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October 27-29, 2020 is an NYC based artificial intelligence company that’s raised over $30 million. I sat down with the founder Dennis Mortensen to learn more about how they’re positioning and selling the product to the enterprise.

Talking to him got me super curious about the rise of artificial intelligence, and I hope this interview does similar for you.

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Ray Kurzweil
Inventor, Author, and Futurist

Nicholas Thompson
Editor in Chief, Wired

There is more to artificial intelligence than today’s futuristic movies and sci-fi robots. The history of AI dates back to 400 BCE, and has been built over the centuries by inventors, writers, and scientists across the globe. Join us in exploring humanity’s long-standing fascination with artificial intelligence.

Whether it is Google’s DeepMind Health or IBM’s Watson System, Artificial Intelligence is revolutionizing the field of medicine. Our interactions with some form of Artificial Intelligence are inevitable in today’s world.
Artificial Intelligence is surely the future of efficient, accurate and hopefully more empathetic medicine- be it conventional or Ayurveda. Join me tomorrow for the 4th Session of Ayurveda Thinkathon with my guest Suchana Seth to understand more! #AIinayurveda #machinelearningandayurveda #ayurvedaresearch #AIethics #responsiblemachinelearning #ayurveda

Anita Schøll Brede is the CEO and Co-Founder of, one of the 10 most innovative artificial intelligence startups in 2017 according to Fast Company. Learn more about #SUItalySummit at


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Artificial Intelligence vs Human Intelligence || Who is Winning the Intelligence Race ?
Who Is Winning the AI Race: China, the EU or the United States? The United States leads the race for global advantage in artificial intelligence, at least for the time being, with China coming in second and the EU lagging behind.

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AI Win On the race

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Things you will be learning in this video are:

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🔥Edureka NIT Warangal Post Graduate Program on AI and Machine Learning:
This Edureka Tutorial on “Future Of AI/ML” talks about the future possibilities of artificial intelligence and Machine Learning and how we can get a job in AI/ML. Below are the topics covered in this tutorial:
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Edureka’s Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you:

1. Master the Basic and Advanced Concepts of Python
2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs
3. Master the Concepts of Sequences and File operations
4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python
5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application
6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn
7. Master the concepts of MapReduce in Hadoop
8. Learn to write Complex MapReduce programs
9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python
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Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built-in debugger.

Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next “Big Thing” and a must for Professionals in the Data Analytics domain.

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Neil deGrasse Tyson discusses the future of robotics and A.I. with the former head of DARPA, Arati Prabhakar. Back in the studio, guest robotics engineer Hod Lipson joins the conversation to explain engineering next generation robotics.
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Host Neil deGrasse Tyson brings together celebrities, scientists and comedians to explore a variety of cosmic topics and collide pop culture with science in a way that late-night television has never seen before. Weekly topics range from popular science fiction, space travel, extraterrestrial life, the Big Bang, to the future of Earth and the environment. Tyson is an astrophysicist with a gifted ability to connect with everyone, inspiring us all to “keep looking up.” The studio audience portion of the series is filmed in the Cullman Hall of the Universe at the American Museum of Natural History’s Rose Center for Earth and Space in New York City — where Tyson serves as the Frederick P. Rose Director of the Hayden Planetarium.

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The Future of Artificial Intelligence | StarTalk

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In this Keynote Session, some of Google’s leading minds on artificial intelligence and machine learning discuss their vision for a future where artificial intelligence can improve the lives of everyone.

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Written – Raj
collaborator – Prabakaran
Category – Education, Science and mystery
License – Stand YouTube License

This video explains about artificial intelligence, Artificial general intelligence and Technological singularity. Difference between artificial intelligence and artificial general intelligence explains the technological singularity.

But debate about Artificial intelligence future technology are different ideas from each side. some debate that Artificial general intelligence lead extinct of human life because artificial intelligence get more intelligence compare to humans on the other hand some believe that which not happens.

Elon Musk and Stephan William Hawking’s believe that Artificial intelligence future technology lead human extinct

For more details please watch full video and thanks for watching.

IBM’s deep blue project can only play chess, an autonomous car can only drive a car, an AI checkers program can only play checkers. A universal artificial intelligence is one software program that can do any human task. It can drive a car, play chess, play any video game, cook in a restaurant, clean a house, fly a plane, write software programs, etc.

So far I have made videos on playing chess, playing video games, driving a car, and doing math equations. I stated in my books/patent apps/website, that my robot can do any human task. This video shows the robot playing tetris. In the video I show how the robot thinks while he’s playing the game.

Tetris is a puzzle game that require the player to stack up blocks to form stacked rows. Humans learn how to stack up blocks and solve puzzles starting from a very young age. Stacking blocks so the pieces fit are lessons learned in Kindergarten and in grade school. When the robot is playing tetris, he has to tap into knowledge about block stacking or puzzle stacking. He has to know that this shape fits into that shape.

In addition to knowledge about piecing together puzzles, the robot has to have strategies to play the game. He has to have objectives, and recursive objectives and so forth. These objectives and strategies are discovered through either trial and error or from instruction manuals. The robot can read strategies from a video game magazine or he can discover strategies based on trial and error.

Also, making decisions about where should blocks be stacked and conflicts of interests are learned from teachers in school. By the time the robot is at age 10, his brain contains self-learning pathways or self-adaptive pathways. He has the knowledge to teach himself the best strategies to play tetris. For example, no teacher has taught the robot how to play tetris. He used his own intelligence to find out what the game is about, how to play the game, what are the best strategies in the game, what decisions to make, and so forth.

The truth is that playing tetris is a very complicated thing to do. The video only shows a general way the robot thinks as it is making decisions in the game. The internal instructions are much more complex.

This robot doesn’t use planning programs or heuristic searches. This is not an expert program that was designed specifically to play tetris. This robot can play chess, play checkers, play monopoly (or any board game), drive a car, fly a plane, play any video game, or do any human task. Programmers don’t have to change the robot’s brain for each human task.

For more information about human level artificial intelligence, visit my website:

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, robot thoughts, deep learning, human thoughts, ai plays role playing games, ai play rpg, demo ai, general ai.

In this video we discuss the challenges faced in developing AI that can play any video game you give it. This is the focus of the General Video Game – AI competition.

Full details including a link to the written piece at:

In addition, a full list of all my work on AI can be found at:

No copyright is claimed for the game footage, images and music, to the extent that material may appear to be infringed, I assert that such alleged infringement is permissible under fair use principles in copyright laws. If you believe material has been used in an unauthorized manner, please contact me.

Artificial General Intelligence or short AGI was commonly referred as Strong AI. The continues advancements in robotics are also spurring the development of AGI. Currently we only have narrow AI or weak AI. But robots are paving the way for strong AI. In the future, robots might possibly become smarter than us or at least, reach human level intelligence. The field of robotics has seen many improvements over the years, as artificial intelligence systems continue to get better. Machine intelligence is a trendy topic among computer scientists and other relevant researchers on the field. As robots continue to get better, concerns for the rise of a superintelligence or an artificial general intelligence that could have different goals from ours, is increasingly getting the attention of computer scientists and lay people alike. We have often seen works of science fiction where robots and AGI have malicious intent. However, things could go really bad fur us even if initially these intelligent machines are programmed to obey human orders and follow our values. As a machine continues to improve itself by modifying it’s own source code, it could lead to an intelligence explosion. A point of time often referred as a technological singularity. Where it becomes hard if not impossible to predict future trajectories of the AI in question. As of the year 2017, there are over 40 organizations focused on the development of AGI. As we’ve said many times before, today’s AI is narrow. However the field of robotics is accelerating the rise of AGI and we will possibly witness a truly general AI in our lifetimes.

#AGI #AI #Artificialintelligence

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Sources: Boston Dynamics’Big Dog:
Aldebaran – Softbank Robotics’ Nao:
When does a machine become a robot and a robot become a human? – J.D. Fencer

**AI and Deep Learning with TensorFlow: **
This video on Deep Learning Projects will provide you with a list of the top open-source deep learning projects you must try in 2019.

Lung Cancer Detection:
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How it Works?
1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work
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Edureka’s Deep Learning in TensorFlow with Python Certification Training is curated by industry professionals as per the industry requirements & demands. You will master the concepts such as SoftMax function, Autoencoder Neural Networks, Restricted Boltzmann Machine (RBM) and work with libraries like Keras & TFLearn. The course has been specially curated by industry experts with real-time case studies.



Deep Learning in TensorFlow with Python Training is designed by industry experts to make you a Certified Deep Learning Engineer. The Deep Learning in TensorFlow course offers:
In-depth knowledge of Deep Neural Networks
Comprehensive knowledge of various Neural Network architectures such as Convolutional Neural Network, Recurrent Neural Network, Autoencoders
Implementation of Collaborative Filtering with RBM
The exposure to real-life industry-based projects which will be executed using TensorFlow library
Rigorous involvement of an SME throughout the AI & Deep Learning Training to learn industry standards and best practices

Why should one go for this course?

Deep Learning is one of the most accelerating and promising fields, among all the technologies available in the IT market today. To become an expert in this technology, you need structured training with the latest skills as per current industry requirements and best practices.

Besides strong theoretical understanding, you will be working on various real-life data projects using different neural network architectures as a part of the solution strategy.

Additionally, you will receive guidance from a Deep Learning expert who is currently working in the industry on real-life projects.


Skills that you will be learning:

Deep Learning and TensorFlow Concepts
Working with Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN)
Proficiency in Long short-term memory (LSTM)
Implementing Keras, TFlearn, Autoencoders
Implementing Restricted Boltzmann Machine (RBM)
Knowledge of Neural Networks & Natural Language Processing (NLP)
Using Python with TensorFlow Libraries
Perform Text Analytics
Perform Text Processing

Who should go for this course?

The TensorFlow with Python Training is for all the professionals who are passionate about Deep Learning and want to go ahead and make their career as a Deep Learning Engineer. It is best suited for individuals who are:

Developers aspiring to be a ‘Data Scientist’
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Deep Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
Analysts wanting to understand Data Science methodologies

However, Deep learning is not just focused on one industry or skill set, it can be used by anyone to enhance their portfolio.


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The Hoover Institution and the Stanford Institute for Human-Centered Artificial Intelligence (HAI) hosted Ensuring America’s Innovation in Artificial Intelligence with Condoleezza Rice and Dr. Fei-Fei Li on Tuesday, June 30, 2020.

Artificial Intelligence (AI) has the potential to radically transform every industry and every society. Such profound changes offer great opportunities to improve the human condition for the better, but also pose unprecedented challenges. As this new era arrives, the creators and designers of AI must account for diversity of thought and ensure systems are built to properly reflect what it means to be human. Guiding the future of AI in a responsible way that translates American values of equality, opportunity and individual freedom will be paramount to ensuring our shared dream of creating a better future for all of humanity.

It takes nature and evolution more than five hundred million years to develop a powerful visual system in humans. The journey for AI and computer vision is about fifty years. In this talk, I will briefly discuss the key ideas and the cutting edge advances in the quest for visual intelligences in computers. I will particularly focus on the latest work developed in my lab for both image and video understanding, powered by big data and the deep learning (a.k.a. neural network) architecture.

Fei-Fei Li, Chief Scientist, AI/ML, Google Cloud, Professor of Computer Science, Stanford University
Director, Artificial Intelligence Lab

Martin Ford, author of the NYTimes Bestseller, “Rise of the Robots” and winner of the 2015 Financial Times/McKinsey Business Book of the Year Award shares his view of the impact of AI & Robotics on tomorrow’s world. Highlights taken from the dedicated conference organized by Societe Generale in Milan on December 4, 2017 to promote the launch of its Rise of the Robots index.

This evening public lecture took place in Edmonton on June 5, 2019.

#AI vs #ML vs #DL
This Lecture Explains The Differences Among Artificial Intelligence,Machine Learning & Deep Learning (AI vs ML vs DL) .
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This Edureka video on “Cognitive AI” explains cognitive computing and how it helps in making better human decisions at work. Also, it explains the differences between cognitive computing and artificial intelligence.

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About the Masters Program

Edureka’s Machine Learning Certification Training using Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. This Machine Learning using Python Training exposes you to concepts of Statistics, Time Series and different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. Throughout the Data Science Certification Course, you’ll be solving real-life case studies on Media, Healthcare, Social Media, Aviation, HR.


Why Go for this Course?

Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning


Who should go for this course?

Edureka’s Python Machine Learning Certification Course is a good fit for the below professionals:
Developers aspiring to be a ‘Machine Learning Engineer’
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
‘Python’ professionals who want to design automatic predictive models

If you are looking for live online training, write back to us at or call us at US: + 18338555775 (Toll-Free) or India: +91 9606058406 for more information.

Geordie Rose, Founder of D-Wave (recent clients are Google and NASA) believes that the power of quantum computing is that we can `exploit parallel universes’ to solve problems that we have no other means of confirming. Simply put, quantum computers can think exponentially faster and simultaneously such that as they mature they will out pace us. Listen to his talk now!

Artificial General Intelligence – AGI might be the last invention of mankind. For better or for worse. Artificial intelligence is very beneficial to society in today’s age. AI will probably continue to be beneficial in the coming decades. However, as intelligent machines continue to improve, with the development of a true AGI or artificial general intelligence, there might be a serious threat to humanity. This issue is known as the AI control problem or the AI alignment problem. The risks involved in the process of improving intelligent systems might be intrinsic to intelligent machines that are goal-oriented. Today’s AI are known as narrow AI. They are able to beat humans in specifics tasks like chess but the same AI can not beat humans across multiple domains. At least not yet. A true artificial general intelligence might be able to solve some of the deepest secrets of nature. It might run simulations and come up with new mathematical equations and models to solve seemingly unsolvable problems in science. Such an intelligent machine might be able to cure any disease and create a wealth of sorts we’ve only seen in science fiction. It is difficult for many people to take the AI control problem seriously. Not just for the general public but also for researchers and some computer scientists who are themselves involved in the creation of tomorrow’s AI. The skeptics for this thesis do not bring forth any compelling argument why we shouldn’t be concerned about AI. To say AGI is far into the future and therefore we shouldn’t worry is a non sequitur. However long it takes to create true artificial general intelligence, if we do not destroy ourselves and continue to improve our machines, the day we will stand in the presence of an AGI will come sooner than we realize. Hopefully we will be ready.

#AGI #AI #Artificialintelligence

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On 29 March 2019 at the UOC, during the meeting of the EADTU Artificial Intelligence Task Force, we took the chance to interview Wayne Holmes. The result is a conversation with Guillem Garcia Brustenga, Director of Trend Detection and Analysis at the eLearn Center. At this meeting in the UOC’s 22 @ building, Artificial Intelligence, personal assistants and the university of the future were discussed.

Dr. Holmes is a lecturer specializing in Education and Innovation Sciences at the Institute of Educational Technology at The Open University, where he conducts research on Artificial Intelligence in Education. His research focuses on the application of Artificial Intelligence in Education (AIED), how it can improve learning, and how we can ensure that its application is socially and ethically responsible.

La Universidad del Futuro. Inteligencia Artificial en la Educación

El 29 de marzo de 2019 en la UOC, en el marco de la reunión de la Task Force de Inteligencia Artificial de EADTU, se aprovechó la presencia de Wayne Holmes, para hacer y grabar una conversación con Guillem Garcia Brustenga, Director de Detección y Análisis de Tendencias del eLearn Center. En este encuentro en el edificio del 22 @ de la UOC, hablaron de Inteligencia Artificial, asistentes personales y la universidad del futuro.

El Dr. Holmes es profesor especializado en Ciencias de la Educación e Innovación, en el Institute of Educational Technology en The Open University, donde investiga sobre Inteligencia Artificial en Educación. Su investigación está centrada en la aplicación de la Inteligencia Artificial en la educación (AIED), cómo ésta puede mejorar el aprendizaje, y cómo podemos asegurar que su aplicación sea social y éticamente responsable.

#UOC #Education #AI

Andreas Schleicher, director of education and skills at the Organisation for Economic Co-operation and Development (OECD), visited the Future of Work Laboratory at the Lisbon Council.

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Download “World Class: How to Build a 21st Century School System” here:

This video discusses the importance of Artificial Intelligence (AI) in the Education Sector and how Education Technology or EdTech can benefit from it.

Right from Ecommerce to healthcare to education, in each and every sector the, intervention of AI has increased by multi fold. Many companies are now investing in developing their own version of AI and Machine learning. So, what exactly is AI and why it is called as the next big thing?

Artificial Intelligence is defined as the capability of a machine to imitate intelligent human behavior. It makes our digital, automated processes smarter. It also enhances the reliability quotient of any technology. So, what we used to see in the Science-Fiction movies is now a reality.

Also, each and every decision that we make is now data driven. The best example of the same is the online recommendations that we receive while surfing retail websites such as Amazon or Flipkart. It is the Machine learning technology that recommends you products based on your previous purchases.

Now, Imagine using similar technology to track performance of an individual student based on his previous grades, participation and performances. Won’t it help the student to enhance his or her performance? Therefore, AI has been taken seriously to literally fix the many loopholes in the education sector across the globe.

Bill Gates through the Bill and Melinda Gates Foundation has invested more than $120 in personalized learning. The idea is to develop software that creates individual lesson plans for students based on their performance. The amount itself confirms that the world is taking AI seriously and so should we.

Let’s explore the possibilities and effects that such a step would have on our society and educational system.
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Artificial Intelligence (AI) in Indian Classrooms- A Need of the Hour!

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I do NOT own this video. It belongs to Tedx Talk
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Can Technology Replace Doctors?

Everything is in its own way of change, so is in medical field. Emergence of Surgical robots, Pillo the personal health care robots, nurse robots etc. Are the near future of medical science. So before setting your future goals have a glance at the changing technologies

Robotics and AI are removing the human constraints and physical limitations on surgery and placement of innovative medicines. With ultra-high resolution robotic assistance, we can now consider the optimal site to place stem cells in the eye, brain, heart to drive regeneration. Or where to place cellular anti-cancer therapies to kill cancers. In the future, AI will further remove the speed, complexity and precision limitations inherent in a human being driving the robotic arm.Of course, human judgment is essential for the critical decision making but we should be able to rapidly automate the procedure. Automation should provide a higher quality of care, broader access and lower cost for patients.

Apart from conventional medicine, robots are also finding application in other branches of healthcare, such as psychology. Recently, psychology experts and artificial intelligence enthusiasts at the Stanford University of California got together to develop a chatbot that could function as your own cognitive behavioral therapist for just $39 a month. The chatbot, known as Woebot, makes use of artificial intelligence algorithms to track your mood and understand your psyche over time through regular conversations, which it then uses to make productive conversation and offer helpful tips to help reduce depression, anxiety and other psychological problems one can develop staying in a crowded city and living the listless modern life.


Prateek Joshi, founder and CEO of Plutoshift joins Will Sarni and Tom Freyberg on The Stream to talk all things artificial intelligence (AI).

He discusses why growing up in India made him appreciate the value of water, his move to Silicon Valley in the US and the role of AI in public and private sector water applications.

Discussed links:
IWA whitepaper on Digital Water:

Water Foundry/Plutoshift whitepaper:

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