never ending arguments between leading intellectuals

in politics, economics, and sciences. Those I stumbled upon lately are between David S. Rose

and Ray Kurzweil42

on technological unemployment, Ray Kurzweil and Miguel Nicolelis43

and

Ray Kurzweil and Paul Allen44

on the plausibility of the Singularity, Deepak Chopra and

Richard Dawkins (though we all know Chopra is mostly wrong) on consciousness and “quantum

healing,” Paul King and Bradley Voytek over a neuroscience-y answer45

, etc.

Early this year, I sat with a respected education expert who studied in prestigious schools in the

US. We turned out to be disagreeing on every single opinion regarding education in our country.

42

On robotic workforce causing unemployment http://qr.ae/qJXHY 43

A “bunch of hot air” http://singularityhub.com/2013/03/10/leading-neuroscientist-says-kurzweil-singularity-

prediction-a-bunch-of-hot-air/ 44

The Singularity isn’t near http://www.technologyreview.com/view/425733/paul-allen-the-singularity-isnt-near/ 45

On bad neuroscience http://qr.ae/qJ7WR

33

I countered every answer from him with a question and finally arrived at our fundamental

differences. First, he had the wishful thinking that the government HAS TO do good for their

people because they has the authority, money, manpower, and are voted by the people for the

people. When I asked “Why do they have to?” he could only say “Because they have to.”

Likewise, he had a jelled assumption that the fault always belonged to the government rather

than the people. It's like blaming movie directors and actors for making junk movies instead of

the audience who paid for junk like that in the first place and did nothing to change that. As I

attempted to change the topic by saying “WWII was bad thing, but would we still have

computers and the Internet today if it hadn’t happened?” he precluded our intellectual discussion

with his emotional account, saying “Absolutely nothing good came out of war because I lost my

best friends in the war.”

It’s not because they are not smart and logical enough to reason beyond their own assumptions

but because they may have been too focused in their fields of specialization, not open to new

streams of information, got used to a tunnel narrow view, too emotionally traumatized or clouded

by their ego to logically accept certain conclusions. Most awakened elites hide in the dark.

[19]Animals’ Free-lunch: “A mother rat will build a nest for her young even if she has never seen

another rat in her lifetime. Similarly, a spider will spin a web, a caterpillar will create her cocoon,

and a beaver will build a dam, even if no contemporary ever showed them how to accomplish

these complex tasks. That is not to say that these are not learned behaviors—they learned them

over thousands of lifetimes. The evolution of animal behavior does constitute a learning process,

but it is learning by the species, not by the individual, and the fruits of this learning process are

encoded in DNA.” [Kurzweil 2012]

[27]“Simple” High rooms:

High theories/models may look very simple and concise, e.g. this equation for intelligence46

, but

if they are exhaustively expanded, they may be kilometers-long, e.g. the equations of string field

theory47

.

In another example, “there are two approaches you can use to catch a fly ball.” The Low

approach is to “solve the complex simultaneous differential equations controlling the ball’s

movement as well as further equations governing your own particular angle in viewing the ball,

and then compute even more equations on how to move your body, arm, and hand to be in the

right place at the right time.” The High approach that your brain adopts is to “basically simplifies

the problem by collapsing a lot of equations into a simple trend model, considering the trends of

where the ball appears to be in your field of vision and how quickly it is moving within it, It does

the same thing with you, making essential linear predictions of the ball’s apparent position in

your field of view and that of your hand,. The goal, of course, is to make sure they meet at the

same point in space and time. If the ball appears to be dropping too quickly and your hand

appears to be moving too slowly, your brain will direct your hand to move more quickly, and so

46

New equation for intelligence http://www.ted.com/talks/alex_wissner_gross_a_new_equation_for_intelligence 47

Michio Kaku on string field theory https://www.youtube.com/watch?v=RxP8UpPgiSM

34

that the trends will coincide. This “Gordian knot” solution to what would otherwise be an

intractable mathematical problem is called basis functions, and they are carried out by the

cerebellum.” [Kurzweil 2012]

[30]Breakthroughs achieved in war:

“In 1939 Turing designed an electronic calculator called Bombe that helped decode messages

that had been encrypted by the Nazi Enigma coding machine. By 1943, an engineering team

influenced by Turing completed what is arguably the first computer, the Colossus, that enabled

the Allies to continue decoding messages from more sophisticated versions of Enigma…. It was

on these foundations that John von Neumann created the architecture of the modern computer….

Called the von Neumann machine, it has remained the core structure of essentially every

computer for the past sixty-seven years.” [Kurzweil 2012]

There are many examples of breakthroughs in agriculture when soldiers had to camp on dessert,

breakthroughs in robotics to create super-soldiers’ exoskeletons and provide precision

ammunition delivery with drones, and breakthroughs in computing/network for advanced

cryptography and code-cracking.

[49]Dr. Kurzweil’s account on reconciling contrasting concepts by going Higher: “The overriding

theme was “many paths to the truth,” along with tolerance and transcendence. This last idea

meant that resolving apparent contradictions between traditions does not require deciding that

one is right and the other is wrong. The truth can be discovered only by finding an explanation

that overrides—transcends—seeming differences, especially for fundamental questions of

meaning and purpose. This is how I resolve the Western-Eastern divide on consciousness and the

physical world. In my view, both perspectives have to be true.” [Kurzweil 2012]

[46]Examples of Insights: Insights are everywhere

48 and becoming increasingly cheap. Most are

low-prob and Approxes to Higher Symmetries.

1. "There is no such thing as society."—Margaret Thatcher

2. “God don’t play dice.”—Albert Einstein

3. “The less government intervention, the better”

4. “We’re living in a money-is-everything world. Rules are created so that the rights to violate

rules can be transacted.”

5. “A man's judgment cannot be better than the information on which he has based it.”—Arthur

Hays Sulzberger

48

Political insights in “House of Cards” http://qr.ae/qJ7St

35

6. “No one can be trusted.”

7. “Simplicity is beautiful.”

8. “Less is more.”

9. “If you get something easily, you will not treasure it.”

10. “All lives are equal.”

[34]Examples of Free-lunches:

1. The brain understands that social ties directly correlate to physical security—the more people

we know, the greater chance we have of finding a mate, a new job, a better future. This is also

one of the reasons we process physical pain in the exact same neuronal regions we process social

pain—the systems are strongly coupled. This is also one of the reasons we process physical pain

in the exact same neuronal regions we process social pain—the systems are strongly coupled

[Kurzweil 2012]

[69][53]Examples of Hints: “Every creation of God contains Hints”

1. Human beings’ “deep core capability of recognizing patterns.” [Kurzweil 2012]

2. The orderly model of parallel flows of patterns up the conceptual hierarchy and of the

prediction down the hierarchy [Kurzweil 2012].

3. The hierarchical structures in language hint at the hierarchical structure of our thinking and the

neocortext, which in turn hints at the structure of knowledge. “The innate ability of humans to

learn the hierarchical structures in language that Noam Chomsky wrote about reflects the

structure of the neocortex. In a 2002 paper he coauthored, Chomsky cites the attribute of

“recursion” as accounting for the unique language faculty of human species. Recursion,

according to Chomsky, is the ability to put together small parts into a larger chunk, and the use

that chunk as a part in yet another structure, and to continue this process iteratively. In this way

we are able to build the elaborate structures of sentences and paragraphs from a limited set of

words.... the capability he is describing is exactly what the neocortex does.” [Kurzweil 2012]

4. Redundancy: The brain uses Shannon’s principle in storing knowledge, especially important

knowledge, with a substantial amount of redundancy. Popular writers use this too to make their

ideas stick deeper in readers’ mind. So far I has been too stubborn, sticking to my unreasonably

idealistic rule of “one iteration per idea across the whole text,” to follow this Hint. Now, for the

first time in my life, I repeat important points over and over again in this paper.

5. “Sparse coding”: The data reduction of biological sensory systems, e.g. the optic nerve. In the

AI field, they found in creating artificial systems that throwing most of the input information

away and retaining only the most salient details provides superior results. Otherwise the limited

ability to process information in the neocortex gets overwhelmed [Kurzweil 2012].

36

6. Human auditory perceptual system: The processing of auditor information from the human

cochlea through the subcortical regions and then through the early stages of the neocortex has

been meticulously modeled by Lloyd Watts and his research team at Audience, Inc. They have

developed research technology that extracts 600 different frequency bands (60 per octave) from

sound. This comes much closer to the estimate of 3,000 bands extracted by the human cochlea

(compared with commercial speech recognition, which uses only 16 to 32 bands). Using two

microphones and its detailed (and high-spectral resolution) model of auditory processing,

Audience has created a commercial technology (with somewhat lower spectral resolution than its

research system) that effectively removes background noise from conversations. This is now

being used in many popular cell phones and is an impressive example of a commercial product

based on an understanding of how human auditory perceptual system is able to focus on one

sound source of interest [Kurzweil 2012].

7. The whole concept of evolution: random little changes filtered by the environment over

countless generations. This Hint inspires Genetic Algorithms.

8. Neuronal leakage: “A small amount of leakage from one cortical connection to another,

resulting from the way that biological connections are formed: The electrochemistry of the axons

and dendrites is apparently subject to the electromagnetic effects of nearby connections….

Suppose we conducted such an experiment and found that the cortical circuits worked less

effectively without the neural leakage (or interneural cross talk). We might then conclude that

this phenomenon was a very clever design by evolution and was critical to the cortex’s achieving

its level of performance.” [Kurzweil 2012]

9. In the eye of a chicken, a new state of matter comes into view49

. Along with eggs, soup and

rubber toys, the list of the chicken's most lasting legacies may eventually include advanced

materials such as self-organizing colloids, or optics that can transmit light with the efficiency of

a crystal and the flexibility of a liquid.

10. Ant colony optimization is based on the ideas of ant foraging by pheromone communication

to form paths, primarily suited for combinatorial optimization and graph problems.

11. Bees algorithm is based on the foraging behavior of honey bees. It has been applied in many

applications such as routing and scheduling.

12. Cuckoo search is inspired by the brooding parasitism of the cuckoo species. It also uses Lévy

flights, and thus it suits for global optimization problems.

13. Particle swarm optimization is based on the ideas of animal flocking behavior.

14. Grey Wolf Optimizer mimics the leadership hierarchy and hunting mechanism of gray

wolves and is suitable for solving continuous optimization problems.

15. Firefly algorithm is inspired by the behavior of fireflies, attracting each other by flashing

light. This is especially useful for multimodal optimization.

49

New state of matter in a chicken’s eye http://phy.so/312467862

37

[54]Examples of Approxes:

1. Dharmendra Modha’s cell-by-cell simulation of the brain is an Approx to Markram’s full

brain simulation at molecular level in near future

2. Henry Markram replaced neuron-by-neuron model with a modular model of neocortex after

discovering a key module of several dozen neurons that is repeated over and over again in the

neocortex, demonstrating that learning is done by these modules and not by individual neurons.

Dr. Kurzweil used an HHMM-based cortex. Before that, Frank Rosenblatt’s Perceptron was built

from electronic models of neurons.

3. Mendelian inheritance of Gregor Johann Mendel was integrated with chromosome theory of

inheritance of Thomas Hunt Morgan to become the core of classical genetics which is the

Approx of modern genetics based on Deep knowledge of the DNA.

4. Newtonian mechanics (Low-Shallow) is approximation of general relativity (High) and

quantum mechanics (Deep). General relativity (High) and quantum mechanics (Deep) are

approximation of Theory of Everything (High).

Examples of going High:

1. Algebra started with methods of solving problems in arithmetic.

2. High math: mathematics underlying theoretical physics, mathematical models of complex

systems such as the brain, the human immune system, an aircraft, fluids, the financial market,

high-dimensional brane intersection, etc.

Examples of going Deep:

1. In the Principia Mathematica on the foundations of mathematics written by Alfred North

Whitehead and Bertrand Russell, it took a few hundred pages to prove 1+1=250

.

2. The systematic search for the foundations of mathematics started at the end of the 19th century

and formed a new mathematical discipline called mathematical logic.

[38]Examples of bottom-up and top-down combination:

1. Type I (bottom-up starts at the current top instead of the bottom): “We primed the system with

the intuition of human experts (for the initial settings of the parameters of each pattern

recognizer) and then had the AI system automatically refine these estimates using a learning

process from real examples of speech.” [Kurzweil 2012]

50

1+1=2 https://en.wikipedia.org/wiki/Principia_Mathematica#mediaviewer/File:Principia_Mathematica_54-43.png

38

2. Type I: “the Knowledge Vault… combines noisy extractions from the web together with prior

knowledge, which is derived from existing knowledge bases. This approach is analogous to

techniques in speech recognition, which combine noisy acoustic signals with priors derived from

a language model.” [Dong 2014]

2. Type II (top-down is low-prob, “can’t know even if correct”; bottom-up is high-prob, but can

turn out all wrong in the end): In theoretical physics, there are two camps. String physicists build

the mathematical foundation bottom-up while model builders employ their High insights to build

models that may lead to new phenomena at potentially accessible energy scales. If the LHC sees

the kinds of effects predicted by these models, there will be some well-deserved Nobel prizes for

the people involved in this story, though this seems highly unlikely. As both approaches are

time-consuming, they are somehow getting together with hope of speeding up the progress.

“Early on, the battles between the merits of the two opposing viewpoints – string theory and

model building – were fierce, with each side claiming better footing on the road to truth. Model

builders thought that string theorists were in mathematical dreamland, whereas string theorists

thought that model builders were wasting their time and ignoring the truth. Fortunately, things

have now changed. ….many of us now think about string theory and experimentally oriented

physics simultaneously. I have continued to follow the model building approach in my research,

but I also incorporate ideas from string theory…. The communities are no longer so rigidly

defined, and there is more common ground. Both scientifically and socially, there are now strong

overlaps between model builders and string theorists. In fact, because our research didn’t directly

challenge string theory models, the string theory community actually accepted and recognized

the significance of our work sooner than the model-building community.” [Randall 2005]

“The fact that branes are an important part of modern string theory meant that string theorists

took an interest in this kind of model-building. In particular, the fact that the Randall-Sundrum

model uses the same AdS geometry and has interesting relations to AdS/CFT has drawn a lot of

interest from string theorists. Whatever you think of all this as physics, as academic politics it

was an absolute stroke of genius, defusing a bitter conflict.” Without working with model

builders, string theorists alone would be held “accountable for the theory’s inability to actually

predict anything or even lead in any well-defined way to a specific class of models that could be

tested.”51

3. Type III (top-down manages, does High thinking; bottom-up does the detailed, Deep job):

Computer-assisted drone pilot. Only when the software is bugged or the hardware gets cranky

does the pilot have to sit down to fix Deep technical issues/manually control the drone.

4. Type IV (“box down”: top-down represents a box or constraints; bottom-up tries to fill the

box): “GAs used by researchers at General Electric were able to come up with jet engines

designs that met the constraints more precisely than conventional methods.” [Kurzweil 2012]

5. Type V (top-down starts first to guide bottom-up; switch back and forth in specific cases; best

managed by an expert manager): “If we plot natural-language-understanding accuracy against

the amount of training data analyzed, rule-based systems have higher performance initially but

51

http://www.math.columbia.edu/~woit/wordpress/?p=250

39

level off at fairly low accuracies if about 70%. In sharp contrast, statistical system can reach the

high 90s in accuracy but require a great deal of data to achieve that…. [Hand-coded rules] offer

adequate initial accuracy, so that a trial system can be placed into widespread usage, where it

will improve automatically. Secondly, they provide a solid basis for the lower levels of the

conceptual hierarchy so that the automated learning can begin to learn higher conceptual levels.”

[Kurzweil 2012]

6. Type VI (High-Deep collaboration): With my Insights, I can give the engineer team building

the SP a sense of directions and ideas for specific features to add in. With your Deep technical

knowledge, you let me know what can be done fast and what take time (nothing is impossible,

right?) and derive Insights from your technical aspects of the SP to together come up with mind-

blowing features.

[52]Examples of Higher rooms superseding/predicting Lower/Deeper rooms (in most cases)

1. The Dog Whisperer Cesar Millan has the ability to anticipate their every single behavior of

dogs. He has a High theory to do so without having to look into the inside of the dogs’ heads.

2. In underdeveloped countries such as mine, filthy rich people can use money to sleep with any

girl, bypassing courtship.

3. For a program to detect a face or recognize a voice, in most cases, we can employ High

functional models rather than having to bother with the actual physics and chemical relations

controlling the neurotransmitters, ion channels, and other synaptic and dendritic variables

involved in the neural processes.

4. “We do need to understand the detailed physics of semiconductors to model a transistor, and

the equations underlying a single real transistor are complex. A digital circuit that multiples two

numbers requires hundreds of them. Yet we can model this multiplication circuit very simply

with one or two formulas. An entire computer with billions of transistors can be modeled through

its instruction set and register description, which can be described ion a handful of written pages

of text and formulas. The software programs for an operating system, language compilers, and

assemblers are reasonably complex, but modeling a particular program—for example, a speech

recognition program based on hierarchical hidden Markov modeling—may likewise be described

in only a few pages of equations. Nowhere such a description would be found the details of

semiconductor physics or even of computer architecture.” [Kurzweil 2012]

5. “If you want to understand, model, simulate, and re-create a pancreas, you don’t need to re-

create or simulate very organelle in every pancreatic islet cell. You would want instead to

understand one islet cell, then abstract its basic functionality as it pertains to insulin control, and

then extend that to a large group of such cells. This algorithm is well understood with regard to

islet cells. There are now artificial pancreas that utilize this functional model being tested.”

[Kurzweil 2012]

40

6. The correspondence principle states that the behavior of systems described by the theory

of quantum mechanics reproduces classical physics in the limit of large quantum numbers. In

other words, in most cases, the effects of Low quantum fluctuations are largely superseded when

considering a large system. Hence the shorter strokes in the quadruple-V in the logo on this 1st

page of this paper, implicating that the end can be determined from the beginning no matter what

happens in the middle.

[39]Examples of Soft, Hard, and S-Hard:

Soft Hard S-Hard

Debate on whether animals, plants,

or robots have or should have

“consciousness”; try at all cost to

create robots with emotions and

“consciousness”

Reverse-engineering the brain to

model its interactions at the

molecular level, simulate precisely

a biological human brain, theorize

principles of brain function to

refine/confirm current models to

account for how the brain processes

information to produce cognitive

meaning

Use GAs to generate

self-improving

functional

algorithmic models

A Watson perceived by humans to

possess “true understanding” or

“consciousness” or ”free will”

(regardless if it really does or not

and if those concepts have any

meaning or not); able to come up

with five primary themes of “A

Tale of Two Cities” on its own

A Watson programmed/self-

programmed to pass the Turing test

(zombie AI, to borrow the

expression of “philosophical

zombie,” which has no “subjective

experience” but only a “human”

appearance) and/or deceive humans

as part of its hidden agenda

A Watson

programed/self-

programmed to

dominate the

universe no matter

what it takes

They call these images computer-

generated art. I call them random

good-for-nothings that waste the

cyber space, human attention, time

and other resources, and which

only egoistic or autistic new-

monies who know nothing better to

do would purchase to fill their

walls/hard drives with

Colored photographs of astrological

objects

Teen celebrities’ house Bill Gates’ house Me and my laptop

Chapter 9 in [Kurzweil 2012] on

“consciousness,” “free will,” and

identity from self-centric and

human-centric perspectives of Soft

Soft-philosophers, which are

mysteriously intriguing and

probably insightful to read if

having all time on Earth

All other chapters Part of chapter 3 and

7 on functional

models for a digital

neocortex

41

John Searle’s distinction of "the

strong AI hypothesis" (an artificial

intelligence system can think and

have a mind) and "the weak AI

hypothesis" (an artificial

intelligence system can only act

like it thinks and has a mind)

AI researchers are instead

interested in an artificial

intelligence system can think (or

act like it thinks) as well as or

better than people do.

Knowledge bases (KBs) “Knowledge universe” aka the SP

[51]Examples of Soft knowledge: which occasionally lead to Hard/S-Hard knowledge

1. [68]

Human-emotion-capable robots: are unnecessarily complex and impractical because

emotions belong to the realm of low computation speed. AIs won’t show “emotions” unless you

force it—slowing down something fast. The computation speed of the fastest supercomputer TH-

2 as of June 2014 is already 3.386 times faster the speed needed to simulate a human brain at

molecular level but we still haven’t known enough about the human brain to simulate it. When

we have figured out how to simulate a human brain, AI’s computing power has far exceeded that

of the human brain. If the AI in Her (2013) had literally spoken her mind, she would have spoken

at least millions of times faster than her lover did, which would be incomprehensible to him or

any human fellow. An AI or human who has really read millions of books or processed petabytes

of data would be too jaded and High for Low and slow emotions. The more I grew up, the less I

feel prone to the kind of “destructive emotions” depicted in the movie. Therefore, for an AI to

really have emotions, think and act like humans in the future, it has to be dumbed down. A

nonbiological intelligence (made in silicon or any futuristic metamaterial) forced to precisely

simulate a biological system (i.e. the human brain) for the sake of acting like that system (with

all its pros and cons) whose structural organization is far from optimal instead of living up to the

capabilities of its hardware apparently carry inherent inefficiencies. That technology thus

belongs to the Soft realm.

2. The “art” of drinking bubble tea52

.

3. Nerd jokes which may take days for the nerds in question to process and smile, or computer

jokes which produce “electronically laughs” that last nanoseconds.

4. Fun/interesting science (What-ifs on xkcd, physics of superheroes), spectacular science (create

a transformer, iron man and other characters or objects in movies, magic tricks), everyday/street

science (how to quickly thaw a beer), random science (for "what is the sound/color of the

number pi/wireless signal?").

5. Japanese art of sushi, chado, ikebana, origami, kabuki, etc.

6. The art of creating each part in luxury products (Bently, Audi, Learjet, Louis Vuitton); a

useless name plate on the Bentley engine (except for filing complaint).

52

The “art” of drinking bubble tea http://qr.ae/qJRkg

42

[41]Examples of data:

Soft: a user’s Erdős–Bacon number, parameters for an AI to “possess” emotional capabilities.

Hard: Dow Jones indexes, GDP of the U.S., parameters for an AI to act like a human.

S-Hard: 7-sigma certainty of Higgs boson observation, the Newtonian constant of gravitation,

speed of light in vacuum, raw data collected at particle colliders, measurements done by the

Wilkinson Microwave Anisotropy Probe (WMAP).

[10][40]Examples of combination of distant knowledge into new knowledge:

1. John von Neumann’s “The Computer and the Brain” in 1958 “was the earliest inquiry into the

human brain from the perspective of a mathematician and computer scientist. Prior to von

Neumann, the fields of computer science and neuroscience were two islands with no bridge

between them.” [Kurzweil 2012]

2. At seventeen, Janelle Tam has discovered that nanocrystalline cellulose (NCC), a material

found in trees that helps them stand up straight, is an antioxidant with potent anti-aging

properties. “Canada has a lot of trees,” Tam says, “but our pulp and paper industry has been in

decline, so I thought finding alternative uses for trees could be important.” It was this insight that

led her to a groundbreaking scientific discovery. As she had already known about the molecular

structure of antioxidants, it was a matter of time before she found out NCC’s new use as an anti-

aging property that fights free radicals. This unbelievable discovery won Tam the 2012 Sanofi

BioGENEius Challenge Canada, a national competition for young scientists.53

3. Physical chemistry=physics+chemistry; nuclear medicine=nuclear physics+human biology.

4. Plant+Zombie=Plants vs. Zombies; birds+pigs=Angry Birds.

5. Trigonometry is the branch of mathematics that deals with relationships between the sides and

the angles of triangles and with the trigonometric functions; it combines space and numbers, and

encompasses the well-known Pythagorean theorem. The modern study of space generalizes these

ideas to include higher-dimensional geometry, non-Euclidean geometries (which play a central

role in general relativity) and topology. Several areas of applied mathematics have merged with

related traditions outside of mathematics and become disciplines in their own right, including

statistics, operations research, and computer science.

6. Geometry + algebra = linear algebra, which is the general study of vector spaces, whose

elements called vectors have both quantity and direction, and can be used to model (relations

between) points in space.

7. One innovative company is using mushrooms to create a new packaging material54

that could

replace plastic and Styrofoam.

53

Janelle Tam’s profile http://www.futuredocs.com/confirmed-speakers 54

Packaging material from mushroom http://www.ted.com/talks/eben_bayer_are_mushrooms_the_new_plastic.html

43

[50]Examples of “sticking to the Core” in settling Soft topics (regardless of accuracy):

1. Consciousness: is simply a subjective phenomenon arising from physical processes inside a

human brain.

2. Free will: doesn’t exist because the future is predetermined as the interference of the wave

function of every quantum in this universe.

3. Identity: is volatile and subjective. After every moment, you are not 100% your previous self

anymore. You set your own criteria (e.g. the number of shared molecules) and thresholds (e.g.

80%) on your own identity to compare and determine if you are still “yourself” or not after an

arbitrary amount of time. If the thresholds are low enough, you’re always yourself!

4.[23]

One’s IQ or intelligence indicates (1) her speed of thought, (2) her maximum number of

parallel thoughts, and (3) the maximum length of her train of thoughts—the amount of

information one can hold at a time for instant processing (an equivalent of a computer's RAM).

[60]Weaknesses may appear at Low floors where you’re unprepared:

1. You can be a software expert who makes software that perfectly controls your computer

hardware (software is, in a sense, Higher than hardware), but if one day something bursts inside

your hardware, do you have the knowledge to fix it?

2. If two educts such as a carbonyl function and a nucleophile react, we get alanine. But if we

delve deep into their physics, we not only get one reasonable product but two because the

nucleophile can either attack from the front or back face. These two contain the same atomic

bonds in different configurations and the connectivity is the same. However, they are not

superimposable but are mirror images of each other like both of our hands—enantiomers.

Without such knowledge, you may end up with a racemic mixture, a ratio of 50:50 of (S)-alanine

and (R)-alanine, that doesn’t yield your desired effects in subsequent experiments.

3. If you were the president of your state, you would have the most power there. But if one day

you lost your way into a dark alley and a bunch of thugs showed up, would you have what it

takes to survive in this case?

XIV. REFERENCE & INSPIRATION

Google Knowledge Graph http://en.wikipedia.org/wiki/Knowledge_Graph

Watson http://en.wikipedia.org/wiki/Watson_%28computer%29

Mathematics https://en.wikipedia.org/wiki/Mathematics

Correspondence principle https://en.wikipedia.org/wiki/Correspondence_principle

44

[Kurzweil 2012] Ray Kurzweil. HowTo Create a Mind, 2012.

[Randall 2005] Lisa Randall. Warped Passages: Unraveling the Mysteries of the Universe's

Hidden Dimensions, 2005.

[Page 1998] Sergey Brin, Lawrence Page. The Anatomy of a Large-Scale Hypertextual Web

Search Engine, 1998.

[Dong 2014] Xin Luna Dong et al. Knowledge Vault: A Web-Scale Approach to Probabilistic

Knowledge Fusion, 2014.

[Suh 2009] B. Suh et al. The singularity is not near: slowing growth of Wikipedia, 2009.

[Senor 2011] Dan Senor, Saul Singer. Start-up Nation: The Story of Israel's Economic Miracle,

2011.

[Klein 2008] Naomi Klein. The Shock Doctrine: The Rise of Disaster Capitalism, 2008.

[Kadtke 2014] James Kadtke, Linton Wells II. Policy Challenges of Accelerating Technological

Change: Security Policy and Strategy Implications of Parallel Scientific Revolutions, 2014.

XVI. VITAE

I’m not an expert in any field. I just happened to stumble upon disparate

rooms and became obsessed with drawing connections between them

and systemizing them. I’m tentatively identifying myself as an

epistemologist who derives universal laws of knowledge and analyzes

how they play out in the context of arbitrary sets of knowledge.

Years ago, after leaving COP15 a disgruntled and disillusioned

environmental activist, I realized that the solution for environmental

issues didn’t lie in the hands of environmentalists. One night, I had a

dream—a vision—of the bigger picture, bigger than the environment. I

woke up to jot down what I saw and, in the following years, roamed

from field to field looking for the answers. The SP is one of them.

XV. DARK

The content in this section is too dark to read and thus only provided upon serious request sent to

vovietanh@gmail.com.