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I, Quantum Robot - Scientific American (blog)

I, Quantum Robot - Scientific American (blog) | Systems Theory | Scoop.it
Scientific American (blog)
I, Quantum Robot
Scientific American (blog)
Artificial Intelligence is the ability of a computer system to operate in a manner similar to human intelligence.

Via Alejandro J. Alvarez S., luiy
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Alejandro J. Alvarez S.'s curator insight, March 18, 2013 5:50 PM

Very interesting, I enjoyed reading it.

luiy's curator insight, March 19, 2013 6:13 AM

The quantum robot is the idea of combining quantum theory with robot technology. In other words, it is a practical use of the combination of quantum computing and robot technology. Quantum computing involves using quantum systems and quantum states to do computations.

 

A robot is an automated machine that is capable of doing a set of complex tasks. In some applications of robots, the programming used to run the robots may be based on artificial intelligence. Artificial Intelligence is the ability of a computer system to operate in a manner similar to human intelligence. Think of artificial intelligence as if you were training a machine to act like a human. Essentially, quantum robots are complex quantum systems.They are mobile systems with on board quantum computers that interact with their environments. Several programs would be involved in the operation of the robot. These programs would be quantum searching algorithms and quantum reinforcement learning algorithms.

 

Quantum reinforcement learning is based on superposition of the quantum state and quantum parallelism. A quantum state is a system that is a set of quantum numbers. The four basic quantum numbers represent the energy level, angular momentum, spin, and magnetization. In the superposition of quantum states, the idea is to get one state to look like another.

 

Let’s say I have two dogs. One dog knows how to fetch a bone (energy level), sit up (angular momentum), give a high five (spin), and shake hands (magnetization). Now, let’s apply the superposition of quantum states. Since one dog has been trained and given the commands, the other dog must learn to mimic or copy what the first dog did. Each time a command is achieved, reinforcement is given. The reinforcement for the dog would be a bone (or no bone if the command is not achieved).

 

In quantum reinforcement learning, it is slightly different. The idea would be similar to an “If-Then” statement. An example would be if the quantum state has a certain energy level, then the angular momentum is certain value. This idea of “If-Then” statements in the quantum world leads to an idea which can be a topic of its own; Quantum Logic.

Systems Theory
theoretical aspects of (social) systems theory
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Schumpeter and the Second Machine Age

Volg de Centric-blog over The Internet of Things, Cloud Computing, Het Nieuwe Werken, interoperabiliteit en Sustainable Architecture.
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Robo Brain is Learning from the Internet

Robo Brain is Learning from the Internet | Systems Theory | Scoop.it
Robo Brain is now at work examining images and concepts available on the Internet so that it can teach robots how to recognize, grasp and manipulate objects and predict human behavior in the environment.

Via Spaceweaver
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Alessio Erioli's curator insight, August 26, 3:58 PM

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This Oxford professor thinks artificial intelligence will destroy us all - Vox

This Oxford professor thinks artificial intelligence will destroy us all - Vox | Systems Theory | Scoop.it
This Oxford professor thinks artificial intelligence will destroy us all
Vox
In theory, these hyper-intelligent machines could be used to serve human ends. They could .... Humans are not secure systems.
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AI Systems Will Prove Useful Long Before They Become Self-Aware - Wired

AI Systems Will Prove Useful Long Before They Become Self-Aware - Wired | Systems Theory | Scoop.it
Wired
AI Systems Will Prove Useful Long Before They Become Self-Aware
Wired
winning Watson supercomputer. This could be built today in theory, but it will probably be a few years before anything like it is built in practice.
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A Thousand Kilobots Self-Assemble Into Complex Shapes - IEEE Spectrum

A Thousand Kilobots Self-Assemble Into Complex Shapes - IEEE Spectrum | Systems Theory | Scoop.it
This is probably the most robots that have ever been in the same place at the same time, ever ("@kedwardbear: #Robot swarms: 1000 #kilobots self-assemble into complex shapes.
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The man behind Facebook's artificial brain attempt (Wired UK)

The man behind Facebook's artificial brain attempt (Wired UK) | Systems Theory | Scoop.it
Deep learning has suddenly spread across the commercial tech world, from Google to Microsoft to Baidu to Twitter, just a few years after most AI researchers openly scoffed at it
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Humans Are Heading Down A Path That Will Allow Us To Supercharge The Brain

Humans Are Heading Down A Path That Will Allow Us To Supercharge The Brain | Systems Theory | Scoop.it
A small jolt of electrical stimulation can boost memory and focus. What'll be possible once we can implant chips into the brain?
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IBM Unveils a ‘Brain-Like’ Chip With 4,000 Processor Cores | Enterprise | WIRED

IBM Unveils a ‘Brain-Like’ Chip With 4,000 Processor Cores | Enterprise | WIRED | Systems Theory | Scoop.it
The human brain is the world’s most sophisticated computer, capable of learning new things on the fly, using very little data. It can recognize objects, understand speech, respond to change. Since the early days of digital technology, scientists have worked to build computers that were more like the three-pound organ inside your head. Most efforts…
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Robotic suit gives shipyard workers super strength - health - 04 August 2014 - New Scientist

Robotic suit gives shipyard workers super strength - health - 04 August 2014 - New Scientist | Systems Theory | Scoop.it
Workers building the world's biggest ships could soon don robotic exoskeletons to lug around 100-kilogram hunks of metal as if they're nothing

Via Jean-Philippe BOCQUENET
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Bostrom on Superintelligence (2): The Instrumental Convergence Thesis

Bostrom on Superintelligence (2): The Instrumental Convergence Thesis | Systems Theory | Scoop.it
This is the second post in my series on Nick Bostrom’s recent book Superintelligence: Paths, Dangers, Strategies. In the previous post, I looked at Bostrom’s defence of the orthogonality thesis. This thesis claimed that pretty much any level of intelligence — when “intelligence” is understood as skill at means-end reasoning — is compatible with pretty much any (final) goal. Thus, an artificial agent could have a very high level of intelligence, and nevertheless use that intelligence to pursue very odd final goals, including goals that are inimical to the survival of human beings. In other words, there is no guarantee that high levels of intelligence among AIs will lead to a better world for us.

Via Jean-Philippe BOCQUENET
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3 Things You Should Know The Network Economy

3 Things You Should Know The Network Economy | Systems Theory | Scoop.it
In recent years a robust science of networks has been established, so we’ve gained important insights into how they function. It’s time we start putting the science to work in how we manage enterprises.
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What is the Difference between Posthumanism and Transhumanism?

What is the Difference between Posthumanism and Transhumanism? | Systems Theory | Scoop.it
While at conferences and doing research and writing over the past couple of years, I’ve noticed a lot of confusion about the terms “posthuman,” “transhuman,” and “posthumanism.”  A lot of people—including scholars who should know better—use these terms pretty much interchangeably and indiscriminately.  Part of the problem is that these terms are all fairly new.  So for clarity’s sake, I offer these simple thumbnail definitions of all three terms…

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When Robots Come for Our Jobs, Will We Be Ready to Outsmart Them? | Opinion | WIRED

When Robots Come for Our Jobs, Will We Be Ready to Outsmart Them? | Opinion | WIRED | Systems Theory | Scoop.it
To survive in this new environment, we human beings must foster high-level cognitive or emotional skills, and find jobs that require them.
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Supercomputers make discoveries that scientists can't - tech - 27 August 2014 - New Scientist

Supercomputers make discoveries that scientists can't - tech - 27 August 2014 - New Scientist | Systems Theory | Scoop.it
No researcher could read all the papers in their field – but machines are making discoveries in their own right by mining the scientific literature
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WIRED: Radical New Theory Could Kill the Multiverse Hypothesis and Gets Rid of Concepts Like "Length" and "Mass"

WIRED: Radical New Theory Could Kill the Multiverse Hypothesis and Gets Rid of Concepts Like "Length" and "Mass" | Systems Theory | Scoop.it
Mass and length may not be fundamental properties of nature, according to new ideas bubbling out of the multiverse.

 

Though galaxies look larger than atoms and elephants appear to outweigh ants, some physicists have begun to suspect that size differences are illusory. Perhaps the fundamental description of the universe does not include the concepts of “mass” and “length,” implying that at its core, nature lacks a sense of scale.


This little-explored idea, known as scale symmetry, constitutes a radical departure from long-standing assumptions about how elementary particles acquire their properties. But it has recently emerged as a common theme of numerous talks and papers by respected particle physicists. With their field stuck at a nasty impasse, the researchers have returned to the master equations that describe the known particles and their interactions, and are asking: What happens when you erase the terms in the equations having to do with mass and length?

 

Nature, at the deepest level, may not differentiate between scales. With scale symmetry, physicists start with a basic equation that sets forth a massless collection of particles, each a unique confluence of characteristics such as whether it is matter or antimatter and has positive or negative electric charge. As these particles attract and repel one another and the effects of their interactions cascade like dominoes through the calculations, scale symmetry “breaks,” and masses and lengths spontaneously arise.

 

Similar dynamical effects generate 99 percent of the mass in the visible universe. Protons and neutrons are amalgams — each one a trio of lightweight elementary particles called quarks. The energy used to hold these quarks together gives them a combined mass that is around 100 times more than the sum of the parts. “Most of the mass that we see is generated in this way, so we are interested in seeing if it’s possible to generate all mass in this way,” said Alberto Salvio, a particle physicist at the Autonomous University of Madrid and the co-author of a recent paper on a scale-symmetric theory of nature.


In the equations of the “Standard Model” of particle physics, only a particle discovered in 2012, called the Higgs boson, comes equipped with mass from the get-go. According to a theory developed 50 years ago by the British physicist Peter Higgs and associates, it doles out mass to other elementary particles through its interactions with them. Electrons, W and Z bosons, individual quarks and so on: All their masses are believed to derive from the Higgs boson — and, in a feedback effect, they simultaneously dial the Higgs mass up or down, too.


The new scale symmetry approach rewrites the beginning of that story.
“The idea is that maybe even the Higgs mass is not really there,” said Alessandro Strumia, a particle physicist at the University of Pisa in Italy. “It can be understood with some dynamics.”

 

The concept seems far-fetched, but it is garnering interest at a time of widespread soul-searching in the field. When the Large Hadron Collider at CERN Laboratory in Geneva closed down for upgrades in early 2013, its collisions had failed to yield any of dozens of particles that many theorists had included in their equations for more than 30 years. The grand flop suggests that researchers may have taken a wrong turn decades ago in their understanding of how to calculate the masses of particles.

 

“We’re not in a position where we can afford to be particularly arrogant about our understanding of what the laws of nature must look like,” said Michael Dine, a professor of physics at the University of California, Santa Cruz, who has been following the new work on scale symmetry. “Things that I might have been skeptical about before, I’m willing to entertain.”



Via Dr. Stefan Gruenwald
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Systems Thinking and System Change

Systems Thinking and System Change | Systems Theory | Scoop.it
Fritjof Capra is a best-selling writer and leading systems thinker. Marjorie Kelly interviews Capra about the emergence of systems thinking and what lessons it has to offer in a world of convergent crises.
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Systems Theory

Systems Theory | Systems Theory | Scoop.it
By Gordon Rugg Systems theory is about what happens when individual items are connected and become a system. “Items” in this context can be anything physical and/or abstract, which gives you a pret...
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Cybernetics Tradition

Jillian Packer Dena Rosko Sherry Janda Joseph Kemp Gonzaga University 2008 (Cybernetics Tradition #claudeshannon #cybernetictradition http://t.co/6DYHDSpGAa via @SlideShare)...
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Do quantum computers threaten global encryption systems? - BBC News

Do quantum computers threaten global encryption systems? - BBC News | Systems Theory | Scoop.it
BBC News
Do quantum computers threaten global encryption systems?
BBC News
With that secure channel created, different encryption systems that are much less susceptible to attack by quantum computers are used to protect data shuttling back and forth.
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Why IBM’s New Brainlike Chip May Be “Historic” | MIT Technology Review

Why IBM’s New Brainlike Chip May Be “Historic” | MIT Technology Review | Systems Theory | Scoop.it
A chip that uses a million digital neurons and 256 million synapses may signal the beginning of a new era of more intelligent computers.
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How the Web Became Our ‘External Brain,’ and What It Means for Our Kids | Opinion | WIRED

How the Web Became Our ‘External Brain,’ and What It Means for Our Kids | Opinion | WIRED | Systems Theory | Scoop.it
Search YouTube for “baby” and “iPad” and you’ll find clips featuring one-year-olds attempting to manipulate magazine pages and television screens as though they were touch-sensitive displays. These children are one step away from assuming that such technology is a natural, spontaneous part of the material world.
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Keep, Delete, Modify: Synthetic Genes, Synthetic Cells, Synthetic Life

Keep, Delete, Modify: Synthetic Genes, Synthetic Cells, Synthetic Life | Systems Theory | Scoop.it
Nature needed about one billion years to create the simplest single-cell organisms that swam around in the primordial soup. Now, scientists are eager to create synthetic life – but better and faster.

 

Hamilton Smith (Nobel Prize in Chemistry 1978 with Werner Arber and Daniel Nathans) started his lecture at the 64th Nobel Laureate Meeting in Lindau with a quote from Richard Feynman (Nobel Prize in Physics 1965): Feynman had probably meant physical models, whereas Smith referred to living organisms. In his laboratory at the J. Craig Venter Institute, he tries to create synthetic cells: “I hope that if we create that, we will understand.”


Nowadays, the entire human genome has been decoded. But how a live human being develops from DNA molecules, a human being that can breath, eat, walk, study, love, receive Nobel Prizes and award them – nobody really understands yet. Even for single-cell organisms, this isn’t crystal clear. Even the simplest bacteria exhibit genes without apparent function, that are not essential for life. During evolution, a lot of ‘genetic waste’ has accumulated that might have been useful at some point, but was rendered useless by mutations. Some genetic fragments were in fact smuggled into the genome by viruses, others were created by accidental duplications of genetic segments. Numerous molecular mechanisms lead to many genetic variations – rendering evolution possible in the first place. But over time, many of these genes and segments have become useless.


Currently Smith tries to tidy up the genome of Mycoplasma mycoides, a microbe normally living in the digestive tract of ruminants. Originally Smith and his team wanted to use the genome of Mycoplasma genitalium, the bacterium with the smallest known genome – it needs only 475 genes to live. Smith estimates that about 100 of these are non-essential. But since M. mycoides has a much higher cell division rate, although its genome is twice as large, experiments with M. mycoides proved to be more effective. During this ‘minimal cell project’, the researchers switch off one gene after another and study the effects on the microbes. (And the slower the microbes grow, the longer the researchers have to wait for their results.) Smith’s final goal is “a genome that is very understandable – we are searching for the genetic kernels of life”.


Smith also assumes that all genes from the last group can be switched off without negative impacts on the microbes. Concerning the middle category, the researchers have to carefully weigh all options. When all is done, the result should be a bacterium that can still multiply rapidly, at least in laboratory conditions that offer plenty of nourishment, constant temperatures, but no competitors. The researchers’ goal is a fifty percent genome reduction in a happily thriving microbe that divides at least once in 100 minutes.


Smith likes using computer terms to describe his work. He compares the genome of any organism with its software, the rest is hardware (the cytoplasm, proteins and enzymes), controlled by said software. As soon as a cell receives a new genetic program, it starts to put this program to use. In order to test their own synthetic programs, Smith and his team replaced the bacterium’s DNA with synthetic DNA containing their basic program. To date, the old ‘hardware’ has not adopted the new program ‘update’. In computer speak, troubleshooting and maintenance are called “debugging”: Smith and his team will be busy with debugging for some time.

 


Via Dr. Stefan Gruenwald
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Philosophical Disquisitions: Bostrom on Superintelligence (1): The Orthogonality Thesis

Philosophical Disquisitions: Bostrom on Superintelligence (1): The Orthogonality Thesis | Systems Theory | Scoop.it

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William Gibson: the man who saw tomorrow

William Gibson: the man who saw tomorrow | Systems Theory | Scoop.it
William Gibson's science-fiction novel, 30 years old this month, leapt into cyberspace almost before it existed, writes Ed Cumming

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The Rapid Advance of Artificial Intelligence

The Rapid Advance of Artificial Intelligence | Systems Theory | Scoop.it
Scientists and engineers are creating a world in which cars drive themselves, machines recognize people and humanoid robots travel unattended.

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Microsoft Challenges Google’s Artificial Brain With ‘Project Adam’ | Enterprise | WIRED

Microsoft Challenges Google’s Artificial Brain With ‘Project Adam’ | Enterprise | WIRED | Systems Theory | Scoop.it
Drawing on the work of a clever cadre of academic researchers, the biggest names in tech—including Google, Facebook, Microsoft, and Apple—are embracing a more powerful form of AI known as “deep learning,” using it to improve everything from speech recognition and language translation to computer vision, the ability to identify images without human help.

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