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I-World™: AI-Powered Future:I-World™: AI-Powered Future:
Universal AI Model: Encyclopedic AI™:Universal AI Model: Encyclop...
The AI-Powered World: I-WorldThe AI-Powered World: I-World
ENCYCLOPEDIC INTELLIGENCE PlatformENCYCLOPEDIC INTELLIGENCE Pla...
Real AI will be 'either best or worst thing' forReal AI will be 'either best or worst thing' for
humanityhumanity
• The cr...
WHAT IS RAI AND WHAT IS AIWHAT IS RAI AND WHAT IS AI
• RAI IS INTELLIGENT SYSTEMS (SMART CYBER-PHYSICAL SYSTEMS, Autonomou...
Designing REAL AI based on the Theory ofDesigning REAL AI based on the Theory of
Reality and Disruptive InnovationsReality...
THE I-WORLD PLATFORM: Future World Technology
Roadmap
• WORLD 1.0 (Industrial World) :: GlobalWORLD 1.0 (Industrial World)...
General Purpose InnovationsGeneral Purpose Innovations
GPT Spillover Effects Date Classification
Domestication of plants N...
The AI-Powered World: I-WorldThe AI-Powered World: I-World
• Smart spaces, territories, and communities, intelligent machi...
DEEP Ubiquitous AI: Encyclopedic Intelligence Platform:DEEP Ubiquitous AI: Encyclopedic Intelligence Platform:
Creating Ma...
BE READY TO BE DISRUPTED BY THEBE READY TO BE DISRUPTED BY THE
ULTIMATE AI TECHNOLOGYULTIMATE AI TECHNOLOGY
• Emerging tec...
Encyclopedic Cyber-Physical Intelligence, or ASI:Encyclopedic Cyber-Physical Intelligence, or ASI: GlobalGlobal
Ontology, ...
Encyclopedic AI: a new AI paradigmEncyclopedic AI: a new AI paradigm
• ““Artificial Intelligence is colossally hyped these...
GLOBAL TRENDS AND DISRUPTIVE AIGLOBAL TRENDS AND DISRUPTIVE AI
TECHNOLOGIESTECHNOLOGIES
Global IT-Enabled TrendsGlobal IT-...
The Future I-World:The Future I-World: Smart Cyber-Physical SystemsSmart Cyber-Physical Systems
• The Future AI World is t...
The Future I-Word: No existential riskThe Future I-Word: No existential risk
• As to Stephen Hawking, “the development of ...
•• What are strong AI and weak AI, AGI,What are strong AI and weak AI, AGI,
ASI, and SuperIntelligence?ASI, and SuperIntel...
"Smart" AI vs "Dumb" AI: Sci-Fiction as Reality"Smart" AI vs "Dumb" AI: Sci-Fiction as Reality
• "Dumb" AIs are a form of ...
STUPID Fake AI vs REAL Smart AI
• STUPID Artificial intelligence (AI) is widely defined as “intelligence exhibited by mach...
What is “Stupid” AI?What is “Stupid” AI?
• It's the study of methods for making computers behave intelligently.It's the st...
The Hype of Stupid AI:The Hype of Stupid AI: from the AI Winter to the newfrom the AI Winter to the new
AI WinterAI Winter...
Some “Stupid AI” projectsSome “Stupid AI” projects
• The listing of narrow-minded AI
specialized projects in: brain simula...
““Stupid AI” PRINCIPLESStupid AI” PRINCIPLES
• Research Issues
• 1) Research Goal: The goal of AI research should be to cr...
AI versus Machine learning : what's theAI versus Machine learning : what's the
difference?difference?
• AI and machine lea...
AI versus Machine learning : what's theAI versus Machine learning : what's the
difference?difference?
• Machine learning i...
Standard Stupid AI Conferences:Standard Stupid AI Conferences: MACHINE LEARNINGMACHINE LEARNING
• MACHINE LEARNING
• DRONE...
SEAS: Sentient World SimulationSEAS: Sentient World Simulation
• SEAS is currently being used by Homeland Security and the...
The Partnership on “Stupid” AI: GoalsThe Partnership on “Stupid” AI: Goals
• We are at an inflection point in the developm...
Smart OpenAI:Smart OpenAI: ML Artificial General IntelligenceML Artificial General Intelligence
• OpenAI conducts fundamen...
Apple AI:Apple AI: ML AIML AI
• Apple is working on the same problems as many other companies exploring machine learning:A...
Amazon AI:Amazon AI: Bringing powerful artificial intelligence to allBringing powerful artificial intelligence to all
deve...
Microsoft Artificial IntelligenceMicrosoft Artificial Intelligence
• Pursuing computing advances to create intelligent mac...
The Facebook AI:The Facebook AI: 10-year road map10-year road map
Google AI: Google BrainGoogle AI: Google Brain
• The mission of the Brain team is "Make machines intelligent. Improve peop...
DeepMind AIDeepMind AI
• DeepMind's scientific mission is to push the boundaries of AI, developing systems thatDeepMind's ...
Grand Challenge 5:Grand Challenge 5:
The Architecture of Brain and Mind Integrating Low-Level Neuronal BrainThe Architectu...
Machine Learning Types: Markov chainsMachine Learning Types: Markov chains
• Machine learning tasks are typically classifi...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent...
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Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent Technologies, Infrastructures, Industries, People, Communities, Cities, Countries, and Smart World

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AI-Powered Future:
AI Communities, AI Smart Cities, Intelligent Countries, Smart World
New AI Paradigm
REAL AI: Hardware + Software + Brainware + Mindware
Smart AI vs Stupid AI: ontological engineering vs feature engineering
On the Partnership on AI: Amazon, Apple, AAAI, DeepMind, Facebook, Google, IBM, Microsoft, OpenAI
AI Computers, AI chip, AI GPU, etc
Dumb/ML Artificial Intelligence as humanity's "biggest existential threat"
Machines with Superhuman Brains
Machines, telecommunication networks, drones, robots, self-driving cars, plants have the potential to reinvent our life and industries as far-ranging as safety, government, education, healthcare, logistics, commerce, and transit. And thanks to new developments in disruptive software (wetware, brainware and mindware), such as artificial intelligence, they’re getting smart. This will create a vast, still-unknown world of possibilities.

Published in: Technology
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  • DOWNLOAD FULL BOOKS INTO AVAILABLE FORMAT ......................................................................................................................... ......................................................................................................................... 1.DOWNLOAD FULL PDF EBOOK here { https://tinyurl.com/y8nn3gmc } ......................................................................................................................... 1.DOWNLOAD FULL EPUB Ebook here { https://tinyurl.com/y8nn3gmc } ......................................................................................................................... 1.DOWNLOAD FULL doc Ebook here { https://tinyurl.com/y8nn3gmc } ......................................................................................................................... 1.DOWNLOAD FULL PDF EBOOK here { https://tinyurl.com/y8nn3gmc } ......................................................................................................................... 1.DOWNLOAD FULL EPUB Ebook here { https://tinyurl.com/y8nn3gmc } ......................................................................................................................... 1.DOWNLOAD FULL doc Ebook here { https://tinyurl.com/y8nn3gmc } ......................................................................................................................... ......................................................................................................................... ......................................................................................................................... .............. Browse by Genre Available eBooks ......................................................................................................................... Art, Biography, Business, Chick Lit, Children's, Christian, Classics, Comics, Contemporary, Cookbooks, Crime, Ebooks, Fantasy, Fiction, Graphic Novels, Historical Fiction, History, Horror, Humor And Comedy, Manga, Memoir, Music, Mystery, Non Fiction, Paranormal, Philosophy, Poetry, Psychology, Religion, Romance, Science, Science Fiction, Self Help, Suspense, Spirituality, Sports, Thriller, Travel, Young Adult,
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  • Artificial intelligence (AI) and machine learning (ML) as different as sky and earth The malicious use of AI will impact how we construct and manage our digital infrastructure as well as how we design and distribute AI systems, and will likely require policy and other institutional responses. The question this report hopes to answer is: how can we forecast, prevent, and (when necessary) mitigate the harmful effects of malicious uses of AI? We convened a workshop at the University of Oxford on the topic in February 2017, bringing together experts on AI safety, drones, cybersecurity, lethal autonomous weapon systems, and counterterrorism . This document summarizes the findings of that workshop and our conclusions after subsequent research. We structure our analysis by separately considering three security domains, and illustrate possible changes to threats within these domains through representative examples: • Digital security. The use of AI to automate tasks involved in carrying out cyberattacks will alleviate the existing tradeoff between the scale and efficacy of attacks. This may expand the threat associated with labor-intensive cyberattacks (such as spear phishing). We also expect novel attacks that exploit human vulnerabilities (e.g. through the use of speech synthesis for impersonation), existing software vulnerabilities (e.g. through automated hacking), or the vulnerabilities of AI systems (e.g. through adversarial examples and data poisoning). • Physical security. The use of AI to automate tasks involved in carrying out attacks with drones and other physical systems (e.g. through the deployment of autonomous weapons systems) may expand the threats associated with these attacks. We also expect novel attacks that subvert cyberphysical systems (e.g. causing autonomous vehicles to crash) or involve physical systems that it would be infeasible to direct remotely (e.g. a swarm of thousands of micro-drones). • Political security. The use of AI to automate tasks involved in surveillance (e.g. analysing mass-collected data), persuasion (e.g. creating targeted propaganda), and deception (e.g. manipulating videos) may expand threats associated with privacy invasion and social manipulation. We also expect novel attacks that take advantage of an improved capacity to analyse human behaviors, moods, and beliefs on the basis of available data. These concerns are most significant in the context of authoritarian states, but may also undermine the ability of democracies to sustain truthful public debates. https://arxiv.org/ftp/arxiv/papers/1802/1802.07228.pdf
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  • Order Global AI Report on http://www.worldxxi.com. One of the most synergistic, ground-breaking and revolutionary concepts is the idea of Intelligent World, having the major features and parameters as: All connected; All digital; All intelligent (Everything will become intelligent, and our world as a whole will be intelligent, including its territories, geopolitical communities and cities). The driver and engine of Intelligent World, Artificial Intelligence (AI), is redesigned as an intelligent complex socio-technological system having the Future Human-Machine Intelligence Architecture: (General Encyclopedic Universal) Global AI™: Natural Intelligence + AI + ANN + ML + Automation + Robots + IoT + Cyber-Physical Systems + Smart Territories & Intelligent Communities = (AI Powered World, I-World). And according to Huawei’s CEO Eric Xu, “The journey to an intelligent world has already begun”. Don't miss your train!
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  • A Big Confusion from Big Internet Companies: Confusing ML Systems with AI Systems Artificial intelligence is divided as “narrow AI”, designed to perform specific tasks within a domain, and “general AI”, which can learn and perform tasks anywhere. Machine learning (ML) as the development of new statistics-based algorithms and models in computer science is referred to “narrow AI”. ML is to empirically discover models/algorithms/knowledge/insights/rules through learning from historical relationships and trends in the data, specifically, Big Data. As such, ML involves computational statistics, statistical computing and mathematical optimization, whereas AI draws upon many sciences and technologies: computer science, mathematics, psychology, linguistics, philosophy, neuroscience, physical science, engineering, etc. AI is about creating intelligent systems [that can know, learn, reason, plan, perceive, process natural language, act], involving machine intelligence, artificial consciousness, and intelligent communities. ML is just automated feature engineering, feature learning or data representation learning, to automatically discover the representations needed for feature detection or classification from raw data, or real-world data as images, video, and sensor data. Crucial, modern ML systems are not real AIs for many good reasons: designed to perform specific tasks within a domain (e.g. language translation); decisions as not preprogrammed by humans; decisions as emergent properties of the learning algorithms and the biased data set they are trained on; multiple hidden layers in an artificial neural network; performing either supervised learning, reinforcement learning, or unsupervised learning; the lack of unifying theory surrounding an uncountable number of machine learning algorithms and methods; a lack of discovery component; requiring mathematically and computationally convenient input; a lack of transparency and interpretability in decision-making; safety and security issues; considerations regarding accountability; issues of data quality and potential bias. ML systems could be trained with data that is biased, inaccurate, incomplete or misleading. Accordingly, reliable and effective machine learning is difficult because finding patterns is hard mostly due to lack of available training data; so, machine-learning programs often fail to deliver. Many recent advances in ML have not been due to radical innovations in learning algorithms, but rather by the advances in computer power and enormous amount of data enabled by the Internet. This is fast capitalized by big Internet firms, as Google, Facebook, Amazon etc. presenting themselves as AI first companies. As a result, given the complexity of contemporary ANNs, we have trouble discerning how MLs produce decisions, translating the process into a human language, as understanding of AlphaGo’s logic, motives and rationales. As research psychologist Gary Marcus noted in his article: "Is "Deep Learning" a Revolution in Artificial Intelligence?" "Realistically, deep learning is only part of the larger challenge of building intelligent machines. Such techniques lack ways of representing causal relationships (...) have no obvious ways of performing logical inferences, and they are also still a long way from integrating abstract knowledge, such as information about what objects are, what they are for, and how they are typically used. The most powerful A.I. systems, like Watson (...) use techniques like deep learning as just one element in a very complicated ensemble of techniques, ranging from the statistical technique of Bayesian inference to deductive reasoning." Given the technological distrust to ML systems, special big concerns are caused by applying ML for Lethal Autonomous Weapons Systems (LAWS). In sum, ML has little to do with Real AI, or General AI, with clear logic, high safety and security, transparency and accountability, critical to developing an AI Internet that people trust. So, whenever you see AI, read it just as ML, including the Big Internet Companies, as well as "Artificial Intelligence and Machine Learning: Policy Paper" of The Internet Society. https://www.internetsociety.org/resources/doc/2017/artificial-intelligence-and-machine-learning-policy-paper http://www.worldxxi.com
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Global AI: I-World: AI X.0: Future Intelligence: Искусственный Суперинтеллект: from Intelligent Q-Computing to Intelligent Technologies, Infrastructures, Industries, People, Communities, Cities, Countries, and Smart World

  1. 1. I-World™: AI-Powered Future:I-World™: AI-Powered Future: Universal AI Model: Encyclopedic AI™:Universal AI Model: Encyclopedic AI™: AI, Deep Learning, Quantum Intelligence,AI, Deep Learning, Quantum Intelligence, AI Supercomputer, Encyclopedic AI PlatformAI Supercomputer, Encyclopedic AI Platform Smart Cyber-Physical Systems,Smart Cyber-Physical Systems, AI Communities, AI Smart Cities, Intelligent Countries,AI Communities, AI Smart Cities, Intelligent Countries, Intelligent Communities of the FutureIntelligent Communities of the Future Smart World:Smart World: IWorld (Intelligent Innovative Interconnected InclusiveIWorld (Intelligent Innovative Interconnected Inclusive World)World) Future Intelligence: Natural Intelligence & Artificial Intelligence:Future Intelligence: Natural Intelligence & Artificial Intelligence: Be Ready To Be Incorporated by REAL AIBe Ready To Be Incorporated by REAL AI Real “Artificial intelligence has the power to eradicate poverty andReal “Artificial intelligence has the power to eradicate poverty and disease and hasten the end of human civilisation as we know it”disease and hasten the end of human civilisation as we know it”
  2. 2. The AI-Powered World: I-WorldThe AI-Powered World: I-World ENCYCLOPEDIC INTELLIGENCE PlatformENCYCLOPEDIC INTELLIGENCE Platform X:X: AI Communities, AI Cities, AI Countries, AI Continents, Smart WorldAI Communities, AI Cities, AI Countries, AI Continents, Smart World What Is Not Artificial Intelligence WHAT IS REAL ARTIFICIAL INTELLIGENCE: True AI vs. False AI How To Design TRUE AI Systems Should Humans Fear the Rise of SuperIntelligent Systems? Encyclopedic AI: AI + ANN + Automation + Robots + IoT + Cyber- Physical Systems = (AI Powered World, I-World)   Quantum Artificial Intelligence and Superintelligent Q-RobotsQuantum Artificial Intelligence and Superintelligent Q-Robots Cyber-Physical Intelligence: Natural Intelligence cum Artificial IntelligenceCyber-Physical Intelligence: Natural Intelligence cum Artificial Intelligence Smart AI vs Stupid AISmart AI vs Stupid AI RealReal AI: (Hardware + Software) + (Brainware + Mindware) httphttp://www.worldxxi.com/://www.worldxxi.com/ Azamat AbdoullaevAzamat Abdoullaev http://www.slideshare.net/ashabook/eis-ltdhttp://www.slideshare.net/ashabook/eis-ltd Ubiquitous Computing Intelligence: from Smart Devices to Smart WorldUbiquitous Computing Intelligence: from Smart Devices to Smart World I-WORLD DEVELOPMENTI-WORLD DEVELOPMENT httphttp://://wwwwww..slideshareslideshare..netnet//ashabookashabook//creatingcreating--thethe--futurefuture--tomorrowstomorrows--worldworld http://www.slideshare.net/ashabook/iworld-25498222http://www.slideshare.net/ashabook/iworld-25498222 httphttp://://wwwwww..slideshareslideshare..netnet//ashabookashabook//smartsmart--worldworld EU, Russia, 2017
  3. 3. Real AI will be 'either best or worst thing' forReal AI will be 'either best or worst thing' for humanityhumanity • The creation of powerful artificial intelligence will be “either the best, or the worst thing, ever to happen to humanity”. • Researching the future of intelligence is “crucial to the future of our civilisation and our species”.Researching the future of intelligence is “crucial to the future of our civilisation and our species”. • ““We spend a great deal of time studying history,” Hawking said, “which, let’s face it, is mostly theWe spend a great deal of time studying history,” Hawking said, “which, let’s face it, is mostly the history of stupidity. So it’s a welcome change that people are studying instead the future ofhistory of stupidity. So it’s a welcome change that people are studying instead the future of intelligence.”intelligence.” • ““The potential benefits of creating intelligence are huge”.The potential benefits of creating intelligence are huge”. • ““We cannot predict what we might achieve when our own minds are amplified by AI.We cannot predict what we might achieve when our own minds are amplified by AI. • Perhaps with the tools of this new technological revolution, we will be able to undo some of thePerhaps with the tools of this new technological revolution, we will be able to undo some of the damage done to the natural world by the last one – industrialisation. And surely we will aim to finallydamage done to the natural world by the last one – industrialisation. And surely we will aim to finally eradicate disease and poverty.eradicate disease and poverty. • ““Every aspect of our lives will be transformed. In short, success in creating AI could be the biggestEvery aspect of our lives will be transformed. In short, success in creating AI could be the biggest event in the history of our civilisation.”event in the history of our civilisation.” • Stephen Hawking, Exploring the Impact of Artificial intelligence, the Leverhulme Centre for the Future of Intelligence (LCFI) atStephen Hawking, Exploring the Impact of Artificial intelligence, the Leverhulme Centre for the Future of Intelligence (LCFI) at • http://www.cam.ac.uk/research/news/the-best-or-worst-thing-to-happen-to-humanity-stephen-hawking-launches-centre-for-thhttp://www.cam.ac.uk/research/news/the-best-or-worst-thing-to-happen-to-humanity-stephen-hawking-launches-centre-for-th • https://www.theguardian.com/science/2016/oct/19/stephen-hawking-ai-best-or-worst-thing-for-humanity-cambridgehttps://www.theguardian.com/science/2016/oct/19/stephen-hawking-ai-best-or-worst-thing-for-humanity-cambridge • Elon Musk, the SpaceX and Tesla CEO urged lawmakers to regulate AI now before it poses a grave threat toElon Musk, the SpaceX and Tesla CEO urged lawmakers to regulate AI now before it poses a grave threat to humanity, stating that artificial intelligence is humanity's "biggest existential threat.“humanity, stating that artificial intelligence is humanity's "biggest existential threat.“ • In fact, ML/Dumb Artificial Intelligence andIn fact, ML/Dumb Artificial Intelligence and humanity's greed and stupidityhumanity's greed and stupidity are humanity's "biggestare humanity's "biggest existential threats“.existential threats“.
  4. 4. WHAT IS RAI AND WHAT IS AIWHAT IS RAI AND WHAT IS AI • RAI IS INTELLIGENT SYSTEMS (SMART CYBER-PHYSICAL SYSTEMS, Autonomous Systems,RAI IS INTELLIGENT SYSTEMS (SMART CYBER-PHYSICAL SYSTEMS, Autonomous Systems, as the INTERNET OF EVERYTHING)as the INTERNET OF EVERYTHING) • ““Cyber-physical symbol systems having the necessary and sufficient means of general intelligentCyber-physical symbol systems having the necessary and sufficient means of general intelligent action”action” • Artificial beings endowed with human-like intelligenceArtificial beings endowed with human-like intelligence • Intelligent entities endowed with superhuman intelligence • RAI is smart computing platforms having interconnected abstraction levels, including aRAI is smart computing platforms having interconnected abstraction levels, including a supercomputer architecture, AI hardware, smart web browsers, i-OS platform (desktop, laptop, server,supercomputer architecture, AI hardware, smart web browsers, i-OS platform (desktop, laptop, server, or mobile), smart applications, intelligent software development frameworks (support programs,or mobile), smart applications, intelligent software development frameworks (support programs, compilers, code libraries, tool sets, and APIs), smart cloud computing as PAAS, and virtualizedcompilers, code libraries, tool sets, and APIs), smart cloud computing as PAAS, and virtualized intelligent hardware, OS, software and storage.intelligent hardware, OS, software and storage. • RAI is the capacity of a digital, optical, biological or quantum computer or computer control robotRAI is the capacity of a digital, optical, biological or quantum computer or computer control robot device to approximate human mind, consciousness, thinking and intelligence by sensing, perceiving,device to approximate human mind, consciousness, thinking and intelligence by sensing, perceiving, knowing, reasoning, learning, natural language processing (communication), pattern recognition,knowing, reasoning, learning, natural language processing (communication), pattern recognition, decision making, problem solving, and intelligent behaviors.decision making, problem solving, and intelligent behaviors. • AI is the science and engineering of making intelligent machines, especially intelligent computer programs.AI is the science and engineering of making intelligent machines, especially intelligent computer programs. • AI is the study of "intelligent agents“, any device that perceives its environment and takes optimal actions to perform some intelligent operations. • Artificial Intelligence is Machine Intelligence, MI, intelligence exhibited by machines.Artificial Intelligence is Machine Intelligence, MI, intelligence exhibited by machines. • AI is artificial neural networks (ANNs) inspired by the biological neural networks constituting animalAI is artificial neural networks (ANNs) inspired by the biological neural networks constituting animal brains and characterized by knowledge embodied in the parameters of a cognitive model.brains and characterized by knowledge embodied in the parameters of a cognitive model. • https://www.aaai.org/Papers/Workshops/2002/WS-02-11/WS02-11-004.pdfhttps://www.aaai.org/Papers/Workshops/2002/WS-02-11/WS02-11-004.pdf •
  5. 5. Designing REAL AI based on the Theory ofDesigning REAL AI based on the Theory of Reality and Disruptive InnovationsReality and Disruptive Innovations • Real/Encyclopedic AI (RAI/EAI): • AI + ANN + Automation + Robots + IoT + Cyber-Physical Systems • = (AI Powered World, I-World) • Real AI: Global Knowledge Base (Theory of theReal AI: Global Knowledge Base (Theory of the World) + Universal Reasoning MechanismWorld) + Universal Reasoning Mechanism (How the World Works) + Deep Learning(How the World Works) + Deep Learning Algorithms + Intelligent Interface + SmartAlgorithms + Intelligent Interface + Smart Technologies + Disruptive InnovationsTechnologies + Disruptive Innovations • https://www.worldxxi.com/https://www.worldxxi.com/
  6. 6. THE I-WORLD PLATFORM: Future World Technology Roadmap • WORLD 1.0 (Industrial World) :: GlobalWORLD 1.0 (Industrial World) :: Global Community 0.0 > Society 1.0> Nation 1.0 >Community 0.0 > Society 1.0> Nation 1.0 > City 1.0City 1.0 > Science 1.0 > Technology 1.0 >> Science 1.0 > Technology 1.0 > Industry 1.0 > Infrastructure 1.0 > Network 1.0Industry 1.0 > Infrastructure 1.0 > Network 1.0 > Telecom 1.0 > Internet 1.0 >> Telecom 1.0 > Internet 1.0 > Web 1.0Web 1.0 >> Service 1.0 > Government 1.0 > Medicine 1.0 >Service 1.0 > Government 1.0 > Medicine 1.0 > Human 1.0 > Intelligence 1.0 >…Space 1.0Human 1.0 > Intelligence 1.0 >…Space 1.0 • WORLD 2.0 (Information World) :: GlobalWORLD 2.0 (Information World) :: Global Community 2.0 > Society 2.0 > Nation 2.0>Community 2.0 > Society 2.0 > Nation 2.0> City 2.0City 2.0 > Science 2.0 > Technology 2.0 >> Science 2.0 > Technology 2.0 > Industry 2.0 > Infrastructure 2.0 > NetworkIndustry 2.0 > Infrastructure 2.0 > Network 2.0 > Telecom 2.0 > Internet 2.0 >2.0 > Telecom 2.0 > Internet 2.0 > Web 2.0Web 2.0 >> Service 2.0 > Government 2.0 > Medicine 2.0Service 2.0 > Government 2.0 > Medicine 2.0 > Human 2.0 > Intelligence 2.0 >…Space 2.0> Human 2.0 > Intelligence 2.0 >…Space 2.0 • WORLD 3.0 (Smart World) :: GlobalWORLD 3.0 (Smart World) :: Global Community 3.0 > Society 3.0 > Nation 3.0>Community 3.0 > Society 3.0 > Nation 3.0> City 3.0 > Science 3.0 > Technology 3.0 >City 3.0 > Science 3.0 > Technology 3.0 > Industry 3.0 > Infrastructure 3.0 > NetworkIndustry 3.0 > Infrastructure 3.0 > Network 3.0 > Telecom 3.0 > Internet 3.0 >3.0 > Telecom 3.0 > Internet 3.0 > Web 3.0Web 3.0 >> Service 3.0 > Government 3.0 > Medicine 3.0Service 3.0 > Government 3.0 > Medicine 3.0 > Human 3.0 > > Intelligence 3.0 > …Space> Human 3.0 > > Intelligence 3.0 > …Space 3.03.0 • WORLD X.0 ::WORLD X.0 :: • Global Community X.0 >Global Community X.0 > • Society X.0 >Society X.0 > • Nation X.0>Nation X.0> • City X.0 >City X.0 > • Science X.0 >Science X.0 > • Technology X.0 >Technology X.0 > • Industry X.0 >Industry X.0 > • Infrastructure X.0 >Infrastructure X.0 > • Network X.0 >Network X.0 > • Telecom X.0 >Telecom X.0 > • Internet X.0 >Internet X.0 > • Web X.0 >Web X.0 > • Service X.0 >Service X.0 > • Government X.0 >Government X.0 > • Medicine X.0 > Human X.0 >Medicine X.0 > Human X.0 > • Intelligence X.0 >…Space X.0Intelligence X.0 >…Space X.0 • httphttp ://www.slideshare.net/ashabook/creating-the-future-tomorrows-world://www.slideshare.net/ashabook/creating-the-future-tomorrows-world • http://http://www.slideshare.net/ashabook/innovation-platformwww.slideshare.net/ashabook/innovation-platform
  7. 7. General Purpose InnovationsGeneral Purpose Innovations GPT Spillover Effects Date Classification Domestication of plants Neolithic Agricultural Revolution 9000-8000 BC Process Domestication of animals Neolithic Agricultural Revolution, Working animals 8500-7500 BC Process Smelting of ore Early metal tools 8000-7000 BC Process Wheel Mechanization, Potter's wheel 4000–3000 BC Product Writing Trade, Record keeping 3400-3200 BC Process Bronze Tools & Weapons 2800 BC Product Iron Tools & Weapons 1200 BC Product Water wheel Inanimate power, Mechanical systems Early Middle Ages Product Three-Masted Sailing Ship Discovery of the New World, Maritime trade, Colonialism 15th Century Product Printing Knowledge economy, Science education, Financial credit 16th Century Process Factory system Industrial Revolution, Interchangeable parts Late 18th Century Organisation Steam Engine Industrial Revolution, Machine tools Late 18th Century Product Railways Suburbs, Commuting, Flexible location of factories Mid 19th Century Product Iron Steamship Global agricultural trade, International tourism, Dreadnought Battleship Mid 19th Century Product Internal Combustion Engine Automobile, Airplane, Oil industry, Mobile warfare Late 19th Century Product Electricity Centralized power generation, Factory electrification, Telegraphic communication Late 19th Century Product Automobile Suburbs, Commuting, Shopping centres , Long-distance domestic tourism 20th Century Product Airplane International tourism, International sports leagues, Mobile warfare 20th Century Product Mass Production Consumerism, Growth of US economy 20th Century Organisation Computer Digital Revolution 20th Century Product Lean Production Growth of Japanese economy 20th Century Organisation Internet Electronic business, Crowdsourcing, Social networking, Information warfare 20th Century Product Biotechnology Genetically modified food, Bioengineering, Gene therapy 20th Century Process Business Virtualization Paperless office, Telecommuting, 21st Century Process
  8. 8. The AI-Powered World: I-WorldThe AI-Powered World: I-World • Smart spaces, territories, and communities, intelligent machines, telecommunication networks, drones, robots, self- driving cars, factories, and plants have the potential to reinvent our future life, safety, government, human settlement, education, science, technology, healthcare, logistics, commerce, and transportation. Cutting-edge disruptions in intelligent software (wetware, brainware and mindware ), such as artificial intelligence, make them superhumanly smart and intelligent. • This will create a vast, unknown world of unlimited possibilities, an AI-Powered World, Intelligent World, or I- World of AI Communities, Transnational, National, Regional, Urban or Local. • http://www.slideshare.net/ashabook/iworld-25498222 • http://www.slideshare.net/ashabook/smart-revolution • http://www.slideshare.net/ashabook/creating-the-future-tomorrows-world • http://www.slideshare.net/ashabook/smartworl-dabr • http://www.slideshare.net/ashabook/shaping-the-future-world • http://www.slideshare.net/ashabook/innovation-platform • http://www.slideshare.net/ashabook/eco-world-commandments • http://www.slideshare.net/ashabook/smart-world • http://www.slideshare.net/ashabook/future-world-27173937 • http:// eu-smartcities.eu/blog/smart-superpowers-projects-states-powers-great-powers-and-hyperpowers • SMART World: http://www.worldxxi.com/SMART World: http://www.worldxxi.com/
  9. 9. DEEP Ubiquitous AI: Encyclopedic Intelligence Platform:DEEP Ubiquitous AI: Encyclopedic Intelligence Platform: Creating Machines with Superhuman BrainsCreating Machines with Superhuman Brains • ENCYCLOPEDIC INTELLIGENCE I:ENCYCLOPEDIC INTELLIGENCE I: httphttp://://wwwwww..slideshareslideshare..netnet//ashabookashabook// encyclopedicencyclopedic--intelligenceintelligence ENCYCLOPEDIC INTELLIGENCE II:ENCYCLOPEDIC INTELLIGENCE II: http://www.slideshare.net/ashabook/encyclopedic-intelligence-24260973http://www.slideshare.net/ashabook/encyclopedic-intelligence-24260973 ENCYCLOPEDIC INTELLIGENCE III:ENCYCLOPEDIC INTELLIGENCE III: http://www.slideshare.net/ashabook/encyclopedic-intelligence-big-science-and-technologyhttp://www.slideshare.net/ashabook/encyclopedic-intelligence-big-science-and-technology ENCYCLOPEDIC INTELLIGENCE IV:ENCYCLOPEDIC INTELLIGENCE IV: http://www.slideshare.net/ashabook/encyclopedic-intelligence-global-marketinghttp://www.slideshare.net/ashabook/encyclopedic-intelligence-global-marketing ENCYCLOPEDIC INTELLIGENCE X:ENCYCLOPEDIC INTELLIGENCE X: https://www.slideshare.net/ashabook/encyclopedic-intelligence-deep-aihttps://www.slideshare.net/ashabook/encyclopedic-intelligence-deep-ai • EIS Encyclopedic Intelligent Systems ltd • http://www.slideshare.net/ashabook/eis-ltdhttp://www.slideshare.net/ashabook/eis-ltd https://https://www.aaai.org/Papers/Workshops/2002/WS-02-11/WS02-11-004.pdfwww.aaai.org/Papers/Workshops/2002/WS-02-11/WS02-11-004.pdf • https://https:// www.amazon.com/Artificial-Superintelligence-Azamat-Abdoullaev/dp/9963842100www.amazon.com/Artificial-Superintelligence-Azamat-Abdoullaev/dp/9963842100 •
  10. 10. BE READY TO BE DISRUPTED BY THEBE READY TO BE DISRUPTED BY THE ULTIMATE AI TECHNOLOGYULTIMATE AI TECHNOLOGY • Emerging technology: Artificial general intelligence Status: Hypothetical, experiments; limited uses in specialized domains Potentially marginalized technologies: Human systems  Potential applications: Creating intelligent devices and robots; AI can lead scientific projects, government, army, corporate governance, film and books creation, inventions etc. Encyclopedic Intelligence, or Artificial General Intelligence, is the ultimate socio- technological disruptive innovation of all Emerging Technologies in Agriculture; Aviation; Construction; Architecture; Materials science; Displays; Electronics; Energy; Entertainment; IT and communications; Medical; Neuroscience; Military; Outer space; Robotics; Transport: https://en.wikipedia.org/wiki/List_of_emerging_techno.. As knowledge and intelligence surpass capital, labor, and raw materials as the dominant economic resource, smart high technologies are also starting to reflect this paradigm shift.  • Intelligent Technologies are rapidly shifting from centralized hierarchies to distributed networks. • Nowadays knowledge and intelligence do not reside in a super-mind, super-book, or super-database, but in complex networks of humans and complex systems, or smart cyber-physical systems integrating human systems. • https://www.slideshare.net/ashabook/encyclopedic-inte.. https://vk.com/id403362847https://vk.com/id403362847 • https://https://www.amazon.com/Artificial-Superintelligence-Azamat-Abdoullaev/dp/9963842100www.amazon.com/Artificial-Superintelligence-Azamat-Abdoullaev/dp/9963842100
  11. 11. Encyclopedic Cyber-Physical Intelligence, or ASI:Encyclopedic Cyber-Physical Intelligence, or ASI: GlobalGlobal Ontology, Social Intelligence, AGI and MLOntology, Social Intelligence, AGI and ML • Superhuman or transhuman minds could be reached by intelligence amplification ofSuperhuman or transhuman minds could be reached by intelligence amplification of human brains and/or artificial intelligence.human brains and/or artificial intelligence. • The intelligence augmentation tools include bioengineering, genetic engineering, smartThe intelligence augmentation tools include bioengineering, genetic engineering, smart drugs, AI assistants, direct brain–computer interfaces and mind uploading.drugs, AI assistants, direct brain–computer interfaces and mind uploading. • Seed AI, a type of artificial intelligence, capable of recursive self-improving hardware,Seed AI, a type of artificial intelligence, capable of recursive self-improving hardware, software, and infrastructure on its own.software, and infrastructure on its own. • Having improved itself, it would become better at improving itself, potentially leading toHaving improved itself, it would become better at improving itself, potentially leading to an exponential increase in intelligence, a technological singularity.an exponential increase in intelligence, a technological singularity. • Seed AI is a significant part of the technological singularity: the development of seed AISeed AI is a significant part of the technological singularity: the development of seed AI will rapidly yield ever-smarter intelligence (via bootstrapping technique to iterativelywill rapidly yield ever-smarter intelligence (via bootstrapping technique to iteratively improve its performance) and thus a new era.improve its performance) and thus a new era. • The intelligence explosion is a possible outcome of humanity buildingThe intelligence explosion is a possible outcome of humanity building artificial general intelligence (AGI)artificial general intelligence (AGI).. • AGI being capable of recursive self-improvement is to lead to rapid emergence of ASIAGI being capable of recursive self-improvement is to lead to rapid emergence of ASI (artificial superintelligence), or Encyclopedic Cyber-Physical Intelligence.(artificial superintelligence), or Encyclopedic Cyber-Physical Intelligence. • https://en.wikipedia.org/wiki/Intelligence_explosionhttps://en.wikipedia.org/wiki/Intelligence_explosion • The principal components of ASI, asThe principal components of ASI, as Encyclopedic Cyber-Physical IntelligenceEncyclopedic Cyber-Physical Intelligence, are:, are: • Global Ontology (master schema of the world), Natural Intelligence (collective humanGlobal Ontology (master schema of the world), Natural Intelligence (collective human wisdom), AGI (artificial general intelligence) and ML (deep machine learning)wisdom), AGI (artificial general intelligence) and ML (deep machine learning) • https://https://www.aaai.org/Papers/Workshops/2002/WS-02-11/WS02-11-004.pdfwww.aaai.org/Papers/Workshops/2002/WS-02-11/WS02-11-004.pdf
  12. 12. Encyclopedic AI: a new AI paradigmEncyclopedic AI: a new AI paradigm • ““Artificial Intelligence is colossally hyped these days, but the dirty little secret is that it still has a long, long way toArtificial Intelligence is colossally hyped these days, but the dirty little secret is that it still has a long, long way to go. Sure, A.I. systems have mastered an array of games, from chess and Go to “Jeopardy” and poker, but thego. Sure, A.I. systems have mastered an array of games, from chess and Go to “Jeopardy” and poker, but the technology continues to struggle in the real world. Robots fall over while opening doors, prototype driverless carstechnology continues to struggle in the real world. Robots fall over while opening doors, prototype driverless cars frequently need human intervention, and nobody has yet designed a machine that can read reliably at the level of afrequently need human intervention, and nobody has yet designed a machine that can read reliably at the level of a sixth grader, let alone a college student. Computers that can educate themselves — a mark of true intelligence —sixth grader, let alone a college student. Computers that can educate themselves — a mark of true intelligence — remain a dream.remain a dream. • Even the trendy technique of “deep learning,” which uses artificial neural networks to discern complex statisticalEven the trendy technique of “deep learning,” which uses artificial neural networks to discern complex statistical correlations in huge amounts of data, often comes up short.correlations in huge amounts of data, often comes up short. • To get computers to think like humans, we need a new A.I. paradigm, one that places “top down” and “bottomTo get computers to think like humans, we need a new A.I. paradigm, one that places “top down” and “bottom up” knowledge on equal footing.up” knowledge on equal footing. • Bottom-up knowledge is the kind of raw information we get directly from our senses, like patterns of light falling onBottom-up knowledge is the kind of raw information we get directly from our senses, like patterns of light falling on our retina.our retina. • Top-down knowledge comprises cognitive models of the world and how it works.Top-down knowledge comprises cognitive models of the world and how it works. • Deep learning is very good at bottom-up knowledge, like discerning which patterns of pixels correspond to goldenDeep learning is very good at bottom-up knowledge, like discerning which patterns of pixels correspond to golden retrievers as opposed to Labradors. But it is no use when it comes to top-down knowledge.retrievers as opposed to Labradors. But it is no use when it comes to top-down knowledge. • To a deep-learning system, there is no difference between the reflection and the real thing, because the system lacks aTo a deep-learning system, there is no difference between the reflection and the real thing, because the system lacks a theory of the world and how it works.theory of the world and how it works. • Integrating that sort of knowledge of the world may be the next great hurdle in A.I., a prerequisite to granderIntegrating that sort of knowledge of the world may be the next great hurdle in A.I., a prerequisite to grander projects like using A.I. to advance medicine and scientific understanding.projects like using A.I. to advance medicine and scientific understanding. • Artificial Intelligence Is Stuck. Here’s How to Move It Forward.Artificial Intelligence Is Stuck. Here’s How to Move It Forward. https://www.nytimes.com/201https://www.nytimes.com/201......
  13. 13. GLOBAL TRENDS AND DISRUPTIVE AIGLOBAL TRENDS AND DISRUPTIVE AI TECHNOLOGIESTECHNOLOGIES Global IT-Enabled TrendsGlobal IT-Enabled Trends • Artificial General IntelligenceArtificial General Intelligence • Quantum Artificial IntelligenceQuantum Artificial Intelligence • Superintelligent Q-RobotsSuperintelligent Q-Robots • Encyclopedic Deep IntelligenceEncyclopedic Deep Intelligence • Big Science and TechnologyBig Science and Technology • World Knowledge GraphWorld Knowledge Graph • Smart Web SearchSmart Web Search • Internet of EverythingInternet of Everything • Smart InfrastructureSmart Infrastructure • Smart IndustrySmart Industry • Intelligent CitiesIntelligent Cities • Smart GovernmentSmart Government • Smart SpaceSmart Space • Smart WorldSmart World IT-Enabled Disruptive TechnologiesIT-Enabled Disruptive Technologies • A Power Set of the Smart WorldA Power Set of the Smart World Emerging TechnologiesEmerging Technologies • {(Smart Mobile Internet and Wireless i-Web,{(Smart Mobile Internet and Wireless i-Web, • Knowledge Work Automation,Knowledge Work Automation, • the Internet of Things or M2M Internet,the Internet of Things or M2M Internet, • i-Cloud Technology,i-Cloud Technology, • i-Robotics,i-Robotics, • i-Vehicles,i-Vehicles, • Smart devices, Smart agents,Smart devices, Smart agents, • Deep learning agents, Semantic machinesDeep learning agents, Semantic machines • NG Genomics,NG Genomics, • Energy Storage,Energy Storage, • Additive Manufacturing or 3D Printing,Additive Manufacturing or 3D Printing, • Advanced Materials,Advanced Materials, • Advanced Oil and Gas Exploration andAdvanced Oil and Gas Exploration and Recovery,Recovery, • Renewable Energy Technologies),…}Renewable Energy Technologies),…}
  14. 14. The Future I-World:The Future I-World: Smart Cyber-Physical SystemsSmart Cyber-Physical Systems • The Future AI World is to emerge as a global socio-technological ecosystem, worldwide distributedThe Future AI World is to emerge as a global socio-technological ecosystem, worldwide distributed cyber-physical networks, integrating both the earth-human systems and sophisticated futurecyber-physical networks, integrating both the earth-human systems and sophisticated future technological systems:technological systems: • machine intelligence: machine learning, deep learning techniques, NLP and robotics,machine intelligence: machine learning, deep learning techniques, NLP and robotics, • STUPID weak narrow intelligence, IBM's Watson supercomputer, expert systems and the self-drivingSTUPID weak narrow intelligence, IBM's Watson supercomputer, expert systems and the self-driving car, IoT technologies, drone-delivery services, and other advanced applications.car, IoT technologies, drone-delivery services, and other advanced applications. • SMART strong encyclopedic intelligence, artificial general intelligenceSMART strong encyclopedic intelligence, artificial general intelligence with comprehensive knowledge and cognitive computingwith comprehensive knowledge and cognitive computing capabilitiescapabilities,, • the internet of everything, future internet,the internet of everything, future internet, • smart web, intelligent search engines,smart web, intelligent search engines, • intelligent transportation, grids, plants,intelligent transportation, grids, plants, • intelligent industries, including public sector and utilities, agriculture, manufacturing, oil and gas,intelligent industries, including public sector and utilities, agriculture, manufacturing, oil and gas, mining, telecommunications, technology, media, healthcare, and pharmaceuticals,mining, telecommunications, technology, media, healthcare, and pharmaceuticals, • intelligent communities, smart cities, intelligent nations and I-World.intelligent communities, smart cities, intelligent nations and I-World. • Humans are to be integrated in the globally distributed smart cyber-physical ecosystems as keyHumans are to be integrated in the globally distributed smart cyber-physical ecosystems as key elements, enhancing enormously their powers, capacities, and capabilities, and to be driven by Deepelements, enhancing enormously their powers, capacities, and capabilities, and to be driven by Deep AI.AI. • AI is the science, engineering and art of developing various forms ofAI is the science, engineering and art of developing various forms of intelligent systems , as computer programs, intelligent agents/rational agents, smart machines, human beings, communities of human beings (such as firms or urban communities) or anything that is capable of goal directed behavior. (Russell & Norvig 2003) • Artificial Superintelligence • RealityReality, universal ontology, and knowledge systems: toward the intelligent world, universal ontology, and knowledge systems: toward the intelligent world. - Hershey; New York: IGI. - Hershey; New York: IGI Publishing, 2008.Publishing, 2008. • http://www.spsl.nsc.ru/Fulltext/CAT/2009/09-11-03/cont01f.htmhttp://www.spsl.nsc.ru/Fulltext/CAT/2009/09-11-03/cont01f.htm • http://www.worldxxi.com/http://www.worldxxi.com/
  15. 15. The Future I-Word: No existential riskThe Future I-Word: No existential risk • As to Stephen Hawking, “the development of full artificial intelligence could spell the end of the As to Stephen Hawking, “the development of full artificial intelligence could spell the end of the  human race. Once humans develop artificial intelligence, it will take off on its own and redesign itselfhuman race. Once humans develop artificial intelligence, it will take off on its own and redesign itself at an ever-increasing rate. Humans, who are limited by slow biological evolution, couldn't competeat an ever-increasing rate. Humans, who are limited by slow biological evolution, couldn't compete and would be superseded”.and would be superseded”. • Stanford’s One-Hundred Year Study of Artificial Intelligence includes loss of control of AI systems asStanford’s One-Hundred Year Study of Artificial Intelligence includes loss of control of AI systems as an area of study, specifically highlighting concerns over the possibility that … we could one day losean area of study, specifically highlighting concerns over the possibility that … we could one day lose control of AI systems via the rise of superintelligences that do not act in accordance with humancontrol of AI systems via the rise of superintelligences that do not act in accordance with human wishes — and that such powerful systems would threaten humanity. Are such dystopic outcomeswishes — and that such powerful systems would threaten humanity. Are such dystopic outcomes • possible? If so, how might these situations arise? . . . What kind of investments in research shouldpossible? If so, how might these situations arise? . . . What kind of investments in research should • be made to better understand and to address the possibility of the rise of a dangerousbe made to better understand and to address the possibility of the rise of a dangerous superintelligence or the occurrence of an “intelligence explosion”? (Horvitz 2014, ai100.stanford.edu).superintelligence or the occurrence of an “intelligence explosion”? (Horvitz 2014, ai100.stanford.edu). • A common concern about the development of artificial intelligence is the potential threat it could poseA common concern about the development of artificial intelligence is the potential threat it could pose to mankind.to mankind. • The opinion of experts within the field of artificial intelligence is mixed, both concerned andThe opinion of experts within the field of artificial intelligence is mixed, both concerned and unconcerned by risk from eventual superhumanly-capable AI.unconcerned by risk from eventual superhumanly-capable AI. • There is no reason for such concerns for real artificial general intelligence.There is no reason for such concerns for real artificial general intelligence. • Humans are mere to be integrated in the globally distributed AGI as key elements, enhancingHumans are mere to be integrated in the globally distributed AGI as key elements, enhancing enormously their powers, capacities, and capabilitiesenormously their powers, capacities, and capabilities • The Future AI World is emerging as globally distributed cyber-physical networks, integrating bothThe Future AI World is emerging as globally distributed cyber-physical networks, integrating both the natural ecosystems, social systems and sophisticated future technological systems,the natural ecosystems, social systems and sophisticated future technological systems, I-WorldI-World • Abdoullaev A. Reality, universal ontology, and knowledge systems: toward the intelligent world. -Abdoullaev A. Reality, universal ontology, and knowledge systems: toward the intelligent world. - Hershey; New York: IGI Publishing, 2008.Hershey; New York: IGI Publishing, 2008. • httphttp://://www.spsl.nsc.ru/Fulltext/CAT/2009/09-11-03/cont01f.htmwww.spsl.nsc.ru/Fulltext/CAT/2009/09-11-03/cont01f.htm • https://https://www.aaai.org/Papers/Workshops/2002/WS-02-11/WS02-11-004.pdfwww.aaai.org/Papers/Workshops/2002/WS-02-11/WS02-11-004.pdf • httphttp://www.worldxxi.com/://www.worldxxi.com/
  16. 16. •• What are strong AI and weak AI, AGI,What are strong AI and weak AI, AGI, ASI, and SuperIntelligence?ASI, and SuperIntelligence? • Strong AI, or Smart AI, means AI research aimed at general-purpose human-level AI.Strong AI, or Smart AI, means AI research aimed at general-purpose human-level AI. • Weak AI, or Stupid AI, is to mean AI research aimed at specific, narrow tasks such as speech recognition orWeak AI, or Stupid AI, is to mean AI research aimed at specific, narrow tasks such as speech recognition or checker playing.checker playing. • AGI stands for artificial general intelligence, a term intended to emphasize the ambitious goal of building general-AGI stands for artificial general intelligence, a term intended to emphasize the ambitious goal of building general- purpose intelligent systems, whose depth and breadth is comparable to the range of tasks that smartest humans canpurpose intelligent systems, whose depth and breadth is comparable to the range of tasks that smartest humans can address.address. • ASI stands for artificial superintelligence: AI that is substantially beyond human intelligence.ASI stands for artificial superintelligence: AI that is substantially beyond human intelligence. • Superintelligent systems are complex cyber-physical ecosystems capable of producing high-quality decisions andSuperintelligent systems are complex cyber-physical ecosystems capable of producing high-quality decisions and solving critical problems such as climate change, inequality, sustainable living, intelligent communities, emergingsolving critical problems such as climate change, inequality, sustainable living, intelligent communities, emerging technologies or groundbreaking smart systems.technologies or groundbreaking smart systems. • The idea of superintelligent machines may sound like the dystopian plot of "The Terminator" or "The Matrix,"The idea of superintelligent machines may sound like the dystopian plot of "The Terminator" or "The Matrix," but many experts say the idea technological singularity, the point at which technology will exceed human brainpowerbut many experts say the idea technological singularity, the point at which technology will exceed human brainpower and "superintelligence" will emerge, isn't far-fetched.and "superintelligence" will emerge, isn't far-fetched. • Some think the singularity — the point at which artificial intelligence overtakes human smarts — might happen inSome think the singularity — the point at which artificial intelligence overtakes human smarts — might happen in just 10-16 years.just 10-16 years. • Some believe in a utopian future, in which humans can transcend their physical limitations with the aid of machines.Some believe in a utopian future, in which humans can transcend their physical limitations with the aid of machines. But others think humans will eventually relinquish most of their abilities gradually becoming absorbed into artificialBut others think humans will eventually relinquish most of their abilities gradually becoming absorbed into artificial intelligence (AI)-based cyber-physical organisms, “meta-intelligence group-minds”. paving a path toward digitalintelligence (AI)-based cyber-physical organisms, “meta-intelligence group-minds”. paving a path toward digital immortality.immortality. Global Future 2045 International Congress in New York, June 15-16, 2013Global Future 2045 International Congress in New York, June 15-16, 2013
  17. 17. "Smart" AI vs "Dumb" AI: Sci-Fiction as Reality"Smart" AI vs "Dumb" AI: Sci-Fiction as Reality • "Dumb" AIs are a form of human artificial intelligence (an artificial construct that exhibits intelligence similar, and in some categories far superior, to a"Dumb" AIs are a form of human artificial intelligence (an artificial construct that exhibits intelligence similar, and in some categories far superior, to a sapient biological being).sapient biological being). • Human AIs include both "smart" and "dumb" varieties.Human AIs include both "smart" and "dumb" varieties. • Humanity developed the first-generation "smart" AIs in the mid-21st century.[correction, before 2030]Humanity developed the first-generation "smart" AIs in the mid-21st century.[correction, before 2030] • https://www.halopedia.org/Artificial_intelligencehttps://www.halopedia.org/Artificial_intelligence • Unlike more advanced "smart" AIs, these AIs are created using "traditional" programming methods rather than scanning human brains.Unlike more advanced "smart" AIs, these AIs are created using "traditional" programming methods rather than scanning human brains. • [Correction, ...not using a traditional computer algorithm of rule-based programming but rather mimicking human brains, as a computational model for[Correction, ...not using a traditional computer algorithm of rule-based programming but rather mimicking human brains, as a computational model for neural networks based on mathematics and numerical optimization algorithms, requiring too much training for real-world operation and implementingneural networks based on mathematics and numerical optimization algorithms, requiring too much training for real-world operation and implementing neural networks in circuitry with enormous CPU processing power and time. Besides, artificial neural networks have too many variations, as number ofneural networks in circuitry with enormous CPU processing power and time. Besides, artificial neural networks have too many variations, as number of units and layers, unit weights and topology, supervised or unsupervised.units and layers, unit weights and topology, supervised or unsupervised. • All is done with no idea how information is processed by biological neural networks, while misrepresenting simple statistical association (the basic functionAll is done with no idea how information is processed by biological neural networks, while misrepresenting simple statistical association (the basic function of ANNs) as learning or recognition;of ANNs) as learning or recognition; https://en.wikipedia.org/wiki/Artificial_neural_network#Criticismhttps://en.wikipedia.org/wiki/Artificial_neural_network#Criticism].]. • Consequently, they are more limited in their cognitive capabilities, being incapable of the capacity to feel, perceive, or experience subjectively, and cannotConsequently, they are more limited in their cognitive capabilities, being incapable of the capacity to feel, perceive, or experience subjectively, and cannot learn subjects outside of their specialized role.learn subjects outside of their specialized role. • They are able to recognize new situations and make pre-programmed decisions to account for unexpected events, but lack the creativity, intuition, andThey are able to recognize new situations and make pre-programmed decisions to account for unexpected events, but lack the creativity, intuition, and ingenuity of a smart AI.ingenuity of a smart AI. • Additionally, they cannot learn anything that is outside of their set limits of dynamic memory processing matrix. https://www.halopedia.org/Dumb_AIAdditionally, they cannot learn anything that is outside of their set limits of dynamic memory processing matrix. https://www.halopedia.org/Dumb_AI • "Smart" AI is the colloquial term in the United Nations Space Command for artificial intelligence (AI) which have no limitations in their dynamic"Smart" AI is the colloquial term in the United Nations Space Command for artificial intelligence (AI) which have no limitations in their dynamic memory-processor matrix, meaning they can not only be taught a vast wealth of information, but can learn and comprehend from their surroundings.memory-processor matrix, meaning they can not only be taught a vast wealth of information, but can learn and comprehend from their surroundings. • This is unlike "dumb" AIs who can only learn a limited set of topics and lack ingenuity.This is unlike "dumb" AIs who can only learn a limited set of topics and lack ingenuity. • https://www.halopedia.org/Smart_AIhttps://www.halopedia.org/Smart_AI • Encyclopedic AI models combines neural networks and symbolic approaches, for such a union better simulates the mechanisms of the human mind.Encyclopedic AI models combines neural networks and symbolic approaches, for such a union better simulates the mechanisms of the human mind. • Dumb Artificial Intelligence is exemplified with Deep Machine Learning AI, hyped to high heaven by global ICT companies, as Google, Microsoft,Dumb Artificial Intelligence is exemplified with Deep Machine Learning AI, hyped to high heaven by global ICT companies, as Google, Microsoft, Apple, Amazon and Facebook.Apple, Amazon and Facebook. • Together with humanity's greed and stupidity, Dumb Artificial Intelligence is humanity's "biggest existential threats".Together with humanity's greed and stupidity, Dumb Artificial Intelligence is humanity's "biggest existential threats".
  18. 18. STUPID Fake AI vs REAL Smart AI • STUPID Artificial intelligence (AI) is widely defined as “intelligence exhibited by machines”, as the study of "intelligent agents: any device that perceives its environment and takes actions that maximize its chance of success at some goal”. • AI is also the power of a digital computer or computer-controlled robot to perform the intellectual processes, characteristic of humans, such as intelligence, brain, mind and intellect, cognition and reasoning, discovering meaning, natural language understanding, deduction and induction, planning, gaming, and learning from experience. • The stupid, narrow-minded AI was announced at a workshop at Dartmouth College in 1956, where Allen Newell (CMU), Herbert Simon (CMU), John McCarthy (MIT), Marvin Minsky (MIT) and Arthur Samuel (IBM) became the founders and leaders of it. • As a result, most “stupid” AI's founders predictions and projects badly failed: "machines will be capable, within twenty years, of doing any work a man can do; "within a generation ... the problem of creating 'artificial intelligence' will substantially be solved”; the collapse of the Lisp Machine market. • The last wave of “stupid” AI is connected with statistical techniques (using multi-layer artificial neural networks, interconnected group of nodes, as the network of neurons in the human brain, known as deep learning), big data and faster computers enabled some advances in machine learning and perception. • Deep Blue beat Garry Kasparov in chess, IBM's question answering system, Watson, defeated the Jeopardy champions. AlphaGo-playing system beat a professional Go player . • The Kinect software technology (motion sensing input device or natural user interface) enabled gesture, face and voice recognition. • Deep learning was also applied by Google, Microsoft and Baidu for speech recognition by “intelligent” personal assistants in smartphones. • In all, examples of “stupid” AI include expert systems, autonomous vehicles (such as drones and self-driving cars), financial trading and banking, fraud and crime detection, medical diagnosis, creating art (such as poetry), proving mathematical theorems, playing games (such as Chess or Go), search engines (such as Google search), online assistants (such as Siri), image recognition in photographs, prediction of judicial decisions and targeting online advertisements, or spam filtering, https://en.wikipedia.org/wiki/Artificial_intelligence • Usually, in my Gmail account the most interesting and valuable messages I find as spammed, including Trump’s letters.
  19. 19. What is “Stupid” AI?What is “Stupid” AI? • It's the study of methods for making computers behave intelligently.It's the study of methods for making computers behave intelligently. • Roughly speaking, a computer is intelligent to the extent that it does the right thing rather than theRoughly speaking, a computer is intelligent to the extent that it does the right thing rather than the wrong thing. The right thing is whatever action is most likely to achieve the goal, or, in morewrong thing. The right thing is whatever action is most likely to achieve the goal, or, in more technical terms, the action that maximizes expected utility. AI includes tasks such as learning,technical terms, the action that maximizes expected utility. AI includes tasks such as learning, reasoning, planning, perception, language understanding, and robotics.reasoning, planning, perception, language understanding, and robotics. • Common misconceptionsCommon misconceptions • It's a specific technology. For example, in the 1980s and 1990s one often saw articles confusing AIIt's a specific technology. For example, in the 1980s and 1990s one often saw articles confusing AI with rule-based expert systems; in the 2010s, one sees AI being confused with many-layeredwith rule-based expert systems; in the 2010s, one sees AI being confused with many-layered convolutional neural networks. That's a bit like confusing physics with steam engines. The field of AIconvolutional neural networks. That's a bit like confusing physics with steam engines. The field of AI studies the general problem of creating intelligence in machines; it is not a specific technical productstudies the general problem of creating intelligence in machines; it is not a specific technical product arising from research on that problem.arising from research on that problem. • It's a specific class of technical approaches. For example, it's common to see authors identifying AIIt's a specific class of technical approaches. For example, it's common to see authors identifying AI with symbolic or logical approaches and contrasting AI with "other approaches" such as neural netswith symbolic or logical approaches and contrasting AI with "other approaches" such as neural nets or genetic programming. AI is not an approach, it's a problem. Any approach to the problem countsor genetic programming. AI is not an approach, it's a problem. Any approach to the problem counts as a contribution to AI.as a contribution to AI. • It's a particular community of researchers. This relates to the preceding misconception. Some authorsIt's a particular community of researchers. This relates to the preceding misconception. Some authors use the term "computational intelligence" to refer to a supposedly distinct community of researchersuse the term "computational intelligence" to refer to a supposedly distinct community of researchers using approaches such as neural networks, fuzzy logic, and genetic algorithms. This is veryusing approaches such as neural networks, fuzzy logic, and genetic algorithms. This is very unfortunate since it drives researchers to consider only approaches that are accepted within theirunfortunate since it drives researchers to consider only approaches that are accepted within their community rather than approaches that make sense.community rather than approaches that make sense. • AI is "just algorithms". This is not strictly a misconception, because algorithms (loosely defined asAI is "just algorithms". This is not strictly a misconception, because algorithms (loosely defined as programs) are of course what AI systems are made of, along with all other applications of computers.programs) are of course what AI systems are made of, along with all other applications of computers. However, the kinds of tasks addressed by AI systems tend to differ significantly from traditionalHowever, the kinds of tasks addressed by AI systems tend to differ significantly from traditional algorithmic tasks such as sorting lists of numbers or calculating square roots...algorithmic tasks such as sorting lists of numbers or calculating square roots... • http://people.eecs.berkeley.edu/~russell/temp/q-and-a.html
  20. 20. The Hype of Stupid AI:The Hype of Stupid AI: from the AI Winter to the newfrom the AI Winter to the new AI WinterAI Winter • Artificial intelligence researchers are acutely aware of the dangers of being overly simplistic and tooArtificial intelligence researchers are acutely aware of the dangers of being overly simplistic and too optimistic, known as the “A.I. winter” period of reduced funding and interest in artificial intelligenceoptimistic, known as the “A.I. winter” period of reduced funding and interest in artificial intelligence research.research. • The fifth-generation computer project followed with the USA Strategic Computing Initiative to buildThe fifth-generation computer project followed with the USA Strategic Computing Initiative to build artificial general intelligence failed to be achieved. Instead, the focus shifted on supercomputing forartificial general intelligence failed to be achieved. Instead, the focus shifted on supercomputing for large scale simulation, such as atomic bomb simulations, and producing advanced computinglarge scale simulation, such as atomic bomb simulations, and producing advanced computing machines and commercial applications, as “smart” consumer electronics, smartphones, smart TVs,machines and commercial applications, as “smart” consumer electronics, smartphones, smart TVs, etc.etc. • AI in the 2000s was disguised as informatics, machine learning, analytics, knowledge-based systems,AI in the 2000s was disguised as informatics, machine learning, analytics, knowledge-based systems, business rules management, cognitive systems, intelligent systems, intelligent agents orbusiness rules management, cognitive systems, intelligent systems, intelligent agents or computational intelligence.computational intelligence. • Some AI technologies have achieved commercial success in a number of applications, such asSome AI technologies have achieved commercial success in a number of applications, such as machine translation, data mining, data analytics technology, industrial robotics, logistics, speechmachine translation, data mining, data analytics technology, industrial robotics, logistics, speech recognition, banking software, medical diagnosis and Google's search engine.recognition, banking software, medical diagnosis and Google's search engine. • By 2010s artificial intelligence (and machine learning) again became widely used, well-funded andBy 2010s artificial intelligence (and machine learning) again became widely used, well-funded and many in the technology predict that it will soon succeed in creating machines with artificial generalmany in the technology predict that it will soon succeed in creating machines with artificial general intelligence, with the high possibility of the AI Spring.intelligence, with the high possibility of the AI Spring. • Still, there are flawed assumptions of AI research as in the past, and AI is headed in the wrongStill, there are flawed assumptions of AI research as in the past, and AI is headed in the wrong direction, first of all, because of its heavy reliance on statistical techniques, machine learningdirection, first of all, because of its heavy reliance on statistical techniques, machine learning practices, as comprised of symbolists, with origins in logic and philosophy; connectionists, frompractices, as comprised of symbolists, with origins in logic and philosophy; connectionists, from neuroscience; evolutionary biology; Bayesians, engaged with statistics and probability; andneuroscience; evolutionary biology; Bayesians, engaged with statistics and probability; and analogizers, with origins in psychology.analogizers, with origins in psychology.
  21. 21. Some “Stupid AI” projectsSome “Stupid AI” projects • The listing of narrow-minded AI specialized projects in: brain simulation, cognitive architectures, games, knowledge and reasoning, natural lan http://sourceforge.net/directory/os:windows/freshness:recently-updated/?q=artificial+intelligence • “Stupid” Big AI ROJECTS: • The Partnership on Artificial Intelligence to Benefit People and Society (Partnership on AI): “established to study and formulate best practices on AI technologies, to advance the public’s understanding of AI, and to serve as an open platform for discussion and engagement about AI and its influences on people and society”. • Grand Challenge 5 – Architecture of Brain and Mind, Integrating high level cognitive processes with brain mechanisms and functions in a working robot., a UK attempt to understand and model natural intelligence at various levels of abstraction, being embodied in a succession of robots. • Synthetic Environment for Analysis and Simulations (SEAS), a model of the real world used by Homeland security and the United States Department of Defense that uses simulation and AI to predict and evaluate future events and courses of action. • RESEARCH PRIORITIES FOR ROBUST AND BENEFICIAL ARTIFICIAL INTELLIGENCE. Real AI is not about “the construction of intelligent agents – systems that perceive and act in some environment”, the criterion for intelligence is related to statistical and economic notions of rationality — the ability to make good decisions, plans, or inferences, like presented by AI Open Letter - Future of Life Institute. https://futureoflife.org/ai-open-letter/ • Representing and simulating, understanding and managing, establishing and predicting all possible relationships among things in the world make the core of real AI. http://www.sciencecentral.com/site/4538138
  22. 22. ““Stupid AI” PRINCIPLESStupid AI” PRINCIPLES • Research Issues • 1) Research Goal: The goal of AI research should be to create not undirected intelligence, but beneficial intelligence. • 2) Research Funding: Investments in AI should be accompanied by funding for research on ensuring its beneficial use, including thorny questions in computer science, economics, law, ethics, and social studies, such as: • How can we make future AI systems highly robust, so that they do what we want without malfunctioning or getting hacked? • How can we grow our prosperity through automation while maintaining people’s resources and purpose? • How can we update our legal systems to be more fair and efficient, to keep pace with AI, and to manage the risks associated with AI? • What set of values should AI be aligned with, and what legal and ethical status should it have? • 3) Science-Policy Link: There should be constructive and healthy exchange between AI researchers and policy-makers. • 4) Research Culture: A culture of cooperation, trust, and transparency should be fostered among researchers and developers of AI. • 5) Race Avoidance: Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards. • Ethics and Values • 6) Safety: AI systems should be safe and secure throughout their operational lifetime, and verifiably so where applicable and feasible. • 7) Failure Transparency: If an AI system causes harm, it should be possible to ascertain why. • 8) Judicial Transparency: Any involvement by an autonomous system in judicial decision-making should provide a satisfactory explanation auditable by a competent human authority. • 9) Responsibility: Designers and builders of advanced AI systems are stakeholders in the moral implications of their use, misuse, and actions, with a responsibility and opportunity to shape those implications. • 10) Value Alignment: Highly autonomous AI systems should be designed so that their goals and behaviors can be assured to align with human values throughout their operation. • 11) Human Values: AI systems should be designed and operated so as to be compatible with ideals of human dignity, rights, freedoms, and cultural diversity. • 12) Personal Privacy: People should have the right to access, manage and control the data they generate, given AI systems’ power to analyze and utilize that data. • 13) Liberty and Privacy: The application of AI to personal data must not unreasonably curtail people’s real or perceived liberty. • 14) Shared Benefit: AI technologies should benefit and empower as many people as possible. • 15) Shared Prosperity: The economic prosperity created by AI should be shared broadly, to benefit all of humanity. • 16) Human Control: Humans should choose how and whether to delegate decisions to AI systems, to accomplish human-chosen objectives. • 17) Non-subversion: The power conferred by control of highly advanced AI systems should respect and improve, rather than subvert, the social and civic processes on which the health of society depends. • 18) AI Arms Race: An arms race in lethal autonomous weapons should be avoided. • Longer-term Issues • 19) Capability Caution: There being no consensus, we should avoid strong assumptions regarding upper limits on future AI capabilities. • 20) Importance: Advanced AI could represent a profound change in the history of life on Earth, and should be planned for and managed with commensurate care and resources. • 21) Risks: Risks posed by AI systems, especially catastrophic or existential risks, must be subject to planning and mitigation efforts commensurate with their expected impact. • 22) Recursive Self-Improvement: AI systems designed to recursively self-improve or self-replicate in a manner that could lead to rapidly increasing quality or quantity must be subject to strict safety and control measures.
  23. 23. AI versus Machine learning : what's theAI versus Machine learning : what's the difference?difference? • AI and machine learning are related as a kind and its speciesAI and machine learning are related as a kind and its species • AI studies the general problem of creating intelligence in technologies, machines, societies, humans,AI studies the general problem of creating intelligence in technologies, machines, societies, humans, and any systems, physical, digital or cyber-physicaland any systems, physical, digital or cyber-physical • Narrowly, AI is a branch of computer science attempting to build machines capable of intelligentNarrowly, AI is a branch of computer science attempting to build machines capable of intelligent behaviour.behaviour. • Broadly, AI is the study of methods for making things, simple or complex, behave intelligently.Broadly, AI is the study of methods for making things, simple or complex, behave intelligently. • AI includes tasks such as perception, learning, cognition, thinking, reasoning, planning, languageAI includes tasks such as perception, learning, cognition, thinking, reasoning, planning, language understanding, goal-directed actions, or robotics.understanding, goal-directed actions, or robotics. • Common misconceptions:Common misconceptions: • It's a specific technology, one may see AI as being confused with many-layered convolutional neuralIt's a specific technology, one may see AI as being confused with many-layered convolutional neural networks thanks to the likes of Apple, Google, Amazon, and Facebook.networks thanks to the likes of Apple, Google, Amazon, and Facebook. • It's a specific class of technical approaches, it's common to identify AI with symbolic or logicalIt's a specific class of technical approaches, it's common to identify AI with symbolic or logical approaches and contrasting AI with neural nets or genetic programming.approaches and contrasting AI with neural nets or genetic programming. • It's a particular community of researchers using different approaches such as neural networks, fuzzyIt's a particular community of researchers using different approaches such as neural networks, fuzzy logic, and genetic algorithms.logic, and genetic algorithms. • AI is just algorithms as traditional algorithmic tasks as sorting lists of numbers or calculating squareAI is just algorithms as traditional algorithmic tasks as sorting lists of numbers or calculating square roots.roots. • AI will necessarily increase inequality by increased automation of work concentrating income andAI will necessarily increase inequality by increased automation of work concentrating income and wealth in the hands of fewer people.wealth in the hands of fewer people. • AI is necessarily dehumanizing. AI is misused by some to control humans, by surveillance, roboticAI is necessarily dehumanizing. AI is misused by some to control humans, by surveillance, robotic policing, automated "justice", or an AI-supported command-and-control economypolicing, automated "justice", or an AI-supported command-and-control economy
  24. 24. AI versus Machine learning : what's theAI versus Machine learning : what's the difference?difference? • Machine learning is the branch of AI that explores ways to get computers to improve theirMachine learning is the branch of AI that explores ways to get computers to improve their performance based on experience.performance based on experience. • Common misconceptionsCommon misconceptions • Machine learning is a new field that has largely replaced AI.Machine learning is a new field that has largely replaced AI. • Machines can't learn, they can only do what their programmers tell them to do.Machines can't learn, they can only do what their programmers tell them to do. • Deep learning is a particular form of machine learning that involves training neuralDeep learning is a particular form of machine learning that involves training neural networks with many layers of units. It has become very popular in tasks such as visualnetworks with many layers of units. It has become very popular in tasks such as visual object recognition and speech recognition for ML-powered virtual assistants.object recognition and speech recognition for ML-powered virtual assistants. • A neural network is a kind of computational system inspired by basic properties ofA neural network is a kind of computational system inspired by basic properties of biological neurons, composed of many individual units, each of which receives input frombiological neurons, composed of many individual units, each of which receives input from some units at a lower level and sends output to others of higher levels. Commonsome units at a lower level and sends output to others of higher levels. Common misconceptions: Neural networks are a new kind of computer; Neural networks work likemisconceptions: Neural networks are a new kind of computer; Neural networks work like brains.brains. • Common misconceptionsCommon misconceptions • Deep learning is a new field that has largely replaced machine learning. In fact, deepDeep learning is a new field that has largely replaced machine learning. In fact, deep learning has existed in the neural network community for over 20 years. Recent advanceslearning has existed in the neural network community for over 20 years. Recent advances are driven by minor improvements in algorithms and models and by the availability ofare driven by minor improvements in algorithms and models and by the availability of large data sets, big data, and powerful collections of computers.large data sets, big data, and powerful collections of computers.
  25. 25. Standard Stupid AI Conferences:Standard Stupid AI Conferences: MACHINE LEARNINGMACHINE LEARNING • MACHINE LEARNING • DRONES • NATURAL LANGUAGE PROCESSING • AI • SPEECH RECOGNITION • INDUSTRIAL AUTOMATION • PATTERN RECOGNITION • ROBOTICS • MACHINE INTELLIGENCE SUMMIT 28 - 29 JUNE 2017MACHINE INTELLIGENCE SUMMIT 28 - 29 JUNE 2017 • https://www.re-work.co/events/machine-intelligence-summit-amsterdam-2017/schedulehttps://www.re-work.co/events/machine-intelligence-summit-amsterdam-2017/schedule • Sample Workshop SessionsSample Workshop Sessions • Build real-world AI solutions using the latest technologies from Amazon Echo, IBM Watson, Google, Microsoft,Build real-world AI solutions using the latest technologies from Amazon Echo, IBM Watson, Google, Microsoft, and open source options.and open source options. • Predictive Customer/Lead Engagement – Really powerful use case for AI in operations. This demo highlights somePredictive Customer/Lead Engagement – Really powerful use case for AI in operations. This demo highlights some of IBM Watson's most useful APIs (Language Alchemy, Personality Insights). This functionality can also beof IBM Watson's most useful APIs (Language Alchemy, Personality Insights). This functionality can also be applied across a range of media: social media, email, and content comments.applied across a range of media: social media, email, and content comments. • Predictive Purchase Recommendations – Personalization is the name of the game these days and we dive into itPredictive Purchase Recommendations – Personalization is the name of the game these days and we dive into it heavily during this demo. As you learn how to improve sales and retention by providing uniquely personalizedheavily during this demo. As you learn how to improve sales and retention by providing uniquely personalized recommendations and experiences for your customer.recommendations and experiences for your customer. • Voice Control of IoT Devices – Voice interface combined with AI technology will make the complex queries easier.Voice Control of IoT Devices – Voice interface combined with AI technology will make the complex queries easier. See business applications for Amazon Echo devices.See business applications for Amazon Echo devices. • Image Recognition – An extremely powerful application for nearly every industry. See Google's current capabilitiesImage Recognition – An extremely powerful application for nearly every industry. See Google's current capabilities for facial recognition, emotion recognition, text recognition, damage identification, context awareness.for facial recognition, emotion recognition, text recognition, damage identification, context awareness. • https://gigaom.com/ai-workshophttps://gigaom.com/ai-workshop//
  26. 26. SEAS: Sentient World SimulationSEAS: Sentient World Simulation • SEAS is currently being used by Homeland Security and the US Defense Department to simulate crises on the US mainland.   • SEAS "enables researchers and organizations to try out their models or techniques in a publicly known, realistically detailed environment.“ • It "is now capable of running real-time simulations for up to 62 nations, including Iraq, Afghanistan, and China.  • The simulations gobble up breaking news, census data, economic indicators, and climactic events in the real world, along with proprietary information such as military intelligence. The Iraq and Afghanistan computer models are the most highly developed and complex of the 62 available to JFCOM-J9.  • Each has about five million individual nodes representing things such as hospitals, mosques, pipelines, and people. • The Sentient World Simulation project (SWS) is to be based on SEAS and initiated by US Joint Forces Command. • The ultimate goal to be a "continuously running, continually updated mirror model of the real world that can be used to predict and evaluate future events and courses of action. • SWS will react to actual events that occur anywhere in the world and incorporate newly sensed data from the real world. • As the models influence each other and the shared synthetic environment, behaviors and trends emerge in the synthetic world as they do in the real world. • Analysis can be performed on the trends in the synthetic world to validate alternate worldviews. • Information can be easily displayed and readily transitioned from one focus to another using detailed modeling, such as engineering level modeling, to aggregated strategic, theater, or campaign-level modeling. • http://www.mgmt.purdue.edu/centers/perc/html/aboutperc/seaslabs/seaslabs.htm SEAS • http://www.theregister.co.uk/2007/06/23/sentient_worlds/ The Register] article "Sentient world: war games on the grandest sc ale" published June 23, 2007
  27. 27. The Partnership on “Stupid” AI: GoalsThe Partnership on “Stupid” AI: Goals • We are at an inflection point in the development and application of AI technologies. The upswing in AI competencies, fueled by data, computaWe are at an inflection point in the development and application of AI technologies. The upswing in AI competencies, fueled by data, computa • We designed the Partnership on AI, in part, so that we can invest more attention and effort on harnessing AI to contribute to solutions for somWe designed the Partnership on AI, in part, so that we can invest more attention and effort on harnessing AI to contribute to solutions for som • DEVELOP AND SHARE BEST PRACTICESDEVELOP AND SHARE BEST PRACTICES • Support research, discussions, identification, sharing, and recommendation of best practices in the research, development, testing, andSupport research, discussions, identification, sharing, and recommendation of best practices in the research, development, testing, and fielding of AI technologies. Address such areas as fairness and inclusivity, explanation and transparency, security and privacy,fielding of AI technologies. Address such areas as fairness and inclusivity, explanation and transparency, security and privacy, values and ethics, collaboration between people and AI systems, interoperability of systems, and of the trustworthiness, reliability,values and ethics, collaboration between people and AI systems, interoperability of systems, and of the trustworthiness, reliability, containment, safety, and robustness of the technology.containment, safety, and robustness of the technology. • PROVIDE AN OPEN AND INCLUSIVE PLATFORM FOR DISCUSSION AND ENGAGEMENTPROVIDE AN OPEN AND INCLUSIVE PLATFORM FOR DISCUSSION AND ENGAGEMENT • Create and support opportunities for AI researchers and key stakeholders, including people in technology, law, policy, government,Create and support opportunities for AI researchers and key stakeholders, including people in technology, law, policy, government, civil liberties, and the greater public, to communicate directly and openly with each other about relevant issues to AI and itscivil liberties, and the greater public, to communicate directly and openly with each other about relevant issues to AI and its influences on people and society. Ensure that key stakeholders have the knowledge, resources, and overall capacity to participateinfluences on people and society. Ensure that key stakeholders have the knowledge, resources, and overall capacity to participate fully.fully. • ADVANCE PUBLIC UNDERSTANDINGADVANCE PUBLIC UNDERSTANDING • Advance public understanding and awareness of AI by multiple constituencies, including writing and other communications on coreAdvance public understanding and awareness of AI by multiple constituencies, including writing and other communications on core technologies, potential benefits, and costs. Act as a trusted and expert point of contact as questions, concerns, and aspirations arisetechnologies, potential benefits, and costs. Act as a trusted and expert point of contact as questions, concerns, and aspirations arise from the public and others in the area of AI. Regularly update key constituents on the current state of AI progress.from the public and others in the area of AI. Regularly update key constituents on the current state of AI progress. • IDENTIFY AND FOSTER ASPIRATIONAL EFFORTS IN AI FOR SOCIALLY BENEFICIALIDENTIFY AND FOSTER ASPIRATIONAL EFFORTS IN AI FOR SOCIALLY BENEFICIAL PURPOSESPURPOSES • Seek out, support, celebrate, and highlight aspirational efforts in AI for socially benevolent applications. Identify areas of untappedSeek out, support, celebrate, and highlight aspirational efforts in AI for socially benevolent applications. Identify areas of untapped opportunity, including promising technologies and applications not being explored by academia and industry R&D.opportunity, including promising technologies and applications not being explored by academia and industry R&D. • Amazon, Apple,Amazon, Apple, AAAIAAAI,, DeepMindDeepMind, Facebook, Google, IBM, Microsoft,, Facebook, Google, IBM, Microsoft, OpenAIOpenAI
  28. 28. Smart OpenAI:Smart OpenAI: ML Artificial General IntelligenceML Artificial General Intelligence • OpenAI conducts fundamental, long-term research toward the creation of safe AGI.OpenAI conducts fundamental, long-term research toward the creation of safe AGI. • Discovering and enacting the path to safe artificial general intelligence.Discovering and enacting the path to safe artificial general intelligence. • Platforms by OpenAI • We're building platforms for developing and measuring agents which take action in simulated worlds. • Artificial general intelligence (AGI) will be the most significant technology ever created by humans. • OpenAI's mission is to build safe AGI, and ensure AGI's benefits are as widely and evenly distributed as possible. We expect AI technologies to be hugely impactful in the short term, but their impact will be outstripped by that of the first AGIs. • We're a non-profit research company. Our full-time staff of 60 researchers and engineers is dedicated to working towards our mission regardless of the opportunities for selfish gain which arise along the way. • We focus on long-term research, working on problems that require us to make fundamental advances in AI capabilities. By being at the forefront of the field, we can influence the conditions under which AGI is created. As Alan Kay said, "The best way to predict the future is to invent it." • We publish at top machine learning conferences, open-source software tools for accelerating AI research, and release blog posts to communicate our research. We will not keep information private for private benefit, but in the long term, we expect to create formal processes for keeping technologies private when there are safety concerns. https://openai.comhttps://openai.com//
  29. 29. Apple AI:Apple AI: ML AIML AI • Apple is working on the same problems as many other companies exploring machine learning:Apple is working on the same problems as many other companies exploring machine learning: Neural Information Processing Systems, recognizing and processing images, predicting userNeural Information Processing Systems, recognizing and processing images, predicting user behavior and events in the physical world, modeling language for use in personal assistants, andbehavior and events in the physical world, modeling language for use in personal assistants, and how to deal with uncertainty when an algorithm can’t make a high-confidence decision.how to deal with uncertainty when an algorithm can’t make a high-confidence decision.
  30. 30. Amazon AI:Amazon AI: Bringing powerful artificial intelligence to allBringing powerful artificial intelligence to all developersdevelopers • Amazon AI services bring natural language understanding (NLU), automatic speech recognition (ASR), visual search and imageAmazon AI services bring natural language understanding (NLU), automatic speech recognition (ASR), visual search and image recognition, text-to-speech (TTS), and machine learning (ML) technologies within the reach of every developer. Based on the samerecognition, text-to-speech (TTS), and machine learning (ML) technologies within the reach of every developer. Based on the same proven, highly scalable products and services built by the thousands of deep learning and machine learning experts across Amazon,proven, highly scalable products and services built by the thousands of deep learning and machine learning experts across Amazon, Amazon AI services provide high-quality, high-accuracy AI capabilities that are scalable and cost-effective.Amazon AI services provide high-quality, high-accuracy AI capabilities that are scalable and cost-effective. • In addition, the AWS Deep Learning AMI provides a way for AI developers and researchers to quickly and easily begin usingIn addition, the AWS Deep Learning AMI provides a way for AI developers and researchers to quickly and easily begin using any of the major deep learning frameworks to train sophisticated, custom AI models; experiment with new algorithms; and learnany of the major deep learning frameworks to train sophisticated, custom AI models; experiment with new algorithms; and learn new deep learning skills and techniques on AWS’ massive compute infrastructure.new deep learning skills and techniques on AWS’ massive compute infrastructure. • Our approach to AI is made up of three main layers that sit on top of the AWS infrastructure:Our approach to AI is made up of three main layers that sit on top of the AWS infrastructure: • AI Services: At the highest level, for developers who want access to AI technologies without having to train or develop their ownAI Services: At the highest level, for developers who want access to AI technologies without having to train or develop their own ML models, AWS provides a collection of highly scalable pre-trained and pre-tuned managed AI Services that do not require anyML models, AWS provides a collection of highly scalable pre-trained and pre-tuned managed AI Services that do not require any previous artificial intelligence or deep learning knowledge in order to get started.previous artificial intelligence or deep learning knowledge in order to get started. • AI Platforms: For customers with existing data who want to focus on building custom inference models, we provide a set of AIAI Platforms: For customers with existing data who want to focus on building custom inference models, we provide a set of AI platforms which remove the undifferentiated heavy lifting associated with deploying and managing AI training and model hosting.platforms which remove the undifferentiated heavy lifting associated with deploying and managing AI training and model hosting. The Amazon Machine Learning service allows you to train custom machine learning models using your own data, withoutThe Amazon Machine Learning service allows you to train custom machine learning models using your own data, without requiring deep machine learning skills or expertise. In addition, Apache Spark on Amazon EMR includes MLlib for scalablerequiring deep machine learning skills or expertise. In addition, Apache Spark on Amazon EMR includes MLlib for scalable machine learning algorithms.machine learning algorithms. • AI Frameworks: Finally, we support all major AI frameworks for researchers and data scientists who want to build sophisticatedAI Frameworks: Finally, we support all major AI frameworks for researchers and data scientists who want to build sophisticated and cutting-edge intelligent systems. Frameworks such as Apache MXNet, TensorFlow, Caffe, Theano, Torch, Keras, andand cutting-edge intelligent systems. Frameworks such as Apache MXNet, TensorFlow, Caffe, Theano, Torch, Keras, and CNTK provide flexible programming models for training custom models at scale. The AWS Deep Learning AMI, available forCNTK provide flexible programming models for training custom models at scale. The AWS Deep Learning AMI, available for both Amazon Linux and Ubuntu, provides all of these frameworks pre-installed and configured on a convenient Amazonboth Amazon Linux and Ubuntu, provides all of these frameworks pre-installed and configured on a convenient Amazon Machine Image to help you get started quickly and easily.Machine Image to help you get started quickly and easily. • AI Infrastructure: Deep learning frameworks, like Apache MXNet, use neural nets, which involve the process of multiplying a lotAI Infrastructure: Deep learning frameworks, like Apache MXNet, use neural nets, which involve the process of multiplying a lot of matrices.of matrices. https://aws.amazon.com/amazon-ai/https://aws.amazon.com/amazon-ai/
  31. 31. Microsoft Artificial IntelligenceMicrosoft Artificial Intelligence • Pursuing computing advances to create intelligent machines that complement human reasoning to augment and enrich our experiencePursuing computing advances to create intelligent machines that complement human reasoning to augment and enrich our experience and competencies.and competencies. • At Microsoft, researchers in artificial intelligence are harnessing the explosion of digital data and computational power withAt Microsoft, researchers in artificial intelligence are harnessing the explosion of digital data and computational power with advanced algorithms to enable collaborative and natural interactions between people and machines that extend the human ability toadvanced algorithms to enable collaborative and natural interactions between people and machines that extend the human ability to sense, learn and understand. The research infuses computers, materials and systems with the ability to reason, communicate andsense, learn and understand. The research infuses computers, materials and systems with the ability to reason, communicate and perform with humanlike skill and agility.perform with humanlike skill and agility. • Microsoft’s deep investments in the field are advancing the state of the art in machine intelligence and perception, enabling computersMicrosoft’s deep investments in the field are advancing the state of the art in machine intelligence and perception, enabling computers that understand what they see, communicate in natural language, answer complex questions and interact with their environment.that understand what they see, communicate in natural language, answer complex questions and interact with their environment. • In addition, the company’s researchers are thought leaders on the ethics and societal impacts of intelligent technologies.In addition, the company’s researchers are thought leaders on the ethics and societal impacts of intelligent technologies. • The research, tools and services that result from this investment are woven into existing and new products and, at the same time,The research, tools and services that result from this investment are woven into existing and new products and, at the same time, made open and accessible to the broader community in a bid to accelerate innovation, democratize AI and solve the world’s mostmade open and accessible to the broader community in a bid to accelerate innovation, democratize AI and solve the world’s most pressing challenges.pressing challenges. • https://www.microsoft.com/en-us/research/research-area/artificial-intelligence/https://www.microsoft.com/en-us/research/research-area/artificial-intelligence/ • We’re taking a four-pronged approach to how we think about Microsoft AI and how we pursue this bold ambition to democratizeWe’re taking a four-pronged approach to how we think about Microsoft AI and how we pursue this bold ambition to democratize AI for all:AI for all: • We’re going to harness artificial intelligence to fundamentally change how we interact with the ambient computing, the agents, in ourWe’re going to harness artificial intelligence to fundamentally change how we interact with the ambient computing, the agents, in our lives.lives. • We’re going to infuse every application that we interact with, on any device, at any point in time, with intelligence.We’re going to infuse every application that we interact with, on any device, at any point in time, with intelligence. • We’ll make these same intelligent capabilities that are infused in our own apps — the cognitive capabilities — available to everyWe’ll make these same intelligent capabilities that are infused in our own apps — the cognitive capabilities — available to every application developer in the world.application developer in the world. • We’re building the world’s most powerful AI supercomputer and making it available to anyone, via the cloud, to enable all toWe’re building the world’s most powerful AI supercomputer and making it available to anyone, via the cloud, to enable all to harness its power and tackle AI challenges, large and small.harness its power and tackle AI challenges, large and small. • Read more atRead more at https://news.microsoft.com/features/democratizing-ai/#https://news.microsoft.com/features/democratizing-ai/#RI0Od0zBQFJ4uKwK.99RI0Od0zBQFJ4uKwK.99
  32. 32. The Facebook AI:The Facebook AI: 10-year road map10-year road map
  33. 33. Google AI: Google BrainGoogle AI: Google Brain • The mission of the Brain team is "Make machines intelligent. Improve people's lives."The mission of the Brain team is "Make machines intelligent. Improve people's lives." We work to make machines intelligent byWe work to make machines intelligent by focusing on highly flexible models that learnfocusing on highly flexible models that learn their own features, end-to-end, and maketheir own features, end-to-end, and make efficient use of data and computation.efficient use of data and computation. • This approach fits into the broader DeepThis approach fits into the broader Deep Learning subfield of ML and ensures our workLearning subfield of ML and ensures our work will ultimately make a difference for problemswill ultimately make a difference for problems of practical importance. Furthermore, ourof practical importance. Furthermore, our expertise in systems complements thisexpertise in systems complements this approach by allowing us to build tools toapproach by allowing us to build tools to accelerate ML research and unlock itsaccelerate ML research and unlock its practical value for the world.practical value for the world. • By virtue of being part of Google andBy virtue of being part of Google and Alphabet, the Google Brain team hasAlphabet, the Google Brain team has resources and access to projects impossible toresources and access to projects impossible to find elsewhere. Our broad and fundamentalfind elsewhere. Our broad and fundamental research goals allow us to collaborate closelyresearch goals allow us to collaborate closely with and contribute uniquely to manywith and contribute uniquely to many different product teams across the company.different product teams across the company. As part of these collaborations, product teamsAs part of these collaborations, product teams have successfully deployed technology fromhave successfully deployed technology from Google Brain in numerous products.Google Brain in numerous products. • The project's technology is currently used in:The project's technology is currently used in: • Android Operating System's speech recognition system,  • Google Search, • speech recognition systems,  • Google Photos,  • Google Maps and Street View,  • Google Translate, • Google Cloud’s Machine Learning offerings ,  • YouTube,  • Gmail,  • DeepMind’s AlphaGo system, • TensorFlow: An open-source software library for Machine Intelligence • https:// research.google.com/pubs/MachineIntelligenc • https://research.google.com/teams/brain /
  34. 34. DeepMind AIDeepMind AI • DeepMind's scientific mission is to push the boundaries of AI, developing systems thatDeepMind's scientific mission is to push the boundaries of AI, developing systems that can learn to solve any complex problem without needing to be taught how. To achievecan learn to solve any complex problem without needing to be taught how. To achieve this, we work from the premise that AI needs to be general. Agents should operate acrossthis, we work from the premise that AI needs to be general. Agents should operate across a wide range of tasks and be able to automatically adapt to changing circumstances.a wide range of tasks and be able to automatically adapt to changing circumstances. • That is, they should not be pre-programmed, but rather, able to learn automatically fromThat is, they should not be pre-programmed, but rather, able to learn automatically from their raw inputs and reward signals from the environment.their raw inputs and reward signals from the environment. • There are two parts to this research program:There are two parts to this research program: • (1) designing ever-more intelligent agents capable of more-and-more sophisticated(1) designing ever-more intelligent agents capable of more-and-more sophisticated cognitive skills, and (2) building increasingly complex environments where agents can becognitive skills, and (2) building increasingly complex environments where agents can be trained and evaluated.trained and evaluated. • https://deepmind.com/blog/open-sourcing-deepmind-lab/https://deepmind.com/blog/open-sourcing-deepmind-lab/ • DeepMind LabDeepMind Lab is a first-person 3D game platform designed for research and developmentis a first-person 3D game platform designed for research and development of general artificial intelligence and machine learning systems.of general artificial intelligence and machine learning systems. • DeepMind Lab can be used to study how autonomous artificial agents may learn complexDeepMind Lab can be used to study how autonomous artificial agents may learn complex tasks in large, partially observed, and visually diverse worlds.tasks in large, partially observed, and visually diverse worlds. • DeepMind Lab has a simple and flexible API enabling creative task-designs and novel AI-DeepMind Lab has a simple and flexible API enabling creative task-designs and novel AI- designs to be explored and quickly iterated upon.designs to be explored and quickly iterated upon. • It is powered by a fast and widely recognised game engine, and tailored for effective useIt is powered by a fast and widely recognised game engine, and tailored for effective use by the research community.by the research community.
  35. 35. Grand Challenge 5:Grand Challenge 5: The Architecture of Brain and Mind Integrating Low-Level Neuronal BrainThe Architecture of Brain and Mind Integrating Low-Level Neuronal Brain Processes with High-Level Cognitive Behaviours, in a Functioning RobotProcesses with High-Level Cognitive Behaviours, in a Functioning Robot • Biological information processing systems produced by evolution still far outstrip both our understanding and our practicalBiological information processing systems produced by evolution still far outstrip both our understanding and our practical achievements: there are deep gaps in our theories and in our engineering capabilities.achievements: there are deep gaps in our theories and in our engineering capabilities. • In the hope of reducing both gaps we shall look closely at two of the most impressive products of evolution: human brains andIn the hope of reducing both gaps we shall look closely at two of the most impressive products of evolution: human brains and human minds – and attempt to construct a combined vision of how they work demonstrated in a robot that goes far beyond whathuman minds – and attempt to construct a combined vision of how they work demonstrated in a robot that goes far beyond what current systems can do:current systems can do: • •• Brains, the contents of our skulls, are composed of extraordinarily intricate, self-organising, physical structures, performing manyBrains, the contents of our skulls, are composed of extraordinarily intricate, self-organising, physical structures, performing many tasks in parallel at many scales, from individual molecules to large collections of cooperating neurones or chemical transport systems.tasks in parallel at many scales, from individual molecules to large collections of cooperating neurones or chemical transport systems. • •• Minds are more abstract and contain ideas, perceptions, thoughts, feelings, memories, mathematical knowledge, motives, moods,Minds are more abstract and contain ideas, perceptions, thoughts, feelings, memories, mathematical knowledge, motives, moods, emotions, reasoning processes, decisions, motor control skills and other things that cannot be seen by opening up skulls. Yet theiremotions, reasoning processes, decisions, motor control skills and other things that cannot be seen by opening up skulls. Yet their existence and their power to do things depend on all the ‘wetware’ components that make up brains.existence and their power to do things depend on all the ‘wetware’ components that make up brains. • The end goal: a fully functional robot implemented using an artificial brain built out of componentsThe end goal: a fully functional robot implemented using an artificial brain built out of components • simulating low level functions of animal brains will not be achieved in the foreseeable future. Butsimulating low level functions of animal brains will not be achieved in the foreseeable future. But • •• a robot using more abstract models of higher level brain functions and combining many kinds of functionality,a robot using more abstract models of higher level brain functions and combining many kinds of functionality, • along withalong with • •• parallel demonstrations of the plausibility of the claim that those brain functions could beparallel demonstrations of the plausibility of the claim that those brain functions could be • implemented in mechanisms simulating very low level brain mechanisms,implemented in mechanisms simulating very low level brain mechanisms, • could be achieved in 15 to 20 years.could be achieved in 15 to 20 years. • http://www.nesc.ac.uk/esi/events/Grand_Challenges/proposals/ArchitectureOfBrainAndMind.pdfhttp://www.nesc.ac.uk/esi/events/Grand_Challenges/proposals/ArchitectureOfBrainAndMind.pdf
  36. 36. Machine Learning Types: Markov chainsMachine Learning Types: Markov chains • Machine learning tasks are typically classified into three broad categories, depending on the nature of the learning "signal" or "feedback" available to a learning system. These are • Supervised learning: The computer is presented with example inputs and their desired outputs, given by a "teacher", and the goal is to learn a general rule that maps inputs to outputs. It is the machine learning task of inferring a function from labeled training data. • Unsupervised learning: No labels are given to the learning algorithm, leaving it on its own to find structure in its input. Unsupervised learning can be a goal in itself (discovering hidden patterns in data) or a means towards an end (feature learning). • Reinforcement learning: A computer program interacts with a dynamic environment typically formulated as a Markov decision process (MDP) in which it must perform a certain goal (such as driving a vehicle or playing a game against an opponent. • Markov chains - stochastic processes that satisfying the Markov property ("memorylessness"), making predictionsMarkov chains - stochastic processes that satisfying the Markov property ("memorylessness"), making predictions for the future of the process based solely on its present state. A Markov chain is a type of Markov process that hasfor the future of the process based solely on its present state. A Markov chain is a type of Markov process that has either discrete state space or discrete index set (often representing time).either discrete state space or discrete index set (often representing time). • Markov chains have many applications as statistical models of real-world processes, such as studying cruise controlMarkov chains have many applications as statistical models of real-world processes, such as studying cruise control systems in motor vehicles, queues or lines of customers arriving at an airport, exchange rates of currencies, storagesystems in motor vehicles, queues or lines of customers arriving at an airport, exchange rates of currencies, storage systems such as dams, and population growths of certain animal species. The algorithm known as PageRank, whichsystems such as dams, and population growths of certain animal species. The algorithm known as PageRank, which was originally proposed for the internet search engine Google, is based on a Markov process.was originally proposed for the internet search engine Google, is based on a Markov process.

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