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.

AI Race
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In his lecture hosted by BCG GAMMA and Brahe Education Foundation, Max Tegmark speaks about Life 3.0 and the future of Artificial Intelligence, its possibilities and risks. He asks what kind of future do humans want to live in and how can they steer AI towards it? His answers are profound and insightful, but very human-centric for obvious reasons. So lets hear what Sharon Zero has to say about it, from her very unique perspective.

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Martin Ford explores the ways in which AI and automation (aka, “robots”) are outpacing humans in a range of sectors, from education to law, agriculture to healthcare, management and beyond. He offers a realistic view of what the future of work—and your place in it—will look like. Beyond pragmatic concerns, Ford addresses a bigger question: can accelerating technology disrupt our entire economic system to the point where a fundamental restructuring is required? This next industrial revolution, Ford argues, will not be like the last one. In the past, even as jobs were eliminated, jobs were created to replace them.

#YouTube #HumanBias #AI

How do we know what is real and what is honest in this world of super information and connectivity? Human bias, computer algorithms and social media influencers are becoming ever more part of our human existence and the ability to critically evaluate and understand how they work and what they mean transcends the purchasing of gold and silver that my channel has traditionally focused on and is in my opinion relevant to nearly every decision we make in our modern lives.

Almost everything we do in the physical modern 2020 pandemic world we now live in is connected to the online universe – I choose the word universe because it is almost too vast to comprehend how big this online space is. We get our news, socialise, learn, interact, work and many more day to day activates online and collectively we are being disconnected from the physical world more and more every day. Most importantly (to the big corporations around the world at least) our money is managed and spent mostly online and the ability to influence or manipulate our purchasing decisions is worth trillions and trillions of dollars.

When you see something on YouTube that claims something radical and outlandish, just ask yourself is that right? What are the qualifications of the person making these claims? What ulterior motives are there at play here, what this machine wants me to think?
These are critical questions and they are critical for a reason. The how’s, what’s, why’s, who’s and where’s are the most important questions to ask yourself and others when looking to make decisions and will help you dissect the truth from the false.
To conclude, this modern world of algorithms and machine learning combined with the unfathomable amounts of information we are constantly bombarded with has and will continue to influence us. It’s unavoidable. How we interact with this information can help save us time, money and collectively make the internet and this global social network we find ourselves in more beneficial for all concerned.

What do you think? Let me know down in the comments!

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Keynote address to the Association of Transformational Leaders, North Hollywood, September 14, 2018. Sections showing audience interaction removed by agreement with ATL.

The Beyond Center presents the 2018 Beyond Annual Lecture with Max Tegmark.

If AI succeeds in eclipsing human general intelligence within decades, as many leading AI researchers predict, then how can we make it the best rather than worst thing ever to happen to humanity? I argue that this will require planning and hard work, and explore challenges that we need to overcome as well as exciting opportunities.

How can we grow our prosperity through automation without leaving people lacking income or purpose? What career advice should we give today’s kids? How can we make future AI systems more robust, so that they do what we want without crashing, malfunctioning or getting hacked? How can we make machines understand, adopt and retain our goals, and whose goals should should they be? What future do you want? Welcome to the most important conversation of our time!

Natural language processing allows computers to understand human language. It has plenty of applications. For example:
Text summarization, translation, keyword generation, sentiment analysis or chat bots.

So how it works? Let’s take a closer look at it.

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My presentation from the European Big Data Value Forum event in Helsinki on October 15th 2019.

This panel discussion was organized on 20 November 2019 by the NIAS Consciousness Studies Programme and supported by TATA Trusts.
The panellists: Prof. Sangeetha Menon, Dr. Sudarshan Iyengar, Dr. N.C. Narayanan, Dr. Tilak Agerwala & Dr. Saurabh Todariya.

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Machines are already very good at recognising human emotions when they have a static, frontal view of a person’s face. Maja Pantic, Professor of Affective and Behavioral Computing at Imperial College London, shares progress towards identifying people’s emotions “in the wild” and discusses possible applications, from marketing to medicine.

Taken from Joe Rogan Experience #1211:

Don’t simply give an edge to human intelligence above artificial intelligence because you are human. Rate of growth of AI and rate of degradation or HI is clearly seen

Listen to the Science Salon Podcast # 118 (audio-only):

In the popular imagination, superhuman artificial intelligence is an approaching tidal wave that threatens not just jobs and human relationships, but civilization itself. Conflict between humans and machines is seen as inevitable and its outcome all too predictable. In this groundbreaking book, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines. He describes the near-term benefits we can expect, from intelligent personal assistants to vastly accelerated scientific research, and outlines the AI breakthroughs that still have to happen before we reach superhuman AI. He also spells out the ways humans are already finding to misuse AI, from lethal autonomous weapons to viral sabotage. If the predicted breakthroughs occur and superhuman AI emerges, we will have created entities far more powerful than ourselves. How can we ensure they never, ever, have power over us? Russell suggests that we can rebuild AI on a new foundation, according to which machines are designed to be inherently uncertain about the human preferences they are required to satisfy. Such machines would be humble, altruistic, and committed to pursue our objectives, not theirs. This new foundation would allow us to create machines that are provably deferential and provably beneficial. Shermer and Russell also discuss:

• natural intelligence vs. artificial intelligence
• “g” in human intelligence vs. G in AGI (Artificial General Intelligence)
• the values alignment problem
• Hume’s “Is-Ought” naturalistic fallacy as it applies to AI values vs. human values
• regulating AI
• Russell’s response to the arguments of AI apocalypse skeptics Kevin Kelly and Steven Pinker
• the Chinese social control AI system and what it could lead to
• autonomous vehicles, weapons, and other systems and how they can be hacked
• AI and the hacking of elections, and
• what keeps Stuart up at night.

Stuart Russell is a professor of Computer Science and holder of the Smith-Zadeh Chair in Engineering at the University of California, Berkeley. He has served as the Vice-Chair of the World Economic Forum’s Council on AI and Robotics and as an advisor to the United Nations on arms control. He is a Fellow of the American Association for Artificial Intelligence, the Association for Computing Machinery, and the American Association for the Advancement of Science. He is the author (with Peter Norvig) of the definitive and universally acclaimed textbook on AI, Artificial Intelligence: A Modern Approach.

This dialogue was recorded on February 14, 2020 as part of the Science Salon Podcast series hosted by Michael Shermer and presented by The Skeptics Society, in California.

Listen to Science Salon via Apple Podcasts, Spotify, Google Play Music, Stitcher, iHeartRadio, and TuneIn.

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Billions of dollars are being invested in replicating the human brain. But will machine eventually totally replicate a human, including creativity? In this interview, we are asking Dr. Ahmed Elgammal, director of the Art & AI Laboratory, Rutgers University, and Founder & CEO, Artrendex about how AI, human creativity and art intelligence can coexist. How far AI potentially can go and how human art can benefit from it?

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Microsoft (MSFT) on Tuesday announced that it has built one of the top five supercomputers in the world designed specifically for OpenAI. The company made the announcement during its Build developers conference, which is being held virtually rather than in person in Seattle where it is usually held each year.

The supercomputer, Microsoft says, will be used to train OpenAI’s own artificial intelligence models. OpenAI, which was founded in 2015 and received initial funding from the likes of Elon Musk and Sam Altman. Musk has since left the company, while Altman is now its CEO.

The company is working to create artificial general intelligence, or AI that is capable of outperforming humans, according to the group’s charter. The firm says its main concern is that such technologies benefit all of humanity, while ensuring its power doesn’t become concentrated in the hands of a few.

The new supercomputer has an incredible 285,000 CPU cores, 10,000 graphics processing units, and 400 gigabits per second of connectivity for each GPU server. While the computer ranks in the top five of the most powerful machines in the world, Microsoft won’t say exactly where it falls on that list.

#Microsoft #ArtificialIntelligence
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This video shows a robot picking oranges from a farm. There are no sound in the video because i wanted to show the viewers what the robot is thinking, while picking oranges.

Building a robot to pick oranges isn’t as simple as identifying ripe oranges and putting them into a basket. There are company rules the robot has to follow in order to pick oranges. A few years ago, a employee working for this farming company was climbing a tall orange tree and he accidently fell and broke his leg. The farming company was sued for 1 million dollars in medical bills. This prompted the farm company to issue a rule that states no employee can climb a tree to pick oranges.

In addition to this rule, there are many other rules employees have to follow. The robot has to remember and follow all rules and common sense rules that are not stated in the company policies.

At the beginning, the robot generates a overall search strategy for his search area (lines 4, 5, and 6).

In the video, the robot has to devise search strategies for each type of tree. Since orange trees come in different shapes and sizes, the robot has to generate new search strategies for each tree. For example, a tall tree is searched differently from a small tree.

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What Is Artificial Intelligence (A.I) in Bengali ? Can robots destroy humanity in future. In this video I have explained simply How Artificial Intelligence works using Neural Networks & what are the future aspects of A.I ?
Artificial intelligence is of 3 types basically- Artificial narrow intelligence or artificial general intelligence, Artificial wide intelligence or artificial strong intelligence, & finally Singularity.
Artificial Intelligence (AI) is a field that has a long history but is still constantly and actively growing and changing. In this course, you’ll learn the basics of modern AI as well as some of the representative applications of AI. How autonomous vehicles uses a.i to drive themselves and neural networks is also described.

#Artificialintelligence #A.I #machinelearning

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Benefits & Risks of Artificial Intelligence

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Yoshua Bengio, Yann LeCun, Demis Hassabis, Anca Dragan, Oren Etzioni, Guru Banavar, Jurgen Schmidhuber, and Tom Gruber discuss how and when we .

Ray Kurzweil explores how and when we might create human-level artificial intelligence at the January 2017 Asilomar conference organized by the Future of .

AI pioneer Yoshua Bengio explores paths forward to human-level artificial intelligence at the January 2017 Asilomar conference organized by the Future of Life .

Yoshua Bengio, Yann LeCun, Demis Hassabis, Anca Dragan, Oren Etzioni, Guru Banavar, Jurgen Schmidhuber, and Tom Gruber discuss how and when we .

Whom should we believe? Those who tell us that AI is one of the most important things humanity is working on? Or get scared that AI is makes things worse? The debate cannot be solved in the abstract: we need evidence. But unfortunately, the kind of data usually used to answer the big questions does not inspire confidence. There is never a shortage of compelling anecdotes. it is always possible to find at least one to support any position. Talking about the problems of the world without talking about some accessible solutions is the way to paralysis rather than progress.
We have learned to harness fire for the benefits of humanity, but we had to overcome its downsides too. So, my point is, AI is important, but we must be concerned about it. In this talk I will not tell you whether AI is good or bad for humans, but I will make my point on how we can leverage AI for the benefit of Humans and how we can tame the future of AI by infusing in it a conscious Moral

5 ways: ways in which we can create an AI that uses its Intelligence to Learn what Humans value

– Embrace it to steer It
– Explicitly defining Ethical Behaviour
– Bring Transparency to AI systems
– Bridging the gap between system 1 and system 2
– Accountability – organizational /Group Vinay Singh is Data Science Manager at BASF SE, Germany, responsible for driving Artificial Intelligence and Machine Learning Topics. He is visiting research fellow at Department of Management Studies at National Central University of Taiwan and authored a couple of books related to Analytics ( Real-Time Analytics with SAP HANA; Manage your SAP project with SAP Activate; Creating and Using Advanced DSOs in SAP BW on SAP HANA; SAPBusiness Intelligence Essentials – Quick Guide ). He is one of the co-founders of ManiaVarsity. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at

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How to avoid AI hiring AI recruiting BIAS?
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Artificial intelligence for Everyone.

Everything about Applied Artificial Intelligence, Machine Learning in real world.

Mind Data Intelligence is Brian Ka Chan – Applied AI Strategist, Technology/Data/Analytics Executive, ex-Oracle Architect, ex-SAP Specialist. “Artificial intelligence for Everyone” is my vision about the channel. And it will also include fintech, smart cities, and all latest cutting edge technologies.

The goal of the channel to sharing AI & Machine Learning knowledge, expand common sense, and demystify AI Myths. We want everyone from all level of walks to understand Artificial Intelligence.

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AI Strategy Leader Brian Ka Chan is also the author of “Taming Artificial Intelligence: Mind-as-a-Service: The Actionable Human-Centric AI Evolution Blueprint for Individuals, Business”

Discover how CSP enables you to modernize your applications no matter where they are. Plus, learn how to undo human bias at scale with KubeFlow.

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In this talk Galina Shubina will draw on her experiences to discuss how implicit and explicit biases affect our daily lives, and how machine learning algorithms suffer from similar mindbugs.

Galina Shubina has a background in software engineering and all things data. She has two children, three citizenships, and way too many books. Galina has a Bachelors, a Masters, as well as an unfinished PhD in computer science and mathematics. Over a decade of her career was spent at Google and she currently runs her own one-person company. Galina is passionate about improving gender representation and happiness in the tech industry, and challenging herself and others to think outside their boxes in their work and daily lives.

This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at

SixArticles: Issue #8 AI and FutureOfWork

At Google researchers and engineers, have a goal to make machine learning technology work for everyone.

Through life changing accidents, and data minded through NASCAR, human beings are finding ways to rebuild one another so that we are better, faster, and stronger than ever before and all with the help of A.I.. Once nothing more than the stuff of comic books and TV shows, we truly have the technology to become modern superheroes.

The Age of A.I. is a 8 part documentary series hosted by Robert Downey Jr. covering the ways Artificial Intelligence, Machine Learning and Neural Networks will change the world.

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Paul Daugherty (BSE Computer Engineering, 1986) is Chief Technology & Innovation Officer at Accenture, where he oversees overall technology strategy, research and development, and ecosystem relationships, and is responsible for developing Accenture’s business in emerging technologies such as Artificial Intelligence, Cloud Computing, and Blockchain.

Daugherty is co-author of Human + Machine: Reimagining Work in the Age of Artificial Intelligence, a seminal book providing a much-needed management playbook for the business of AI, recently published by Harvard Press.

Max Tegmark Life 3.0 Being Human in the Age of Artificial Intelligence Part 02

In this video I will explain what the main differences are between the current approaches to artificial intelligence and human intelligence.

For this I first explain how neural networks work and in which sense they mimic the human brain.

I then go through the ten most relevant differences that are: Form and function, size, connectivity, power consumption, architecture, activation potential, speed, learning technique, structure, and precision.

Finally I express my opinion that the benefit of research in artificial intelligence is not the reproduce human-like intelligence, but instead to produce types of intelligence unlike our own that complement our own abilities.

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