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Physics : HyperSpace

HyperSpace can be defined in the following manner:

Physical

d1 : Root +1 : Line : Distance : Metre : Unology : Mono

d2 : Root +2 : Area : Intensity : Candela : Biology : Digo

d3 : Root +3 : Cube : Molarity : Mole : Triology : Numro

d4 : Root +4 : HyperCube : Mass : Kilogram : Quadology : Letro

t1 : Root +5 : Circle : Time : Second : Pentology : Chrono

t2 : Root +6 : Ellipse : Temperature : Celcius : Hexology : Audio

t3 : Root +7 : Sphere : Current : Ampere : Heptology : Video

t4 : Root +8 : HyperSphere : Gravity : “Creatre”? : Octology : Neuro


Table 1.  SI base units


SI base unit


Base quantity Name Symbol
length meter m
mass kilogram kg
time second s
electric current ampere A
thermodynamic temperature kelvin K
amount of substance mole mol
luminous intensity candela cd

Cal

Root 0 is the Hypotenuse of a Point

Logical

Root -1 is the Hypotenuse of a AntiLine
Root -2 is the Hypotenuse of a AntiSquare
Root -3 is the Hypotenuse of a AntiCube
Root -4 is the Hypotenuse of a AntiHyperCube
Root -5 is the Hypotenuse of a AntiCircle
Root -6 is the Hypotenuse of a AntiEllipse
Root -7 is the Hypotenuse of a AntiSphere
Root -8 is the Hypotenuse of a AntiHyperSphere

In any Space all these HyperSpaces exist at the same time.

So, You Think Science has a Monopoly on Knowledge?

Toaism

Hinduism

Buddhism

Islamism

Christism

Judaism

Eight Days

E. F. Codd? Sorry, No Relation

I have been studying relational databases for 30 years. Relational technology is a compromise between a single table flat database and a two table associational database. I have also studied the math. It turns out that linear algebra upon which the whole relational shooting match is based doesn’t even meet the criteria to be called an algebra. In tensor analysis any serious mathematician doesn’t use matrices because they are useless after a small dimensional threshold. Actuarial tables? Use the damned equation, bonehead.

Let’s put it this way. You can denormalize until you have a single table that comprises the entire database or normalize until you have two tables: a three column subject-verb-object table that describes the column index (subject), the row index (object) and the intersection index (verb) and a two column index-value (entity) table. Or you can you can have the intermediate mess of tables we call a relational database.

I no longer give a damn what any relational technologist or technician says. The only reason relational databases exist is because the hard disks were too damned small and E. F. Codd and Chris Date were too enamored with their own mental masturbation to normalize their damned structure. Oracle, MySQL and the rest are a bunch of frauds and they don’t know it or they won’t admit it.

White Hex Corporation is declaring Peace by stopping the War called Relational Database Technology.

Constitution : White Hex Corporation

Constitution

White Hex Corporate Freedoms

1. Freedom of Creation

2. Freedom of Vidation

3. Freedom of Audation

4. Freedom of Nodation

5. Freedom of Vocation

6. Freedom of Legation

7. Freedom of Armation

8. Freedom of Matation

White Hex Corporate members can extend these Freedoms

White Hex Corporate members cannot constrain these Freedoms

Effective 2010-0101

Grant Morgan Czerepak

Chief Executive Officer

White Hex Corporation

易經 : Yì Jīng : Change Book

White Hex Corporation is Changing

易經

Yì Jīng

Change Book


Introducing


易經面經

Yì Jīng Miàn Jīng

“Change Book Face Book”

A Facebook Gift App

开中国: Open China

White Hex Corporation fully supports Google

regarding Freedom of Speech in China.

Chinese People’s Republic Constitution

Article 35: Freedom of Speech, Press, Assembly

Citizens of the People’s Republic of China enjoy:

Freedom of Speech

Freedom of Press

Freedom of Assembly

Freedom of Association

Freedom of Procession

Freedom of Demonstration

http://www.usconstitution.net/china.html

Google China Policy: http://tinyurl.com/yhfgo9k

China attacks Google: http://tinyurl.com/yhzmuo6

White House backs Google: http://tinyurl.com/ycundep

White Hex Corporation Policy
White Hex Corporation will work to create an environment world wide for:

Freedom of Religion

Freedom of Expression

Freedom of Association

Freedom of Location

Unicode: Humanity’s Character Set

I have been putting in significant time absorbing the entire contents  of this book.

Unicode is a computing industry standard allowing computers to consistently represent and manipulate text expressed in most of the world’s writing systems. Developed in tandem with the Universal Character Set standard and published in book form as The Unicode Standard, the latest version of Unicode consists of a repertoire of more than 107,000 characters covering 90 scripts, a set of code charts for visual reference, an encoding methodology and set of standard character encodings, an enumeration of character properties such as upper and lower case, a set of reference data computer files, and a number of related items, such as character properties, rules for normalization, decomposition, collation, rendering, and bidirectional display order (for the correct display of text containing both right-to-left scripts, such as Arabic or Hebrew, and left-to-right scripts).[1]

The Unicode Consortium, the nonprofit organization that coordinates Unicode’s development, has the ambitious goal of eventually replacing existing character encoding schemes with Unicode and its standard Unicode Transformation Format (UTF) schemes, as many of the existing schemes are limited in size and scope and are incompatible with multilingual environments.

Unicode’s success at unifying character sets has led to its widespread and predominant use in the internationalization and localization of computer software. The standard has been implemented in many recent technologies, including XML, the Java programming language, the Microsoft .NET Framework, and modern operating systems.

Unicode can be implemented by different character encodings. The most commonly used encodings are UTF-8 (which uses 1 byte for all ASCII characters, which have the same code values as in the standard ASCII encoding, and up to 4 bytes for other characters), the now-obsolete UCS-2 (which uses 2 bytes for all characters, but does not include every character in the Unicode standard), and UTF-16 (which extends UCS-2, using 4 bytes to encode characters missing from UCS-2).

The Unicode Consortium: http://unicode.org/

Kai: White Hex Open Source Project

In the beginning was the priest. Writing materials were produced in limited quantities. Education was monopolized. Scription was a laborious task and difficult to correct with the materials used. Text made filing easy.  Thus you had the Flat database model.

Then came the scribe. Writing materials increased in availability. Education became institutionalized. Scription and transcription were performed by trained personnel who recorded the dictate of untrained personnel in an academic tongue.  Libraries made indexing easy.  Entire scriptoriums were dedicated to the process of document production. Thus you had the Hierarchical database model.

Then came the writer. Writing materials were mass produced. Education became publicized. Individuals wrote their own documents in their own tongue. The printing press guaranteed mass distribution.  Formatted printing made tabulation easy.  Thus you had the Relational database model.

Then came the layperson. Publishing became universally available via the internet.  Education became personalized.  Networks made linking easy.   Thus you had the Associative Model of Data conceived by Simon Williams.

sentences3.jpg

Simon has developed an Associational Database Management System (ADBMS) called Sentences. It foregoes the use of tables and inferred relationships for the use of single attribute entities and explicit relationships. The schema is intrinsic to the database making the business rules immediately available to anyone who accesses it. Finally, it is internet ready with the capability to be distributed across servers. It is a simple, elegant concept well executed, however there are still some hurdles.

The main hurdle is acceptance. Simon has met strong resistance from relational model advocates. He currently has a website offering the Sentences Enterprise Edition for free to anyone who wants it without technical support, but I do not think that is the answer. I believe that the potential of the Associative Model of Data is not fully realized in the Sentences proprietary implementation. If Sentences is to become the industry standard database for the internet, Simon Williams will have to open up Sentences to global collaboration as an open source project. Only then will the Associative Model reach the tipping point that puts it ahead of the relational model as the database architecture of choice for the lay internet user.

Simon needs Java Programmers for development and support of Sentences Open Source and Mathematicians to develop Associational Calculus.

Links:

I highly recommend going to lazysoft.com and downloading the Sentences Personal and Enterprise Edition to get a feel for this new architecture.  Downloading and intalling the latest Java runtime environment and Sentences can be done in roughly ten minutes.  A populated sample database is ready for exploration.

White Hex Corporation plans to use Sentences as part of its multi-media technology tool set.

Simon Williams, the creator of the Associative Model of Data, its architecture and the Sentences Associative Database Mangement System, had a discussion with me the other day. He told me that to make Sentences an Open Source project, he needs two things. First, he needs a Lead Java Developer to guide the Sentences open source project as Sentences is completely Java based. Second, he needs to get the user group for Sentences to reach the tipping point, which means developing Sentences databases and applications. I’ve used the relational data model for twenty years and the associative model is the next logical step in database architecture. If you want to advance internet database technology by helping this architecture and this product move into the mainstream, here’s your chance. Simon can be reached by email: simon.williams at lazysoft.com

The Infinite Czerepak Regression

The relational model is said to be based on Cartesian mathematics.  Descartes greatest contribution was a Cartesian geometry which was the creation of a coordinate system for Euclidean geometry and geometry in general.  Whatever database you use, it has a coordinate system which gives it its structure.  Even a single bit is a structure all by itself.  Cartesian geometry took Euclidean geometry out of synthesis based on theorems and logic and moved it into coordinates based on analysis and algebra.  We are dealing with linear analysis and linear algebra when we are talking about the relational model and it forms the foundation for calculus and relational calculus which lead to  E. F. Codd’s inventing the relational model for database management, the theoretical basis for relational databases.

The truth about a relational database is conceptually it is only one table.  Only one.  Any relational database could be converted into a single spreadsheet.  So, why all the tables?

First, every database can be separated into the logical structure and the physical content.  The logical structure is called the schema and the physical content is called the data.  Logical and physical separation optimizes the administration, management and employment of the database.  As soon as you separate the logical and physical tables you eliminate an enormous amount of duplication in the system as well as all the effort required to maintain the correct values among all the duplicates.  This optimization is the first normalization of the database.

Now, Codd came up with what are known as The Twelve Rules which I have copied from Wikipedia:

Rule 0: The system must qualify as relational, as a database, and as a management system.

For a system to qualify as a relational database management system (RDBMS), that system must use its relational facilities (exclusively) to manage the database.

Rule 1: The information rule:

All information in the database is to be represented in one and only one way, namely by values in column positions within rows of tables.

Rule 2: The guaranteed access rule:

All data must be accessible. This rule is essentially a restatement of the fundamental requirement for primary keys. It says that every individual scalar value in the database must be logically addressable by specifying the name of the containing table, the name of the containing column and the primary key value of the containing row.

Rule 3: Systematic treatment of null values:

The DBMS must allow each field to remain null (or empty). Specifically, it must support a representation of “missing information and inapplicable information” that is systematic, distinct from all regular values (for example, “distinct from zero or any other number”, in the case of numeric values), and independent of data type. It is also implied that such representations must be manipulated by the DBMS in a systematic way.

Rule 4: Active online catalog based on the relational model:

The system must support an online, inline, relational catalog that is accessible to authorized users by means of their regular query language. That is, users must be able to access the database’s structure (catalog) using the same query language that they use to access the database’s data.

Rule 5: The comprehensive data sublanguage rule:

The system must support at least one relational language that
  1. Has a linear syntax
  2. Can be used both interactively and within application programs,
  3. Supports data definition operations (including view definitions), data manipulation operations (update as well as retrieval), security and integrity constraints, and transaction management operations (begin, commit, and rollback).

Rule 6: The view updating rule:

All views that are theoretically updatable must be updatable by the system.

Rule 7: High-level insert, update, and delete:

The system must support set-at-a-time insert, update, and delete operators. This means that data can be retrieved from a relational database in sets constructed of data from multiple rows and/or multiple tables. This rule states that insert, update, and delete operations should be supported for any retrievable set rather than just for a single row in a single table.

Rule 8: Physical data independence:

Changes to the physical level (how the data is stored, whether in arrays or linked lists etc.) must not require a change to an application based on the structure.

Rule 9: Logical data independence:

Changes to the logical level (tables, columns, rows, and so on) must not require a change to an application based on the structure. Logical data independence is more difficult to achieve than physical data independence.

Rule 10: Integrity independence:

Integrity constraints must be specified separately from application programs and stored in the catalog. It must be possible to change such constraints as and when appropriate without unnecessarily affecting existing applications.

Rule 11: Distribution independence:

The distribution of portions of the database to various locations should be invisible to users of the database. Existing applications should continue to operate successfully :
  1. when a distributed version of the DBMS is first introduced; and
  2. when existing distributed data are redistributed around the system.

Rule 12: The nonsubversion rule:

If the system provides a low-level (record-at-a-time) interface, then that interface cannot be used to subvert the system, for example, bypassing a relational security or integrity constraint.

Now there is another way to look at Codd’s Twelve Rules that is not often discussed directly and that is the OSI Model. The OSI Model is used to describe network layers and it is perfectly logical to regard a relational database as a dynamic lattice network composed of conceptual layers.

The Open System Interconnection Reference Model (OSI Reference Model or OSI Model) is an abstract description for layered communications and computer network protocol design. It was developed as part of the Open Systems Interconnection (OSI) initiative. In its most basic form, it divides network architecture into seven layers which, from top to bottom, are the Application, Presentation, Session, Transport, Network, Data-Link, and Physical Layers. It is therefore often referred to as the OSI Seven Layer Model.

Application
(Layer 7)
This layer supports application and end-user processes. Communication partners are identified, quality of service is identified, user authentication and privacy are considered, and any constraints on data syntax are identified. Everything at this layer is application-specific. This layer provides application services for file transfers, e-mail, and other network software services. Telnet and FTP are applications that exist entirely in the application level. Tiered application architectures are part of this layer.
Presentation
(Layer 6)
This layer provides independence from differences in data representation (e.g., encryption) by translating from application to network format, and vice versa. The presentation layer works to transform data into the form that the application layer can accept. This layer formats and encrypts data to be sent across a network, providing freedom from compatibility problems. It is sometimes called the syntax layer.
Session
(Layer 5)
This layer establishes, manages and terminates connections between applications. The session layer sets up, coordinates, and terminates conversations, exchanges, and dialogues between the applications at each end. It deals with session and connection coordination.
Transport
(Layer 4)
This layer provides transparent transfer of data between end systems, or hosts, and is responsible for end-to-end error recovery and flow control. It ensures complete data transfer.
Network
(Layer 3)
This layer provides switching and routing technologies, creating logical paths, known as virtual circuits, for transmitting data from node to node. Routing and forwarding are functions of this layer, as well as addressing, internetworking, error handling, congestion control and packet sequencing.
Data Link
(Layer 2)
At this layer, data packets are encoded and decoded into bits. It furnishes transmission protocol knowledge and management and handles errors in the physical layer, flow control and frame synchronization. The data link layer is divided into two sub layers: The Media Access Control (MAC) layer and the Logical Link Control (LLC) layer. The MAC sub layer controls how a computer on the network gains access to the data and permission to transmit it. The LLC layer controls frame synchronization, flow control and error checking.
Physical
(Layer 1)
This layer conveys the bit stream – electrical impulse, light or radio signal — through the network at the electrical and mechanical level. It provides the hardware means of sending and receiving data on a carrier, including defining cables, cards and physical aspects. Fast Ethernet, RS232, and ATM are protocols with physical layer components.

A layer is a collection of conceptually similar functions that provide services to the layer above it and receives service from the layer below it. On each layer an instance provides services to the instances at the layer above and requests service from the layer below. For example, a layer that provides error-free communications across a network provides the path needed by applications above it, while it calls the next lower layer to send and receive packets that make up the contents of the path. Conceptually two instances at one layer are connected by a horizontal protocol connection on that layer.

If we look at the Relational Model and Codd’s rules in the context of the OSI Model we can think of the rules in the following way as a hybrid I call the Czerepak Rules:

The Czerepak Rules

  • Why Layer: Protect Application Input definition from Catalog View definition.
  • See Layer: Protect Catalog View definition from Catalog User definition
  • Use Layer: Protect Catalog User definition from Catalog Language definition.
  • Act Layer: Protect Catalog Language definition from Catalog Column definition
  • Col Layer: Protect Catalog Column definition from Catalog Row definition
  • Row Layer: Protect Catalog Row Definition from Catalog Constraint definition
  • Yes Layer: Protect Catalog Constraint definition from Catalog Input definition
  • Why Layer: Protect Catalog Input definition from Data View definition.
  • See Layer: Protect Data View definition from Data User definition
  • Use Layer: Protect Data User definition from Data Language  definition
  • Act Layer: Protect Data Language definition from Data Column definition
  • Col Layer: Protect Data Column definition from Data Row definition
  • Row Layer: Protect Data Row Definition from Data Constraint definition
  • Yes Layer: Protect Data Constraint definition from Data Input definition
  • Why Layer: Application Layer: Protect Data Input definition from Access Method View Definition

If you look carefully at the list you will see that it extends beyond the top and beyond the bottom in an infinite regression.

“Turtles all the way down,” or “The Infinite Turtle Theory,” refers to the infinite regression problem in cosmology posed by the Unmoved mover paradox. The phrase was popularized by Stephen Hawking in 1988. The “turtle” metaphor in the anecdote represents a popular notion of a “primitive cosmological myth“, viz. the flat earth supported on the back of a World Turtle.

It is interesting to note that “czerepak” is a Yiddish word which means “turtle”.

A comparable metaphor describing the circular cause and consequence for the same problem is the “chicken and egg problem“. Another metaphor addressing the problem of infinite regression, albeit not in a cosmological context, is Quis custodiet ipsos custodes? The same problem in epistemology is known as the Münchhausen Trilemma.

Nodular, Linear, Tabular, Netular, Tensular, Quantular, Qualular

Computing has undergone an Evolution

Web 0.0: Nodular Computing

When there is no network, you have either a server or a PC on which either a standard program (e.g., an accounting package, image editor, or word processor) or a custom program (e.g., company-specific inventory management, actuarial table calculation, mortgage calculator) takes input on that computer, does some calculations, stores intermediate data, and produces output.

Organizations and individuals liked this configuration for doing local things that could be confined to one location. It opened up the prepackaged software industry, because there were many applications that were general enough that you could sell to many locations. The ability to choose locally which software to run (either on a managed machine or a personal machine) was a great source of empowerment and led to a surge in the purchase of first managed corporate machines in the 1960’s and 1970’s, and then the PCs in the 1980’s. Every system could be different.

Nodular Computer: Mainframe: Priesthoods Operate
Nodular Network: ARPANET: Priesthoods Connect
Nodular Data: Variable: Noun: Priesthoods Query
Nodular Language: Variable PL: Assembler: Priesthoods Manipulate
Nodular Communication: Variable Packet: MULTIVALUABLEML: Priesthoods Communicate
Nodular Schedule: Multi-Stating: DedicatedOn
Nodular Objective: Active

Web 1.0: Linear Computing

Transaction processing systems have a single server with custom software doing computation and data storage. Each client machine is usually a standard “smart” terminal or a personal computer running a standard program acting as one. The input and output occurs on the PC. The PC has no storage and is only connected directly to the single server through a dedicated communications system. Part of the input sometimes comes from other sources.

This configuration let organizations do applications that involved people at diverse locations involved with a single database. It was best for applications that were worth dedicating the communications system as well as the dedicated client machines. Since the client machines were standard, their cost and maintenance could be commodities. The applications were often mission-critical to the company employing them. Interacting with computers started to be integral to the operation of an enterprise, for example at banks or airlines.

Client-server systems have servers similar to the transaction processing systems, with computation, data storage, and maybe some input, and run custom software. The PC is connected by a communications system (a LAN or WAN) that is usable for more than one application. The PCs run custom software that does computation as well as input and output.

As corporations started learning the value of using computers as part of their operation, client-server configurations let them take advantage of the power of the PCs on people’s desks and the sharing afforded by the LAN. The standalone applications showed them the value of user-friendly, usable user interfaces. By running custom applications communicating with the servers they could make more efficient applications. The LAN let them share expensive hardware like large disks and expensive printers. Because they used standard equipment on the client side, they could take advantage of commodity pricing.

Linear Computer: Minicomputer: Scribes Operate
Linear Network: Ethernet: Scribes Connect
Linear Data: String dbms: Verb: Scribes Query
Linear Language: String PL: 3GL: Scribes Manipulate
Linear Communication: String Packet: DIMENSIONALML: Scribes Communicate
Linear Schedule: Multi-Tasking: BatchOn
Linear Objective: Reactive

Web 2.0: Tabular Computing

Web applications is a term for custom software on web servers.This has the same characteristics as the web sites, except that there is a much higher cost to construct the web sites and much more of the data comes from the PCs connecting to the web application.

Rather than hooking sales people to transaction terminals that were connected to a purchasing system you could directly hook purchasers to the purchasing system. Cloud Computing is similar to transaction processing, except that the client machines are usually shared with many applications from many servers. This would let them have those applications managed centrally by specialists, and let them share the application beyond the confines of a single LAN. It would also enable business models where the use of the server could be charged for like a service, bringing in recurring revenue without doing additional development.

Tabular Computer: Microcomputer: Educated Operate
Tabular Network: Internet: Educated Connect
Tabular Data: Relational dbms: Noun Set: Educated Query
Tabular Language: Relational PL: SQL: Educated Manipulate
Tabular Communication: Relation Packet: MULTIDIMENSIONALML: Educated Communicate
Tabular Schedule: Multi-Threading: DemandOn
Tabular Objective: Interactive

Web 3.0: Netular Computing http://tinyurl.com/yay9dwu

All of the preceding systems use single main systems (either a standalone PC or a server) to do the main computation and store the main data. The only change is where the I/O is done. The view of the world is always through this shared main data or computation. With the growth of the Internet because of email and the web, the communications system to connect dispersed, independent PCs together became available. PCs also became more powerful and data storage costs dropped so much that most PCs had huge capacities. New configurations came about that didn’t depend on the server so much. These configurations became known as Peer-to-Peer.

A distinguishing characteristic between various forms of P2P is the role of the other PCs to a given user. In the standalone or central server world, there is one computer that is “special”. In the P2P world, there are configurations where the mass of other PCs serve as a “super-server” for the purposes of redundancy, cost reduction, parallel processing, privacy, or whatever. Which person, if any, uses that PC doesn’t matter. At most, the anonymous properties of the data make a difference, or which other computers it is connected to. I call these “anonymous distributed serving” configurations. Other configurations are for connecting particular PCs because of the individuals using, or location of, each PC. I call these “person to person” configurations.

Netular Computer: Scale-free CPUs: Laypeople Operate
Netular Network: Wireless Network: Laypeople Connect
Netular Data: Associational DBMS: Verb Set: Laypeople Query
Netular Language: Assocational PL: Iconic Language: Laypeople Manipulate
Netular Communication: Association Packet: VECTORALML: Laypeople Communicate
Netular Schedule: Multi-Weaving: PresentOn
Netular Objective: Proactive

And what comes next?

01.06.08ebblog

Web 4.0: Tensular Computing: http://tinyurl.com/yckfw37

Tensors are geometrical entities introduced into mathematics and physics to extend the notion of scalars, (geometric) vectors, and matrices. Many physical quantities are naturally regarded, not as vectors themselves, but as correspondences between one set of vectors and another. An example is the stress, that takes one vector as input and produces another vector as output and so expresses a relationship between the input and output vectors. Tensors were first conceived by Bernhard Riemann and Elwin Bruno Christoffel, and later developed by Tullio Levi-Civita and Gregorio Ricci-Curbastro, in order to formulate the intrinsic differential geometry of a manifold in the form of the Riemann curvature tensor.

Because they express a relationship between vectors, tensors themselves are independent of a particular choice of coordinate system. It is possible to represent a tensor by examining what it does to a coordinate basis or frame of reference; the resulting quantity is then an organized multi-dimensional array of numerical values. The coordinate-independence of a tensor then takes the form of a “covariant” transformation law that relates the array computed in one coordinate system to that computed in another one. The order (or degree) of a tensor is the dimensionality of the array needed to represent it. Thus a scalar is a zeroth-order tensor: its magnitude is its sole component, so it can be represented as a 0-dimensional array. A vector is a first-order tensor, being representable in coordinates as a 1-dimensional array of components. A matrix is a second-order tensor, being representable as a 2-dimensional array. And so on: an order-k tensor can be represented as a k-dimensional array of components. The order is the number of numerical indices necessary to specify an individual component of a tensor

Tensular Computer: Multiple CPUs: Sensory Operation
Tensular Network: High Frequency Gravity Wave Network: Sensory Connection
Tensular Data: Vector DBMS: Sentence Set: Sensory Question
Tensular Language: Vector PL: Mathematical Language: Sensory Manipulation
Tensular Communication: Vector Packet: MULTIVECTORALML: Sensory Communcation
Tensular Schedule: Multi-Layering: PastOn
Tensular Objective: Retroactive

Web 5.0: Quantular Computing

A quantum computer is a device for computation that makes direct use of quantum mechanical phenomena, such as superposition and entanglement, to perform operations on data. The basic principle behind quantum computation is that quantum properties can be used to represent data and perform operations on these data. A theoretical model is the quantum Turing machine, also known as the universal quantum computer.

Although quantum computing is still in its infancy, experiments have been carried out in which quantum computational operations were executed on a very small number of qubits (quantum bit). Both practical and theoretical research continues with interest, and many national government and military funding agencies support quantum computing research to develop quantum computers for both civilian and national security purposes, such as cryptanalysis.

If large-scale quantum computers can be built, they will be able to solve certain problems much faster than any of our current classical computers (for example Shor’s algorithm). Quantum computers are different from other computers such as DNA computers and traditional computers based on transistors. Some computing architectures such as optical computers may use classical superposition of electromagnetic waves. Without some specifically quantum mechanical resources such as entanglement, it is conjectured that an exponential advantage over classical computers is not possible. Quantum computers however do not allow one to compute functions that are not theoretically computable by classical computers, i.e. they do not alter the Church–Turing thesis. The gain is only in efficiency.

Quantular Computer: Autonomous CPUs: Computers Operate
Quantular Network: Quantum Entanglement Network: Computers Connect
Quantular Data: Tensor DBMS: Autonomous Computers Query
Quantular Language: Vector PL: Mathematical Language: Computers Manipulate
Quantular Communication: Vector Packet: TENSORALML: Computers Communcate
Quantular Schedule: Multi-Bundling: FutureOn
Quantular Objective: Creative

Web 6.0: Qualular Computing

Consider your visual experience as you stare at a bright turquoise color patch in a paint store. There is something it is like for you subjectively to undergo that experience. What it is like to undergo the experience is very different from what it is like for you to experience a dull brown color patch. This difference is a difference in what is often called “phenomenal character.” The phenomenal character of an experience is what it is like subjectively to undergo the experience. If you are told to focus your attention upon the phenomenal character of your experience, you will find that in doing so you are aware of certain qualities. These qualities — ones that are accessible to you introspectively and that together make up the phenomenal character of the experience are standardly called ‘qualia’.

There are more restricted uses of the term ‘qualia’. Consider a painting of a dalmatian. Viewers of the painting can apprehend not only its content (i.e., its representing a dalmatian) but also the colors, shapes, and spatial relations obtaining among the blobs of paint on the canvas. It has sometimes been supposed that being aware or conscious of a visual experience is like viewing an inner, non-physical picture or sense-datum. So, for example, on this conception, if I see a dalmatian, I am subject to a mental picture-like representation of a dalmatian (a sense-datum), introspection of which reveals to me both its content and its intrinsic, non-representationational features (counterparts to the visual features of the blobs of paint on the canvas). These intrinsic, non-representational features have been taken by advocates of the sense-datum theory to be the sole determinants of what it is like for me to have the experience. In a second, more restricted sense of the term ‘qualia’, then, qualia are intrinsic, consciously accessible, non-representational features of sense-data and other non-physical phenomenal objects that are responsible for their phenomenal character.

There is another established sense of the term ‘qualia’, which is similar to the one just given but which does not demand of qualia advocates that they endorse the sense-datum theory. However sensory experiences are ultimately analyzed — whether, for example, they are taken to involve relations to sensory objects or they are identified with neural events or they are held to be physically irreducible events — many philosophers suppose that they have intrinsic, consciously accessible features that are non-representational and that are solely responsible for their phenomenal character. These features, whatever their ultimate nature, physical or non-physical, are often dubbed ‘qualia’.

In the case of visual experiences, for example, it is frequently supposed that there is a range of visual qualia, where these are taken to be intrinsic features of visual experiences that (a) are accessible to introspection, (b) can vary without any variation in the representational contents of the experiences, (c) are mental counterparts to some directly visible properties of objects (e.g., color), and (d) are the sole determinants of the phenomenal character of the experiences. Philosophers who hold or have held this view include, for example, Nagel (1974), Peacocke (1983) and Block (1990).

Qualular Computer: Unified CPU: Plurality Operates
Qualular Network: Quantum Entanglement Network: Plurality Connects
Qualular Data: Extensor DBMS: Plurality Queries
Qualular Language: Tensor PL: Unified Language: Plurality Manipulates
Qualular Communication: Tensor Packet: MULTITENSORALML: Plurality Communcate
Qualular Schedule: Multi-Versioning: EvolutiOn
Qualular Objective: Procreative

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