July 29

Waves of Intelligence

Quantum computers are the secret KEY to unlocking all encrypted files. Privacy is now an illusion of the past.
DWAVE:  Funded by InQTel (a branch of the CIA that started Google and Facebook). 
Google, NASA, CERN and other companies have been using DWave for a few years already.  
Quantum Computing is the reality of the minority report: precrime. All of your data they have been gathering from your social media accounts and phone apps and every single thing you do online.  All of your data in your file and now finally able to be analyzed and sorted thanks to Quantum Computing.  Now it will be no problem to make more detailed lists of citizens. Those who will rise up and those who will go along with the plans.  Social Engineering just got a lot more interesting. Computers can now predict humans actions before they happen based on their past and present data. This is happening today in China. 
Google has this  technology: to psychologically profile and predict the behavior of  human consumers so  that high-value ads can be delivered to them across  Google’s search engine and content networks as the main stream story line goes. We know from the PRISM program that this will enable Google to funnel psych profile meta-data on internet users to the NSA.

Quantum   computers can be used to search large databases in a  fraction of  the  time that it would take a conventional computer. Other  applications  could include using quantum computers to study quantum  mechanics, or even to design other quantum computers. Teaching machines how to learn and think for themselves.
Machine Learning (Artificial Intelligence) has given us self-driving cars, practical speech recognition, effective web searches and more. All under the guise of convenience. 
Google’s algorithm recognizes that you searched for something a  couple of seconds after searching something else, and it logs and saves this for future users who make a similar typing mistake. As a result, Google ‘learns’ to correct it for you.
In 2013, a D-Wave Two  system was installed at the new Quantum Artificial Intelligence Lab, a  collaboration among Google, NASA and the Universities Space Research  Association (USRA). The lab is housed at the NASA Ames Research Center  in California. In September 2015 the system was upgraded to a 1000+  qubit D-Wave 2X quantum computer. 
Eric Ladizinksy (Founder of Dwave) has told us Dwave first doubled every couple years, then every year, then every six months and now every 3 months! 
Rose’s Law is a relatively new observation that states that the computational power of quantum computers doubles every 12 months, as opposed to the 18 month doubling of Moore’s Law.  
As  D Wave advanced they made hardware upgrades. Also were able to tune the  machine into the frequency of the universe which seems to make it sound like a “heart beat.” 
We are all made up of and affected by frequency- people, planets, solar systems; we  are now connected to an AI machine that scientifically proven, travels/computes in multiple dimensions at once!
“So the enabler for AI is machine learning,” Intel’s Nidhi Chappell,  “AI has become so pervasive in our lives we don’t come to recognize that it’s powering a lot of things. You probably use it dozens of times a day without knowing it.”
3 types of learning:
Reinforcement  learning: This type of  learning concentrates on how an AI ‘agent’   should behave in order to get  the most out of its work. The machine picks an action or a sequence of  actions, and gets a reward. This is used when teaching machines to play  and win games but needs a large number of trials to learn even simple tasks.
Supervised learning: This is when researchers tell the machine what the correct answer is for a particular input. For example, they show it an image of a car and tell it the correct answer is “car.” It is the most common technique for training  neural networks and other machine learning architectures.
Unsupervised learning/predictive learning: Humans and  animals learn, typically, in an unsupervised manner by watching how the world works and by observing  our parents. Basic concepts such as: objects don’t disappear spontaneously and objects that are not supported fall.  Researchers don’t know how to do this with machines at the moment, at least not at the level that humans and animals can.
In 2018:  Google turns over its search engine algorithm to a massive  network of  self-learning machines. Soon thereafter, a voice interface is  added to  Google, achieving the “Star Trek computer” goal that Google  first  outlined in the 1990’s.
Ray  Kurzweil, director of engineering at Google, also claims that the   biological parts of our body will be replaced with mechanical parts and   this could happen as early as 2100. Kurweil made the claims during his  conference speech at the Global Futures 2045 International Congress in   New York at the weekend. His goal is to merge with the machines in order to be immortal.
Kurtzweil also states 2000 and 8000 qubit systems are coming in 2 years and 4 years that will speed up solving nearly all machine learning optimization problems in one second after they are formulated properly for the Dwave system. In a few years, Kurzweil will have the classical computer power of Google’s data centers and quantum computer power that could be beyond  the power of all classical computers to drive his solution of greater than human intelligence: “artificial intelligence”.
Singularity University describes itself as “a global community using exponential technologies to tackle the world’s biggest challenges  is the creation of Ray Kurzweil who is Google’s Director of Engineering.
With the rapid growth of AI technology will inevitably take over our lives.  AI will do our jobs faster and cheaper.  AI will drive our cars safer and more efficiently.  AI will control our bodies frequencies and mental processes.
In the UK, a report  released by thinktank Reform says roughly 250,000 public servants could  lose their jobs to robots over the next 15 years. Meanwhile, other  governments such as those in Hong Kong and Singapore are increasingly  turning to AI to take over various administrative functions.
News  is that AI is even creeping up into freedom of speech and press – Google’s  Digital Journalism Initiative is spearheading an AI software called  JUICE which claims to “help” (CENSOR) reporters write more “accurate and engaging  pieces” meaning what fits the elites agenda of propaganda as we have already seen in internet censorship today.
Microsoft is already cutting its workforce and jobs to “move towards cloud tech.”  Keyword meaning Artificial Intelligence.
AI can be used to address child abduction issues and prevent traffic congestion, according to the Chinese version of Li’s non-binding proposal. Instead of being better humans we will make machines to do it for us.
“In  the future, robotics may be combined with AI, neurology, mechanical  engineering and many other fields to deeply influence our life and  work,” Ma said at a press conference in Beijing on Friday evening.
AI is also receiving a  big push from Facebook and Google as they invest billions of dollars  through OpenAI and DeepMind to democratize the technology – not to  mention countless acquisitions of AI talent. But the corporate activity  merely proves that big-business has plans for AI, whereas AlphaGo  beating Lee Sedol signals the possibility that AI could indeed be more  capable than humans.
You  can consider corporate activity like Facebook, Google, Snapchat, Baidu  as a signal of trust. You can also trust the direction of car companies  like GM, Mercedes-Benz, Uber, and Tesla towards autonomous cars. And you  can trust academics, the White House and other longitudinal thinkers  when they say past academic research, computational power and large  accessible data sets will together create a perfect storm for AI  impacting our lives Asia will be big in AI. If you look at the data trends, there is a tonne of  AI research done in China, Japan, South Korea and Singapore. In fact  there are more cited publications in China than in the United States.
AI is naturally receiving large contributions from Facebook and Google as they invest billions of dollars through OpenAI and DeepMind to democratize the technology – not to  mention countless acquisitions of AI talent. But the corporate activity merely proves that big-business has plans for AI, whereas AlphaGo beating Lee Sedol signals the possibility that AI could indeed be more capable than humans.

An interesting reddit feed

Jordan Novet May 16, 2013 Posted:  
“It’s  been almost two decades since Peter Shor came up with a a breakthrough  algorithm for finding the prime factors of a number with a quantum  computer, sparking great interest in quantum computing. But commercial  adoption has been pretty much nonexistent. On Thursday, though, Google came forward with news that it’s launching a Quantum Artificial  Intelligence Lab that will include a quantum computer, apparently  making it the second company to pay for a quantum computer. The development suggests that quantum computing could finally be taking off.”
Earlier  this year Lockheed Martin shared details of its implementation of a D-Wave Systems quantum computer, which reportedly cost $10 million: The contractor is using the computer to develop new aircraft, radar and  space systems. 
“Following  a recent upgrade, the USC-Lockheed Martin Quantum Computing Center  based at the USC Information Sciences Institutes now the leader in  quantum processing capacity.
With   the upgrade — to 1,098 qubits from 512 — the D-Wave 2X™ processor is   enabling QCC researchers to continue their efforts to close the gap   between academic research in quantum computation and real-world  critical  problems. The  new processor will be used to study how and  whether quantum effects can  speed up the solution of tough  optimization, machine learning and  sampling problems. Machine-learning  algorithms are widely used in  artificial intelligence tasks.”  Read the  entire article here.
Now  Google is taking steps at incorporating more quantum computing into its operations with the Quantum Artificial Intelligence Lab, which will be  located at the NASA Ames Research Center in Moffett Field, Calif.  Researchers from the Universities Space Research Association will be  able to use the machine 20 percent of the time, Forbes reports. That  could lead to lots of interdisciplinary thinking and collaboration.
For Google, though, the goal of the initiative is to make strides in  machine learning, according to a Thursday Google Research blog post. The  best results could trickle down to end users, perhaps in search results  and speech-recognition applications.
Google  has already assembled machine-learning algorithms that involve quantum  elements. The  applications might have arisen after Google’s earlier partnership with  D-Wave, which came to light in a different blog post from Neven in 2009.
Google  has already used machine learning to recognize faces and other things  in photos and videos. New technology Google executives talked about at  the Google I/O developer conference in San Francisco on Wednesday also  appears to use machine learning to stitch together photos and clean them  up.
What  Google has learned so far is the best results come from blending  regular binary computing using ones and zeros with quantum style  computing. Quantum computing accommodates the space between a one and a  zero with quantum bits of information, or qubits. It can express  likelihood as well as take shortcuts by approximating when handling  certain kinds of workloads. Given what Google has observed thus far, it  could decide to build hardware combining quantum and classical computing  capabilities.
In  any case, quantum computing has a long way to go before reaching commercial viability. But  because the organization at the helm of the quantum research is Google and not IBM or Bell Labs, regular people could start seeing much more of the advantages in just a few years’ time, which in turn could drive commercialization.
 
Lets look at some very small points and you can follow the links for more indepth explanations. 
Richard Feynman once famously stated that nobody un-derstands quantum mechanics. 
Extensive  testing and interviews demonstrate that a significant fraction of  advanced undergraduate and beginning graduate students, even after one  or two full years of instruction  in quantum mechanics, still are not proficient at those functional  skills. They often possess deep-rooted mis-conceptions about such  features as the meaning and significance  of stationary states, the  meaning of an expectation value, properties  of wave functions, and quantum dynamics. Even students who  excel at  solving technically difficult questions are often unable to  answer  qualitative versions of the same questions. 
Quantum Mechanics: where the rules of the world you experience don’t apply.
The property of entanglement: where particles can take on related properties if they end up in an equation together. If you separate these particles, they remain entangled with these properties until you observe one of them—then the other particle assumes its corresponding value. (A 1 or a 0) It’s as if the fact that you observed the first particle immediately transmits information to the other particle about how it should look. 
Schrödinger’s equation:  Tiny particles,  such as electrons or photons,  can simultaneously take on states that we  would normally deem mutually exclusive. They can be  in several places  at once, for example, and in  the case of photons  simultaneously  exhibit two kinds of polarization. We  never see this  superposition of  different states in ordinary life  because it somehow  disappears once a system is observed:   when you  measure the location of an electron or the polarization of a   photon,  all but one of the possible alternatives are eliminated and  you  will see  just one. Nobody knows how that happens, but it does
“The prowess of quantum computing comes from the “ghost-angel” state of a quantum system. The uncertainty of the state applied to quantum mechanics is only true for a linear superposition of coherent quantum states, which I term the ghost-angel state.  This state has not been found to exist for macroscopic objects.”  
In March 2000, scientists at Los Alamos National Laboratory announced the development of a 7-qubit quantum computer within a single drop of liquid.   The quantum computer uses nuclear magnetic resonance (NMR) to  manipulate particles in the atomic nuclei of molecules of trans-crotonic  acid, a simple fluid consisting of molecules made up of six hydrogen  and four carbon atoms. The NMR is used to apply electromagnetic pulses,  which force the particles to line up. These particles in positions  parallel or counter to the magnetic field allow the quantum computer to  mimic the information-encoding of bits in digital computers.
Some Quantum Physics:
It is still unclear why the observer of an experiment determines  behavior  of the system and causes it to favor one state over another. When  light is introduced to atoms, it recharges them. You cannot observe the system or measure its properties without  interacting with it. And where there is interaction, there will be modification of properties.
Basic logic of physics is incorrect and the entire underlying structure of  physics is unable to be used in quantum physics because the core logic is entirely different. Not to mention basic physics is mostly lacking because much is based off the work of Albert Einstein who’s theories were based on incorrect assumptions.  By default everything built on this foundation is built on lies. Theories-Assumptions and guesses.
We  have to choose between the two evils. But remember, now scientists  are  increasingly convinced that the basis of our mental processes is created by these notorious quantum effects. So, where the observation ends and reality begins, is up to each of us.
  • Theoretical  physics is a branch of physics which employs  mathematical models and  abstractions of physical objects and systems to  rationalize, explain  and predict natural phenomena. This is in contrast  to experimental  physics, which uses experimental tools to probe these  phenomena.
  • The advancement of science depends in general on the interplay between experimental studies and theory.
  • D-Wave  starts off with a set of noninteracting qubits—a collection of   supercomputing loops kept at their lowest energy state, called the   ground state—and then slowly, or “adiabatically,” transforms this  system  into a set of qubits whose interactions at its ground state  represent  the correct answer for the specific problem 

More Here.  Here.  And Here. 

According  to Forbes, when  the world’s first digital computer was completed in  1946 it opened up  new vast new worlds of possibility. Still, early  computers were only  used for limited applications because they could  only be programmed in  machine code. It took so long to set up problems  that they were only  practical for massive calculations.
John  Backus created the first programming language, FORTRAN, at IBM in 1957.  For the first time, real world problems could  be quickly and  efficiently transformed into machine language, which made  them far more  practical and useful. In the 1960’s, the market for  computers soared.
Like   the first digital computers, quantum computing offers the possibility   of technology millions of times more powerful than current systems, but   the key to its success will be translating real world problems into   quantum language.
Quantum  computers aren’t limited to two states. They encode information as  quantum bits, or qubits. Qubits represent atoms, ions, photons or  electrons and their respective control  devices that are working  together to act as computer memory and a processor. Because a quantum  computer can contain these multiple states at the same time. It has the  potential to be millions of times more  powerful than today’s most  powerful supercomputers.
 
This superposition of qubits is what gives quantum computers their inherent parallelism. According to physicist David Deutsch, this parallelism allows a quantum computer to work on a million computations at once, while your desktop PC works on one.
 
One problem with the idea of quantum computers is that if you try to look at the subatomic particles, you could bump them, and thereby change their value. If you look at a qubit in superposition to determine its value, the qubit will assume the value of either 0 or 1, but not both. To make a practical quantum computer, scientists have to devise ways of making  measurements indirectly to preserve the system’s integrity. Entanglement provides a potential answer. In quantum physics, if you apply an outside force to two atoms, it can cause them to become entangled, and the second atom can take on the properties of the first atom. So if  left  alone, an atom will spin in all directions. The instant it is  disturbed  it chooses one spin, or one value; and at the same time, the  second entangled atom will choose an opposite spin, or value. This allows scientists to know the value of the qubits without actually looking at them.
Dario Borghino October 6, 2015 
In  what is likely a major  breakthrough for quantum computing, researchers  from the University of  New South Wales (UNSW) in Australia have  managed for the first time to  build the fundamental blocks of a quantum  computer in silicon. The  device was created using standard  manufacturing techniques, by modifying  current-generation silicon  transistors, and the technology could scale  up to include thousands,  even millions of entangled quantum bits on a  single chip.
The  real power of this  breakthrough is not in a slightly higher  operational temperature, but in  the fact that these basic building  blocks of quantum computers were  built by doing simple modifications to  current-generation silicon  transistors. The researchers say they have  worked out a way to extend  this technique to a much larger number of  qubits, even numbering in the  thousands of millions, all reported to be  fully entangled.
Patent Notice
Intellectual Property Notices
D-Wave  Systems Inc. (“D-Wave”) has marked various products, and documents  describing various products and services, with a universal resource  locator that resolves to this document.  Notices applicable to D-Wave’s  intellectual property rights associated with D-Wave’s products and  services including the marked products and services are listed below.   The intellectual property rights include: copyright, trade-mark, patent,  and other intellectual property rights.
Copyright:
No  part of any computer software, or associated documentation, included in  D-Wave’s products and services may be reproduced, stored, or  transmitted in any form, or by any means, without the written permission  from D-Wave.
No  part of any D-Wave’s documentation or website may be reproduced,  stored, or transmitted in any form, or by any means, without the written  permission from D-Wave.
Trade-marks:
D-Wave,  D-Wave One, D-Wave Two, D-Wave 2X, Bare Metal, Chimera, D-Wave  Blackbox, D-Wave QSage, D-Wave Butterfly, Vesuvius and the associated  logos are trade-marks or registered trade-marks of D-Wave Systems Inc.  in the United States and/or other countries.
Patents:
D-Wave’s  chips and portions or components thereof are covered by, or for use  under, one or more of U.S. Patents: 7,135,701; 7,418,283; 7,619,437;  7,639,035; 7,687,938; 7,876,248; 7,880,529; 7,898,282; 7,899,852;  7,984,012; 8,018,244; 8,098,179; 8,169,231; 8,195,596; 8,247,799,  8,421,053; and/or one or more pending U.S. patent applications,  maskworks, as well as patents and pending patent applications in other  countries.
The  D-Wave One™; computer and portions or components thereof are covered  by, or for use under, one or more of U.S. Patents: 7,135,701; 7,418,283;  7,619,437; 7,639,035; 7,687,938; 7,843,209; 7,844,656; 7,870,087;  7,876,248; 7,880,529; 7,898,282; 7,899,852; 7,984,012; 8,008,942;  8,008,991; 8,018,244; 8,032,474; 8,035,540; 8,073,808; 8,098,179;  8,169,231; 8,174,305; 8,175,995; 8,190,548; 8,195,596; 8,195,726;  8,228,688; 8,229,863; 8,244,650; 8,244,662; 8,247,799; 8,279,022;  8,283,943; and/or one or more pending U.S. patent applications,  maskworks, as well as patents and pending patent applications in other  countries.
The  D-Wave Two™; computer and portions or components thereof are covered  by, or for use under, one or more of U.S. Patents: 7,135,701; 7,418,283;  7,619,437; 7,639,035; 7,687,938; 7,843,209; 7,844,656; 7,870,087;  7,876,248; 7,880,529; 7,898,282; 7,899,852; 7,984,012; 8,008,942;  8,008,991; 8,018,244; 8,032,474; 8,035,540; 8,073,808; 8,098,179;  8,169,231; 8,174,305; 8,175,995; 8,190,548; 8,195,596; 8,195,726;  8,228,688; 8,229,863; 8,244,650; 8,244,662; 8,247,799; 8,279,022;  8,283,943; 8,355,765; 8,386,554; 8,421,053; 8,441,329; 8,441,330;  8,464,542; and/or one or more pending U.S. patent applications,  maskworks, as well as patents and pending patent applications in other  countries.
The  D-Wave 2X™; computer and portions or components thereof are covered by,  or for use under, one or more of U.S. Patents: 7,135,701; 7,418,283;  7,619,437; 7,639,035; 7,687,938; 7,843,209; 7,844,656; 7,870,087;  7,876,248; 7,880,529; 7,898,282; 7,899,852; 7,984,012; 8,008,942;  8,008,991; 8,018,244; 8,032,474; 8,035,540; 8,073,808; 8,098,179;  8,169,231; 8,174,305; 8,175,995; 8,190,548; 8,195,596; 8,195,726;  8,228,688; 8,229,863; 8,244,650; 8,244,662; 8,247,799; 8,279,022;  8,283,943; 8,355,765; 8,386,554; 8,421,053; 8,441,329; 8,441,330;  8,464,542; 8,494,993; 8,504,497; 8,536,566; 8,560,282; 8,536,566;  8,611,974; 8,536,566; 8,536,566; 8,700,689; 8,738,105; 8,772,759;  8,786,476; 8,812,066; 8,854,074; 8,874,629; 8,951,808; 8,977,576;  9,015,215; 9,026,574; 9,069,928; and/or one or more pending U.S. patent  applications, maskworks, as well as patents and pending patent  applications in other countries.
Other Intellectual Property Rights:
D-Wave’s  products may be covered by maskworks, design patent or registered  industrial design, or other registered intellectual property rights.

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Posted July 29, 2017 by admin in category "DisInfo", "Technology

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