Systems Theory
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Big Data Needs a Big Theory to Go with It: Scientific American

Big Data Needs a Big Theory to Go with It: Scientific American | Systems Theory | Scoop.it
Just as the industrial age produced the laws of thermodynamics, we need universal laws of complexity to solve our seemingly intractable problems (RT @laurienti: @StarlingInsight is striving to help organizations deal with this type of complexity.
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luiy's curator insight, May 11, 2013 5:28 PM

What makes a “complex system” so vexing is that its collective characteristics cannot easily be predicted from underlying components: the whole is greater than, and often significantly different from, the sum of its parts. A city is much more than its buildings and people. Our bodies are more than the totality of our cells. This quality, called emergent behavior, is characteristic of economies, financial markets, urban communities, companies, organisms, the Internet, galaxies and the health care system.

 

The digital revolution is driving much of the increasing complexity and pace of life we are now seeing, but this technology also presents an opportunity. The ubiquity of cell phones and electronic transactions, the increasing use of personal medical probes, and the concept of the electronically wired “smart city” are already providing us with enormous amounts of data. With new computational tools and techniques to digest vast, interrelated databases, researchers and practitioners in science, technology, business and government have begun to bring large-scale simulations and models to bear on questions formerly out of reach of quantitative analysis, such as how cooperation emerges in society, what conditions promote innovation, and how conflicts spread and grow.

The trouble is, we don't have a unified, conceptual framework for addressing questions of complexity. We don't know what kind of data we need, nor how much, or what critical questions we should be asking. “Big data” without a “big theory” to go with it loses much of its potency and usefulness, potentially generating new unintended consequences.

Systems Theory
theoretical aspects of (social) systems theory
Curated by Ben van Lier
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New weblog about blockchain technologies posted the blockchain and the autonomy of systems You can find the weblog at http://bit.ly/2oJe0yw
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Teaching robots right from wrong

Teaching robots right from wrong | Systems Theory | Scoop.it
Artificial intelligence is outperforming the human sort in a growing range of fields – but how do we make sure it behaves morally? Simon Parkin meets the men trying to teach ethics to computers
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Google’s A.I. Program Rattles Chinese Go Master as It Wins Match

Google’s A.I. Program Rattles Chinese Go Master as It Wins Match | Systems Theory | Scoop.it
A Google program called AlphaGo won a best-of-three match against a Chinese Go master, rattling his nerves and showing the power of new artificial intelligence technologies.
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Artificial Intelligence will Speak Its Own Language Soon

Artificial Intelligence will Speak Its Own Language Soon | Systems Theory | Scoop.it



Grounded language is a new step towards Artificial Intelligence revealed by OpenAI. The article is about a system that invents a language which is tied to perception of the world. In sum, the post reveals possibilities that might be opened via researches related to an artificial language. At least the language will be similar to a signal language typical for animals. Further languages will be evolved into more complex technologies. There is no such thing as an evolution of languages. There is an evolution of the ability to use languages. This ability appeared about 75000 years ago. And it was extremely simple. And what we call a language today is how our language is transformed into a spoken act. As Chomsky mentioned it is a secondary language regarding essential processes of thinking. There are the variety of about 6000 different languages over the world. What we really want is to understand that an underlying principle that gives us the ability to acquire any of these 6000 languages. And create several new ones.The language is not necessary spoken sounds but rather it is more an inner process. It’s closer to a thinking process.The language in some sense is similar to vision.We have a written language and we have some photos. An ability to look at an object from several prospectives is the same to asking questions for details or hidden facts. An inner dialog is the same to imagining scenes. The most interesting part is that two abilities are closer than ever on the lowest level. Also, they are built from the same material with the same principles. Discovering a system that can handle both vision and a language is the base for intelligence.The ultimate goal is to make a system that recognizes reality via visual perception then creates abstraction. Also, the system is able to use a language for manipulations with the abstractions. The goal is to connect it in the way human mind does. I wrote more about this translation process here:






In spite of the fact that a language and vision refer to the same abstractions in the mind the source of all abstractions is the reality and that’s why we start grasping it with the simplest visual objects and not with a language. Later language-described objects become as real as what we look at. But there is no option to grasp a human language for a machine without an interaction with a physical world. That’s why OpenAI’s learning to communicate strategy is promising.Another reason to do such researches is that there is no possibility yet to put robots into a physical world to learn the whole environment. It just will take too much time. It’s not possible to acquire a language through static data. The only way is to be an active participant in an environment. Also, there are no easy ways to make the evasive experiments with a human mind and the computer simulations are the best candidates to become a tool of linguistics in 21 century.The goal is to create an intelligent agent that understands us. And it’s a pretty hard problem. It has been researching since 1960. However, we have not been able to describe a language formally yet because it does not exists without context. The environment is such context.Competition and CooperationWe have already seen a system which is able to demonstrate awesome results in the reinforcement learning experiments. It is DeepMind Q-learning implementation playing the Atari-games. In short, the system had an environment and an agent earning score. And the agent successfully learned how to play well.Another breakthrough was AlphaGo. The key difference is that an opponent was present behind the game. Also, the environment had much more states. One of the brilliant solutions worth mentioning is that the agent was playing against own copies.The next move will be the system where agents are able to find a way to cooperate with each other to achieve an additional value for both. OpenAI research shows how an intelligent agent behaves in a totally different environment — cooperative world like ours.






The BlackBox ProblemAn inner language might be next breakthrough to help manage the complexity of ML frameworks. Today we have to put a lot of efforts to clarify what ML system is doing and why. The language that is pretty close to a human one is an upcoming interface for working with ML engines. For multipurpose agents, such language is the best way to define an objective function. Indeed, as AI systems become increasingly sophisticated and complex, it is hard to envision how we will collaborate with them without language — without being able to ask them, “Why?” More than this, the ability to communicate effortlessly with computers would make them infinitely more useful, and it would feel nothing short of magical.  —  Will KnightThe quote is a part of the article that reveals some points where a language would provide significant advantages:






The Language ItselfDespite basic structure and vocabulary difference, it is possible to describe English and Chinese via the same terms: nouns, verbs, particles, tenses, etc. Both languages were created by thousands of communicating minds on top of surrounded reality. Next article demonstrates details:






Imagine two people the English and the Chinese. They are having a chat. There are no options to send anything except native language. There is no option to learn each other language for them in this situation. (This argument is pretty close to Chinese room argument.) But imagine they have met. It’s not so complex to learn each other language soon. What has changed? They got a surrounded reality. They are able to connect a new language with it. The babies are able to acquire language in the same way.The Language GamesThis article would not be full without mentioning Language Games developed by Ludwig Wittgenstein. Consider the description from Wikipedia: The language is meant to serve for communication between a builder A and an assistant B. A is building with building-stones: there are blocks, pillars, slabs and beams. B has to pass the stones, in the order in which A needs them. For this purpose they use a language consisting of the words “block”, “pillar” “slab”, “beam”. A calls them out; — B brings the stone which he has learnt to bring at such-and-such a call. Conceive this as a complete primitive language. (PI 2.)[3] Later “this” and “there” are added (with functions analogous to the function these words have in natural language), and “a, b, c, d” as numerals. An example of its use: builder A says “d — slab — there” and points, and builder B counts four slabs, “a, b, c, d…” and moves them to the place pointed to by A. The builder’s language is an activity into which is woven something we would recognize as language, but in a simpler form. This language-game resembles the simple forms of language taught to children, and Wittgenstein asks that we conceive of it as “a complete primitive language” for a tribe of builders.So, OpenAI’s research is a step toward creating an agent that will adapt and integrate itself in a cooperation with humans. Each such cooperation could be defined as a language game.Also, I recommend an article written by Eberhard Schoeneburg. It clarifies the role of language-games in AI.ConclusionWe made a step on a road of growing a smart system from seeds. These seeds are preconditions and algorithms. Also, the seeds are clear and perceived while a final system is powerful and hardly understood. And the combination of several seeds will lead to more powerful intelligent machines and to AGI eventually. “Learning to communicate” is another seed in a list of deep reinforcement learning, Q-learning, Monte Carlo planning etc.Still, we don’t know how to copy valuable principles of work from brains and we reinvent similar ones piece by piece by using a try and trial approach and simulations. Also, there is no a tangible consciousness itself but we are on the road to a building of a new framework with an ability to communicate.$$!ad_code_content_spilt_video_ad!$$Just imagine that each ML expert system will be able to talk and depict its thinking process. A grounded language is a discernible trend.I would even say that we have a kind of stagnation in AI today. We are at the stage of growing technology yet. However, it will be possible to recognize capabilities of AI only in a product phase and it is coming.This article was provided by Michael Kropivka. He is an AI and ML researcher, software engineer and the creator of AlgoBrainsLab. He can be found on Medium and Twitter.Want to see your story on pionic? Make a pitch.
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Google Unleashes AlphaGo in China—But Good Luck Watching It There

Google Unleashes AlphaGo in China—But Good Luck Watching It There | Systems Theory | Scoop.it
Google's Go-playing AI is going head-to-head in China against the world's best player. But inside the country, you can't get much of a view of the match.
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Exclusive: North Korea's Unit 180, the cyber warfare cell that worries the West

Exclusive: North Korea's Unit 180, the cyber warfare cell that worries the West | Systems Theory | Scoop.it
min Park and James Pearson
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Move over Bitcoin, the blockchain is only just getting started

Move over Bitcoin, the blockchain is only just getting started | Systems Theory | Scoop.it
Bitcoin and the blockchain are new ways of thinking about money and trust
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Amazon trounces rivals in battle of the shopping 'bots'

Amazon trounces rivals in battle of the shopping 'bots' | Systems Theory | Scoop.it
Earlier this year, engineers at Wal-Mart Stores Inc (WMT.N) who track rivals' prices online got a rude surprise: the technology they were using to check Amazon.com several million times a day suddenly stopped working.
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Teaching machines to understand video could be the key to giving them common sense

Yann LeCun says the next frontier in machine vision is software that learns just by observing the world.
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Rogue Robots: Testing the Limits of an Industrial Robot’s Security - Security News - Trend Micro USA

Rogue Robots: Testing the Limits of an Industrial Robot’s Security - Security News - Trend Micro USA | Systems Theory | Scoop.it
The modern world relies heavily on industrial robots. But is the current robotics ecosystem secure enough to withstand a cyber attack?
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Our Machines Now Have Knowledge We’ll Never Understand

Our Machines Now Have Knowledge We’ll Never Understand | Systems Theory | Scoop.it
Artificial intelligence is making the limits of human knowledge painfully obvious
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Hey, Computer Scientists! Stop Hating on the Humanities

Hey, Computer Scientists! Stop Hating on the Humanities | Systems Theory | Scoop.it
Opinion: Computer science departments need to teach coders more than just how to code.
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Creating robots capable of moral reasoning is like parenting – Regina Rini | Aeon Essays

Creating robots capable of moral reasoning is like parenting – Regina Rini | Aeon Essays | Systems Theory | Scoop.it
We already have a way to teach morals to alien intelligences: it's called parenting. Can we apply the same methods to robots?
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Understanding Samsung's Internet-of-Things Story in 15 Slides -- The Motley Fool

Understanding Samsung's Internet-of-Things Story in 15 Slides --  The Motley Fool | Systems Theory | Scoop.it
Samsung sees tremendous opportunity in the Internet of Things and will play a crucial role in the revolutionary connectivity trend.
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The most dexterous robot yet learned to grasp from virtual objects

The most dexterous robot yet learned to grasp from virtual objects | Systems Theory | Scoop.it
A dexterous multi-fingered robot practiced using virtual objects in a simulated world, showing how machine learning and the cloud could revolutionize manual work.
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Advances in Robotics and 3D Printing Could Make Life-Saving Artificial Hearts a Reality

Advances in Robotics and 3D Printing Could Make Life-Saving Artificial Hearts a Reality | Systems Theory | Scoop.it
Heart-related disorder treatment has undergone a renaissance in the last few decades.
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AlphaGo's Ke Jie defeat offers a sobering look at the future of man versus machine

AlphaGo's Ke Jie defeat offers a sobering look at the future of man versus machine | Systems Theory | Scoop.it
China's 19-year-old Go player Ke Jie faced off against Google's AI - and it beat him at his own game
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The Industrial Internet and the Industrial Internet of Things

The Industrial Internet and the Industrial Internet of Things | Systems Theory | Scoop.it
What is the Industrial Internet and is it different from the Industrial Internet of Things or IIoT? An overview with plenty of resources.
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China Is on Track to Fully Phase Out Cash

China Is on Track to Fully Phase Out Cash | Systems Theory | Scoop.it
Experts believe it won’t be long before China, the first country to introduce paper money, becomes the first to go totally cashless.
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How Privacy Became a Commodity for the Rich and Powerful

How Privacy Became a Commodity for the Rich and Powerful | Systems Theory | Scoop.it
It used to signal a quiet, anonymous life. Now privacy is a premium that may be out of reach for ordinary citizens.
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Can Wal-Mart’s Expensive New E-Commerce Operation Compete With Amazon?

A recent acquisition spree including Jet.com gives the retail giant much-needed digital chops.
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How DIY became a driving force of China’s robot revolution

How DIY became a driving force of China’s robot revolution | Systems Theory | Scoop.it
Makeblock’s do-it-yourself kits have made it a major player in the world of robotics – and are helping China reposition itself as a global powerhouse for the industry
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Smartphone-controlled designer cells could help keep diabetes in check

Smartphone-controlled designer cells could help keep diabetes in check | Systems Theory | Scoop.it
Researchers used optogenetics and a mobile app to stimulate cells that were designed to produce insulin in diabetic mice.
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Inside China’s Plans for World Robot Domination

Inside China’s Plans for World Robot Domination | Systems Theory | Scoop.it
Scenes from China’s quest to dominate the robotic future: At startup E-Deodar, a human-looking droid serves coffee to employees who are building $15,000 industrial bots that are about a third cheaper than foreign brands and are being used to automate assembly lines across the Pearl River Delta manufacturing hub.
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The Myth of a Superhuman AI – Backchannel

The Myth of a Superhuman AI – Backchannel | Systems Theory | Scoop.it
Debunking the myth of a superhuman artificial intelligence: Hyper-intelligent algorithms are not going to take over the world for these five reasons.
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