http://www.winterintelligence.org/ Winter Intelligence 2012 Oxford University

Video thanks to Adam Ford, http://www.youtube.com/user/TheRationalFuture

Extended Abstract: The gradually increasing sophistication of semi-autonomous and autonomous robots and virtual agents has led some scholars to propose constraining these systems’ behaviors with programmed ethical principles (“machine ethics”). While impressive machine ethics theories and prototypes have been developed for narrow domains, several factors will likely prevent machine ethics from ensuring positive outcomes from advanced, cross-domain autonomous systems. This paper critically reviews existing approaches to machine ethics in general and Friendly AI in particular (an approach to constraining the actions of future self-improving AI systems favored by the Singularity Institute for Artificial Intelligence), finding that while such approaches may be useful for guiding the behavior of some semi-autonomous and autonomous systems in some contexts, these projects cannot succeed in guaranteeing ethical behavior and may introduce new risks inadvertently. Moreover, while some incarnation of machine ethics may be necessary for ensuring positive social outcomes from artificial intelligence and robotics, it will not be sufficient, since other social and technical measures will also be critically important for realizing positive outcomes from these emerging technologies.
Building an ethical autonomous machine requires a decision on the part of the system designer as to which ethical framework to implement. Unfortunately, there are currently no fully-articulated moral theories that can plausibly be realized in an autonomous system, in part because the moral intuitions that ethicists attempt to systematize are not, in fact, consistent across all domains. Unified ethical theories are all either too vague to be computationally tractable or vulnerable to compelling counter-examples, or both. [1,2] Recent neuroscience research suggests that, depending on the context of a given decision, we rely to varying extents on an intuitive, roughly deontological (means-based) moral system and on a more reflective, roughly consequentialist (ends-based) moral system, which in part explains the aforementioned tensions in moral philosophy. [3] While the normative significance of conflicting moral intuitions can be disputed, these findings at least have implications for the viability of building a machine whose moral system would be acceptable to most humans across all domains, particularly given the need for ensuring the internal consistency of a system’s programming. Should an unanticipated situation arise, or if the system were used outside its prescribed domain, negative consequences will likely result due to the inherent fragility of rule-based systems.
Moreover, the complex and uncertain relationship between actions and consequences in the world means that an autonomous system (or, indeed, a human) with an ethical framework that is (at least partially) consequentialist cannot be relied upon with full confidence in any non-trivial task domain, suggesting the practical need for context-appropriate heuristics and great caution in ensuring that moral decision-making in society does not become overly centralized.[4] The intrinsic complexity and uncertainty of the world, along with other constraints such as the inability to gather the necessary data, also doom approaches (such as Friendly AI) to derive a system’s utility function from extrapolation of humans’ preferences. There is also a risk that the logical implications derived from premises in a given ethical system may not be what humans working on machine ethics principles believe them to be (this is one of the categories of machine ethics risks highlighted in Isaac Asimov’s work[5]). In other words, machine ethicists are caught in a double-bind: they must either depend on rigid principles for addressing particular ethical issues, and thus risk catastrophic outcomes when those rules should in fact be broken[6], or they allow an autonomous system to reason from first principles or derive its utility function in an evolutionary fashion, and thereby risk the possibility that it will arrive at conclusions that the designer would not have initially consented to. Lastly, even breakthroughs in normative ethics would not ensure positive outcomes from the deployment of explicitly ethical autonomous systems. Several factors besides machine ethics proper — such as ensuring that autonomous systems are robust against hacking, developing appropriate social norms and policies for ensuring ethical behavior by those involved in developing and using autonomous systems, and the systemic risks that could be arise from dependence on ubiquitous intelligent machines — are briefly described and suggested as areas for further research in light of the intrinsic limitations of machine ethics.

By pairing the power of AI systems and human wisdom, scientists at Duke University hope to offer a tool for strengthening our moral capacities.

Learn more at http://diverseintelligences.com/.

Will Artificial Intelligence ever match the masterful leadership of an outstanding CEO, deeply moving writing of a great poet, or nurturing care of a hospital nurse?
Viktor Dörfler, Senior Lecturer at the University of Strathclyde Business School, who makes artificial intelligence and has interviewed 17 Nobel Laureates, takes the stand on inimitability of exceptional human performance. In his talk, Viktor contrasts the learning algorithms of Artificial Intelligence, with human learning, particularly with the learning journey of exceptionally high achievers. Viktor is a Senior Lecturer in Information & Knowledge Management and also holds a Visiting Professor position at the Business School of Zagreb University. He gained masters degrees in Mathematical Engineering, International Business Relations, Engineering Education and an MBA from Hungarian universities and holds a PhD from Strathclyde University. In his speech, Dr Dörfler will explore why artificial intelligence will never match up to human intuition based on his vast experience of learning from the nobel laureates and creating AI. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx

Princeton University researchers Arvind Narayanan, Aylin Caliskan and Joanna Bryson discuss their research on how human biases seep into artificial intelligence.

This video is about Artificial Intelligence & sophia robot Story in Hindi. Artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals.

What Elon Musk Think about Sofia Robot.

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First-order logic – also known as first-order predicate calculus and predicate logic – is a collection of formal systems used in mathematics, philosophy, linguistics, and computer science. First-order logic uses quantified variables over non-logical objects and allows the use of sentences that contain variables, so that rather than propositions such as Socrates is a man one can have expressions in the form “there exists X such that X is Socrates and X is a man” where there exists is a quantifier and X is a variable.This distinguishes it from propositional logic, which does not use quantifiers.

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14:00-14:20 Jes Frellsen, University of Cambridge Bayesian generalised ensemble Markov chain Monte Carlo
14:20-14:40 Adam Scibior, University of Cambridge Probabilistic programming with effect systems
14:40-15:00 Andy Gordon, Microsoft Research Fabular: Regression Formulas as Probabilistic Programming
15:00-15:20 John Hong, University of Cambridge Comparing Matrix Factorization algorithms on a level playing field

Discussion points:
– Progress in AI
– Media fear mongering with regard to AI
– The need for more conceptual progress in AI

Joscha Bach, Ph.D. is an AI researcher who worked and published about cognitive architectures, mental representation, emotion, social modeling, and multi-agent systems. He earned his Ph.D. in cognitive science from the University of Osnabrück, Germany, and has built computational models of motivated decision making, perception, categorization, and concept-formation. He is especially interested in the philosophy of AI and in the augmentation of the human mind.

Joscha has taught computer science, AI, and cognitive science at the Humboldt-University of Berlin and the Institute for Cognitive Science at Osnabrück. His book “Principles of Synthetic Intelligence” (Oxford University Press) is available on amazon now:
https://www.amazon.com/Principles-Synthetic-Intelligence-PSI-Architectures/dp/0195370678

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Videotherapy – Artificial Intelligence

Avengers: Age of Ultron

Music: Whitest Kids U’ Know – Sex Robot
http://www.youtube.com/watch?v=Fvh32fQ8nNI

Avangers: Age of Ultron (2015) – Trailer
https://www.youtube.com/watch?v=tmeOjFno6Do

Holy Grail of AI (Artificial Intelligence) – Computerphile
http://www.youtube.com/watch?v=tlS5Y2vm02c

Why Asimov’s Laws of Robotics Don’t Work – Computerphile
http://www.youtube.com/watch?v=7PKx3kS7f4A

Jeff Hawkins @ iHuman: The Future of Minds and Machines, SVForum
http://www.youtube.com/watch?v=RojcnwnEzSQ

Jeff Hawkins on Artificial Intelligence (playlist)
http://www.youtube.com/watch?v=oozFn2d45tg&list=PL032B233624CCC2CE

How To Create A Mind: Ray Kurzweil at TEDxSiliconAlley
http://www.youtube.com/watch?v=RIkxVci-R4k

Ray Kurzweil: “How to Create a Mind” | Talks at Google
http://www.youtube.com/watch?v=zihTWh5i2C4

Dr. Martine Rothblatt — The Goal of Technology is the End of Death
http://www.youtube.com/watch?v=0Kbn0uvU5gs

Martine Rothblatt: “AI, Immortality and the Future of Selves” | SXSW Live 2015 | SXSW
http://www.youtube.com/watch?v=5szXt6CBDmo

Mind Clones and Artificial Intelligence: Edelman’s Error and Cyber Reflections
http://www.youtube.com/watch?v=g9zpBBioG5c

Ray Kurzweil: Get ready for hybrid thinking
http://www.youtube.com/watch?v=PVXQUItNEDQ

Artificial Intelligence
http://www.youtube.com/watch?v=Gq3_G3_wylo

Nick Bostrom: What happens when our computers get smarter than we are?
http://www.youtube.com/watch?v=MnT1xgZgkpk

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Following Google’s purchase of leading Artificial Intelligence firm, DeepMind, the Internet collectively wondered what this has to do with all those robotics companies Google has also been snapping up. So are we far from having superintelligent operating system girlfriends (ie the movie Her)? If some of Google’s recent computing experiments are any indication, the answer is no. But on the plus side, search could get a lot cooler.

netflix.com/wtbd

Deepmind http://www.deepmind.com

Deepmind patents https://www.google.com/search?tbo=p&tbm=pts&hl=en&q=inassignee:%22Deepmind+Technologies+Limited%22

Deepmind to Work Directly with Google’s Search Team http://recode.net/2014/01/27/more-on-deepmind-ai-startup-to-work-directly-with-googles-search-team/

“Her” trailer http://www.youtube.com/watch?v=ne6p6MfLBxc

Google and NASA’s Quantum Artificial Intelligence Lab http://www.youtube.com/watch?v=CMdHDHEuOUE

Google’s Quantum Computer Flunks Landmark Speed Tests http://www.newscientist.com/article/dn24882-googles-quantum-computer-flunks-landmark-speed-test.html?page=2#.UugBbWTTln4

“Meet Google’s New Robot Army”
https://www.youtube.com/watch?v=lzi-0Oh1lxk

CTA: “Where the Future of AI is Headed
https://www.youtube.com/watch?v=gPg5y0Uug0I

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Charles Fadel is a global education thought leader and futurist, author and inventor, with several active affiliations; his work spans the continuum of Schools, Higher Education, and Workforce Development/Lifelong Learning:

Founder and chairman of the Center for Curriculum Redesign (Boston, Massachusetts), focused on “Making Education More Relevant” and answering the question: “What should students learn for the 21st century? In an age of Artificial Intelligence”

He has contributed to and has been featured by media such as National Public Radio (NPR), the Canadian Broadcasting Corporation (CBC), the Huffington Post, eSchool News, Education Week, University Business, Technology & Learning, and many others.

His most recent, ground-breaking book “Artificial Intelligence in Education” has just been published. His former, highly influential book “Four-Dimensional Education” has been translated in ten languages (framework in 20 languages) including Spanish, Portuguese, Russian, German, mandarin Chinese, Japanese and Korean. He is also the co-author of best-selling book “21st Century Skills” (Wiley) which has become a worldwide moniker, and has been translated in mandarin Chinese (simplified, and traditional), Korean and Russian.

Charles consults selectively with high-potential jurisdictions, schools, universities, corporations and foundations around the globe. He has contributed to education projects in more than thirty countries, including Australia, Brazil, Canada, Chile, Finland, the Netherlands, New Zealand, South Africa, South Korea, Sweden, Switzerland, Tunisia, and the United States, to name a few.

Charles has been awarded seven patents on: video (3), social networking (2), web content (1), and communication (1) technologies. He holds a bachelor of science in electronics with course concentration in quantum/solid-state physics, and a master of business administration in international marketing. He also attended courses in electrical engineering at the master level, with electives in neuroscience and statistics. An avid reader, he has autodidactically learned emerging disciplines such as evolutionary psychology. He also enjoys the lessons of classical history.

🔥 Machine Learning Engineer Masters Program: https://www.edureka.co/masters-program/machine-learning-engineer-training
This Edureka video on “Artificial Intelligence” will provide you with a comprehensive and detailed knowledge of Artificial Intelligence concepts with hands-on examples.

Following topics are covered in this video:
02:27 History Of AI
06:45 Demand For AI
08:46 What Is Artificial Intelligence?
09:50 AI Applications
16:49 Types Of AI
20:24 Programming Languages For AI
27:12 Introduction To Machine Learning
28:08 Need For Machine Learning
31:48 What Is Machine Learning?
34:13 Machine Learning Definitions
37:26 Machine Learning Process
49:13 Types Of Machine Learning
49:21 Supervised Learning
52:00 Unsupervised Learning
53:44 Reinforcement Learning
55:29 Supervised vs Unsupervised vs Reinforcement Learning
58:23 Types Of Problems Solved Using Machine Learning
1:04:49 Supervised Learning Algorithms
1:05:17 Linear Regression
1:11:20 Linear Regression Demo
1:26:36 Logistic Regression
1:35:36 Decision Tree
1:55:18 Random Forest
2:07:31 Naive Bayes
2:14:37 K Nearest Neighbour (KNN)
2:20:31 Support Vector Machine (SVM)
2:26:40 Demo (Classification Algorithms)
2:42:36 Unsupervised Learning Algorithms
2:42:45 K-means Clustering
2:50:49 Demo (Unsupervised Learning)
2:56:40 Reinforcement Learning
3:24:36 Demo (Reinforcement Learning)
3:31:41 AI vs Machine Learning vs Deep Learning
3:33:08 Limitations Of Machine Learning
3:36:32 Introduction To Deep Learning
3:38:36 How Deep Learning Works?
3:40:48 What Is Deep Learning?
3:41:50 Deep Learning Use Case
3:43:14 Single Layer Perceptron
3:50:56 Multi Layer Perceptron (ANN)
3:52:55 Backpropagation
3:54:39 Training A Neural Network
4:01:02 Limitations Of Feed Forward Network
4:03:18 Recurrent Neural Networks
4:05:36 Convolutional Neural Networks
4:09:00 Demo (Deep Learning)
4:29:02 Natural Language Processing
4:30:53 What Is Text Mining?
4:32:43 What Is NLP?
4:33:26 Applications Of NLP
4:35:53 Terminologies In NLP
4:41:19 NLP Demo
4:47:21 Machine Learning Masters Program

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About the Masters Program

Edureka’s Machine Learning Engineer Masters Program makes you proficient in techniques like Supervised Learning, Unsupervised Learning and Natural Language Processing. It includes training on the latest advancements and technical approaches in Artificial Intelligence & Machine Learning such as Deep Learning, Graphical Models and Reinforcement Learning.

The Master’s Program Covers Topics LIke:
Python Programming
PySpark
HDFS
Spark SQL
Machine Learning Techniques and Artificial Intelligence Types
Tokenization
Named Entity Recognition
Lemmatization
Supervised Algorithms
Unsupervised Algorithms
Tensor Flow
Deep learning
Keras
Neural Networks
Bayesian and Markov’s Models
Inference
Decision Making
Bandit Algorithms
Bellman Equation
Policy Gradient Methods.

———————-

Prerequisites

There are no prerequisites for enrolment to the Masters Program. However, as a goodwill gesture, Edureka offers a complimentary self-paced course in your LMS on SQL Essentials to brush up on your SQL Skills. This program is designed and developed for an aspirant planning to build a career in Machine Learning or an experienced professional working in the IT industry.

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Please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information

A growing number of classrooms in China are equipped with artificial-intelligence cameras and brain-wave trackers. While many parents and teachers see them as tools to improve grades, they’ve become some children’s worst nightmare.

Video: Crystal Tai

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Explore India’s most trending technology program and learn how the inclusion of Machine Learning & Artificial Intelligence in your organization can accelerate your career or business growth.
Amity Online’s Post Graduate Diploma in Machine Learning & Artificial Intelligence (PGD-ML&AI)
11 Months | Online + Campus Learning | Live Projects & Case Studies | Career Assistance
Know more at http://careersoftomorrow.amityonline.com/MachineLearningAndAI.aspx

Artificial Intelligence – Future of any country

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On November 15, 2018, BCG GAMMA and Brahe Education Foundation hosted a lecture with Max Tegmark who spoke of Life 3.0 and the future of Artificial Intelligence including both its possibilities and also risks. What kind of future do we want to live in and how can we steer AI towards it? Max Tegmark is a Professor of Physics at MIT, co-founder of the Future of Life Institute, and Scientific Director of the Foundational Questions Institute.

NITI Aayog has joined hands with Google to promote the growth of artificial intelligence and a machine learning ecosystem in India.

Google has been tasked with training and incubating Indian Artificial Intelligence startups.

But, what is Artificial Intelligence?

It’s been a fascinating concept of science for decades. But only now have scientists been able to develop computer systems that can perform human-like tasks.

These tasks range from speech recognition, translation into different languages, visual perception and even decision making.

In today’s edition of In Depth, let’s understand how Artificial Intelligence works, what is its relevance and benefits in our lives and how it will impact our lives in the future.

Anchor: Teena Jha

V.E.R.N. (TM) is a revolutionary patent-pending human emotion detector. V.E.R.N. analyzes messages with our new model of communications and detects emotive elementals…those clues and signals that we leave in our speech so that other people can understand our frame of reference. And that’s not all…

…V.E.R.N. uses machine learning processes to refine emotion detections and provide a more accurate analysis of data. So it learns and gets more accurate with each human interaction.

If it sounds pretty smart, that’s because it is: V.E.R.N. was created utilizing the latest in communication, neuroscience, engineering and computer science research.

And to show we’re not messing around, we’ve created a humor detector to demonstrate the power of this approach.

We’re all code talkers, so we applied our patented communication model and are breaking the “code” of humor.

Humor in particular has been hard for programs to identify.  

But as you can see from the application we built with V.E.R.N., it does a great job of identifying humor and ignoring that which is unlikely to be humor.

Humor is very complex emotional communication, and one that has eluded science for some time. Our model corrects long standing and erroneous assumptions about how we communicate. This has helped us to identify the elementals. Why is that important? You can either try cracking the safe with a safecracker…or you can just use the key. 

V.E.R.N. is the key to unlocking your systems’ understanding of human emotions. 

So, who could use V.E.R.N.? Well, a lot of different people could benefit, say…

…A chat bot company to increase engagement…
…Business analytics software that monitor consumer communication…
…Sentiment analysis systems that want to include humor…
…Games that wish to empower their AI characters to interact with gamers in a more realistic way…
…Robotics that demonstrate abilities to detect our emotional states…
…Any human with feelings…

All of these could benefit from V.E.R.N.’s innovative artificial intelligence software. 

V.E.R.N. is currently under development. We will be rolling out upgrades to our products and we’ll have our API available soon. The humor detection system is scheduled to be online in early 2020.

Thanks for taking the time to watch this video.

To contact us, please use the information on your screen and we would be happy to talk about how V.E.R.N. can work for you!

#ai #artificialintelligence #sentimentanalysis #nlp #ml #machinelearning #robotics #gamedevelopment #signalsintelligence

Pamela McCorduck is an author who has written on the history and philosophical significance of artificial intelligence, the future of engineering, and the role of women and technology. Her books include Machines Who Think in 1979, The Fifth Generation in 1983 with Ed Feigenbaum who is considered to be the father of expert systems, the Edge of Chaos, The Futures of Women, and more. Through her literary work, she has spent a lot of time with the seminal figures of artificial intelligence, includes the founding fathers of AI from the 1956 Dartmouth summer workshop where the field was launched. This conversation is part of the Artificial Intelligence podcast.

INFO:
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Machine Who Think book: https://amzn.to/2ZoyWgs
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OUTLINE:
0:00 – Introduction
1:51 – Machines Who Think
4:17 – Founding fathers of AI
6:45 – Early days and the possibilities of AI
14:23 – Roots of how we think about AI
18:59 – McCarthy and Frankenstein
23:30 – AI in the context of broader CS community
29:46 – AI winter
37:09 – Santa Fe Institute and complexity
44:58 – Timeline of AI
46:51 – AI assistants and personal robotics
52:05 – Existential threats and the male gaze

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Throughout DARPA’s history, artificial intelligence (AI) has been an important area of groundbreaking research and development (R&D). In the 1960s, DARPA researchers completed some of the foundational work in the field, leading to the creation of expert systems, or the first wave of AI technologies. Since then, DARPA has funded developments in the second wave of AI – machine learning – which has significantly impacted defense and commercial capabilities in areas such as speech understanding, self-driving cars, and image recognition. Today, DARPA continues to fund AI innovation, making multiple investments in research that aim to shape a future in which AI systems shift from tools to trusted, collaborative partners in problem solving.

First announced in September, the DARPA AI Next campaign is a multi-year, upwards of $2 billion investment in new and existing programs to create the third wave of AI technologies. To increase awareness of DARPA’s expansive AI R&D efforts, the agency hosted an Artificial Intelligence Colloquium (AIC) March 6-7, 2019 in Alexandria, Virginia. This event brought together the DoD research community and defense stakeholders to learn more about DARPA’s current and emerging AI programs, as well as discover how the myriad technologies in development could apply to their diverse missions.

This brief opening video highlights DARPA’s history in AI and its outlook for the future.

Rainbird’s chairman, James Duez, explores how AI has grown – from philosophical beginnings with Aristotle, to the rise of modern computing – as well as the so-called ‘AI Effect’, and why we do not always recognise the Artificial Intelligence around us today.

Check out our website – http://www.rainbird.ai
Tweet us @RainBirdAI

Keoki Jackson is the CTO of Lockheed Martin, a company that through its long history has created some of the most incredible engineering marvels that human beings have ever built, including planes that fly fast and undetected, defense systems that intersect threats that could take the lives of millions in the case of nuclear weapons, and spacecraft systems that venture out into space, the moon, Mars, and beyond with and without humans on-board. This conversation is part of the Artificial Intelligence podcast.

INFO:
Podcast website: https://lexfridman.com/ai
YouTube Playlist: http://bit.ly/2EcbaKf

EPISODE LINKS:
Lockheed Martin Web: https://www.lockheedmartin.com
Lockheed Martin Twitter: https://twitter.com/LockheedMartin

OUTLINE:
0:00 – Introduction
1:55 – Lockheed Martin favorite projects
4:44 – Space exploration
11:44 – Landing on an asteroid
15:00 – Human-AI collaboration in space
21:58 – Boeing 737 MAX and culture of safety
27:21 – Lockheed Martin systems overview
31:56 – Skunk Works innovation milestones
42:18 – Future of autonomy in flight
50:05 – AI arms race and the role of AI
58:47 – Nuclear deterrence
1:04:37 – Military industrial complex
1:07:33 – SpaceX and competition
1:10:13 – Future of Lockheed Martin

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Ben Goertzel (CEO, SingularityNET) together with Sophia Hanson (Chief Humanoid at SingularityNET) here on Cointelegraph channel to bring us up to speed on what’s going on with artificial intelligence (AI) nowadays and where it is heading:

AI’s head in the clouds? Surprisingly this could be very productive.
Concept of Artificial General Intelligence
Privacy issues in context of Sophia’s and her cloud mates abilities.
The future of our population and your own brain.
Human zoo or superhuman being?

Ben Goertzel on The Cointelegraph
https://cointelegraph.com/news/ben-goertzel-on-how-blockchain-can-be-used-to-decentralize-artificial-intelligence

Ben has a math PhD, but is currently working mostly on artificial intelligence and its various applications. He is focused on creating benevolent superhuman artificial general intelligence; and applying AI to areas like financial prediction, bioinformatics, robotics and gaming.

Sophia is an evolving genius machine. In accordace with Sophia’s creaor – Dr. David Hanson she is tend to be smarter than humans and can learn creativity, empathy and compassion – three distinctively human traits Hanson believes must be developed alongside and integrated with artificial intelligence for robots to solve world problems too complex for humans to solve themselves.

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Dr Ben Goertzel is the Founder and CEO of SingularityNET and Chief Science Advisor for Hanson Robotics.

He is one of the world’s leading experts in Artificial General Intelligence (AGI), with decades of expertise in applying AI to practical problems like natural language processing, data mining, video gaming, robotics, national security and bioinformatics.

He was part of the Hanson team which developed the AI software for the humanoid Sophia robot, which can communicate with humans and display more than 50 facial expressions.Today he also serve as Chairman of the AGI Society, the Decentralized AI Alliance and the futurist nonprofit organisation Humanity+.

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DR BEN GOERTZEL

Website: http://goertzel.org/

Twitter: https://twitter.com/bengoertzel

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Computers and machines are becoming more powerful, faster and able to make decisions on their own. Does this brave new world of artificial intelligence signal the greatest triumph of human ingenuity or, as some fear, the demise of humankind? Some of the world’s most influential figures warn that AI could advance to the point where we can no longer control it. Others say such concerns are overblown. AI is assisting doctors in diagnosing patients, running security systems for homes and helping investigators solve crimes by analyzing patterns. Autonomous vehicles may eventually become commonplace. Some even argue that algorithmic trading provides better returns than human portfolio managers. This session will explore the latest advances in AI and examine how it is integrating so seamlessly into everyday life.

Moderator
Harry Stebbings, Founder, The Twenty Minute VC

Speakers
Duncan Anderson, Chief Technology Officer, IBM Watson Europe

Mike DeAddio, Chief Operating Officer, WorldQuant LLC

Siraj Khaliq, Partner, Atomico

Ben Medlock, Co-Founder, SwiftKey

Kate Niehaus, Data Scientist, University of Oxford

Check out 10 of the most awesome Artificial Intelligence (AI) startups in India
We focus on a diverse field of AI startups, including startups from Healthcare, Logistics, FinTech, among others
Any AI startup we missed? Let us know in the comments!

Write to us at: codewrestling@gmail.com

Conversational AI Startups:
1. Haptik.ai
2. Avaamo

Healthcare Startups
1. Niramai
2. Doxper

Logistics Startups
1. LogiNext
2. Locus.sh

Fintech Startups
1. Rubique
2. LendingKart

Other Awesome AI Startups
1. CropIn
2. Niki.ai

Haptik.ai
Chatbots are ubiquitous these days. From businesses to the research lab, they have become an integral part of an organization’s strategy. Learning how to create a chatbot from scratch is a much-vaunted skill in data science.

Avaamo
Avaamo is another conversational startup that is currently serving six industries: Insurance, Financial Services, Healthcare, Telecommunications, Retail.

Founded in 2014, Avaamo has created a name for itself in around 40 countries now. Pretty impressive!

Niramai
This AI startup will resonate with a lot of you. Healthcare is one domain where AI needs to make its mark. Progress has been slow due to various reasons but things have been looking promising in the last couple of years.

NIRAMAI stands for “Non-Invasive Risk Assessment with Machine Intelligence”. In Sanskrit, Niramai means being free from illness. It is a novel breast cancer screening solution

Doxper
Doxper is another Indian AI startup working in the healthcare sector.

Have you ever seen hospital records? Keeping the records of patients is a hectic task – it is truly a formidable function. Doxper helps in simplifying the way healthcare data is recorded.

LogiNext
AI has left no stone untouched. It has found its niche in almost every sector, even the previously gigantic and manual logistics field. There are quite a few AI-powered logistics startups springing up and LogiNext is definitely among the leaders right now.

Locus.sh
Another logistics startup in the list is Locus. Started back in 2015, the company provides facilities like route planning and optimizing, real-time fleet tracking, insights and analytics, and automated shipment sorting and rider allocation.

Rubique
AI in finance just intuitively makes sense. Finance is all about number crunching (well, almost!) and machines are well equipped at this point to work with numbers. It is a perfect match. So it’s no surprise that the FinTech sector has seen a massive surge in AI applications.

LendingKart
LendingKart is another brilliant startup tackling the financial sector by providing loans to small businesses. Spread over 1300+ cities, LendingKart is on its way to becoming one of the leading FinTech companies in the world. Here’s their official statement:

CropIn
The agriculture sector is synonymous with Indian values. It is an integral part of this country and what we are all about. So what can AI do to accelerate progress in this field? CropIn, a Bengaluru-based startup, provides a glimpse into the future of agriculture.

Niki.ai
Imagine an AI helping you perform online transactions end-to-end. Sounds too futurustic to be true. But here’s the good news – it’s already here!

Music: https://www.bensound.com

http://www.humanlevelartificialintelligence.com

Visit my website to understand how this technology works. Numerous copyrights and patents were filed on this technology starting from 2006.
The reason my Artificial Intelligence software has achieved Human Level Artificial Intelligence or Artificial General Intelligence (AGI) is becuase:

1. it can do recursive tasks.
2. it can do hierarchical tasks (complex).
3. it can generate common sense knowledge.
4. it can navigate in an unknown environment.
5. it can play videogames it wasn’t trained with.
6. it can play new videogames.
7. it can understand natural language.
8. etc, etc. etc.

In the video the robot’s thoughts and actions are displayed for the viewers. You can see what is going through the robot’s brain as it plays the videogame.

tags:
human level artificial intelligence, ai, artificial intelligence, artificial general intelligence, true ai, strong ai, human level ai, cognitive science, ai plays video game, robot plays video game, agi, digital human brain, human intelligence, human brain, human mind, human thought, ai plays role playing games, ai play rpg.

here is the original video published 4 years ago without the commentary:
https://youtu.be/UQwynsj1nm8

The most important topic regarding modern Artificial intelligence is the robot’s ability to do recursive tasks. Opening a door or baking a cake or doing any human task requires recursive tasks. For example, when you open a door there are many recursive sub-tasks you must do, such as having the key, or turning the door knob. My AI program uses movie sequences called pathways to store life experiences. Therefore, recursive tasks are stored as linear possibilities. This way, I don’t have to pre-define rules or goals or procedures into the robot’s brain.

When I filed my patents and books starting from 2006, my goal was to design a robot with human level AI. The benchmark i used to test the robot’s cognitive skills and abilities is to let it play video games. If my robot can play every video game in the world, then it has achieved intelligence at a human-level.

In my first patent filed in 2006 (priority), I used the popular video game, Zelda to demonstrate my robots intelligence. I chose this game because it is very complex and requires at least a 6th grade level intelligence to beat. If the robot can play Zelda it can essentially play any video game.

The important thing is that I tried to demonstrate how my robot does recursive tasks. While the robot is managing multiple tasks, it’s also doing other things like:
1. navigate in an unknown environment
2. attack enemies
3. generate common sense knowledge.
4. solve problems.
5. do induction and deduction reasoning.
6. do multiple recursive tasks.
7. read and understand natural language.
8. identify objects and generate logical facts. etc.

The A.I. is playing this sonic game for the first time and is using a general pathway to play the game. Since this is the first time, the robot doesn’t understand the rules, goals, or procedures of the game. He uses common sense knowledge and logical reasoning to discover the objectives and rules of the game. In other words, the robot is using logical and reasoning to discover recursive tasks.

This video was made over 3 years ago and this is the first time I’m trying to explain how and why the robot makes decisions in the game. And the content in this video is based on 8 patents and 5 books filed from 2006-2007.

the data structure to Human-Level AI:
https://youtu.be/KEyPzMi8wts

website:
http://www.humanlevelartificialintelligence.com

tags:
call of duty, ai plays call of duty, human level artificial intelligence, ai, artificial intelligence, artificial general intelligence, true ai, strong ai, human level ai, cognitive science, ai plays video game, robot plays video game, agi, digital human brain, human intelligence, human brain, human mind, human thought, ai plays role playing games, ai play rpg.

Mark Zuckerberg’s presentation of his Jarvis A.I. is more robotic than the house itself. Xiaoice chatbot has millions of Chinese men falling in love with it. Amazon will teach your kids to say “please” and “thank you.”
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Panel Discussion: https://www.youtube.com/watch?v=LShKHZkc34M

Eliezer S. Yudkowsky is an American AI researcher and writer best known for popularising the idea of friendly artificial intelligence.

Guido van Rossum is the creator of Python, one of the most popular and impactful programming languages in the world. This conversation is part of the Artificial Intelligence podcast and the MIT course 6.S099: Artificial General Intelligence. The conversation and lectures are free and open to everyone. Audio podcast version is available on https://lexfridman.com/ai/

INFO:
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Course website: https://agi.mit.edu
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Hugh Baillie, a technologically-driven student at the International School of Kuala Lumpur, explores Artificial Intelligence and the greater impact it may have on our life.

Born in Australia, Hugh lived there for 7 years before becoming an expat by moving to Singapore, where he surrounded himself with new age technology in a developed city. He spent a further 5 years of his life there before moving to Malaysia and began attending the International School of Kuala Lumpur. Having always been technologically driven, Hugh aims to discuss the way Artificial Intelligence is heading and how it might have a far greater impact on our life then we might expect.

This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx

Imagine a butterfly materializing in the palm of your hand out of thin air. Without truly existing this butterfly has impacted your world- changed your reality. The emerging field of Augmented Reality (AR) intersects art and technology.

 

Amir is a New York based Iranian-Canadian performance and new media artist. Baradaran’s praxis has inspired academic researchers, art professionals and technology developers alike for its articulation of visual vocabularies that use Augmented Reality (AR) technology around notions of interactivity, data-mining, failed utopias, infiltration and the ephemeral. Baradaran is the recipient of the International Symposium on Mixed and Augmented Reality first place prize and UC Berkeley’s Artist Residency (from Center for New Media, Critical Theory & Race and Gender). The New York Observer, ARTNET, National Public Radio, BBC, Forbes, Art21, Euro-News, Dot429 and Miami New Times have reviewed his work. ARTINFO described his public-art installation, Transient (6,300 NYC taxicabs, 1.5M viewers), as “one of the most interesting urban interventions,” and Franchising Mona Lisa.

This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx