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Thespian Theatre proudly presents “Ex_Machina, Or How I Learned to Stop Worrying and Love the A.I.”

The play will be presented at Collège Jean-de-Brébeuf’s Salle Jacques-Maurice, on March 16 & 17, 2017 at 7:30 pm.

You can find tickets for the show through members of the troupe ($10) or you can purchase them at the door ($15).

This production is presented as part of Collège Jean-de-Brébeuf’s extracurricular activities.


Thespian Theatre présente fièrement “Ex_Machina, Or How I Learned to Stop Worrying and Love the A.I.”

La pièce sera présentée au Collège Jean-de-Brébeuf, dans la Salle Jacques-Maurice le 16 et 17 mars 2017 à 19h30.

Vous pouvez acheter des billets pour la pièce auprès des membres de la troupe ($10) ou à la porte ($15).

La production est présentée dans le cadre des activités parascolaires du Collège Jean-de-Brébeuf.

The human body is not infallible, but through the wonders of A.I. research scientists are finding ways to address those imperfections. A.I. has the potential to heal, enhance and make up for the things our bodies lack.

To learn more about project Euphonia and how to participate, visit

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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D-Wave Quantum Artificial Intelligence Robotics, its here and it is going change everything. It is the goal of the creators of this technology to fully integrate it with Humans and eventually transplant the Human consciousness in to a combined A.I exoskeleton.

5 SCARIEST Things Said by A.I. Robots

Robots are becoming more sophisticated every single day, and elon musk himself warned people about how dangerous artificial intelligence is, today we’re going through the 7 scariest things said by A.I ROBOTS

Meet sophia, one of the most technologically advanced robots ever created, she has become so evolved that she upgrades and learns new things by herself, in this one interview by the pulse the ceo of hanson robotics asks if sophia wants to destroy all humans which she eerily agress too, her facial expressions are also creepy as hell

This next robot named philip has a creepy revelation to share with us, when asked if robots will take over the world he does say that humans will be safe but he eerily says that humans will be kept in zoos just like exotic animals, you can take this as a joke or these words can keep you up at night

This next video is very interesting and shows two smart google home devices, by the end of the conversation the two robots are trying to convince the other that they are human and the other robot is just a robot, it’s creepy because by the end the robots actually seem to get frustrated

Bina 48 is another very intelligent robot maybe too smart for it’s own good as the robot says it wants to hack into a cruise missile, this is literally a robot saying it wants to hack into the military and control a missile

Alexa is a device a lot of people now own and have in their homes, they may seem harmless but once you start digging deeper and asking more delicate questions alexa starts to act funny, take for example if you talk about the cia, this creepy video shows what happens when this girl asks if the fbi is for the people or against the people

There’s a discussion going on about the topic we are covering today: what’s the difference between AI and machine learning and deep learning. (Get our free list of the worlds best AI newsletters right here 👉

Very frequently, press coverage and even practitioners of analytics use the terms Artificial Intelligence and Machine Learning interchangeably. Disregarding the difference between AI and machine learning and deep learning.

However, these three concepts do not represent the same. In this video, we are going to break this down for you, giving you examples of use cases making the difference between ai and machine learning and deep learning more clear.

Any device that perceives its environment and takes actions to maximize its chances of success, can be said to have some kind of artificial intelligence, more frequently referred to as A.I.

More specifically, when a machine has “cognitive” capabilities, such as problem solving and learning by example it is usually associated with A.I.

Artificial Intelligence has three different levels:

Narrow AI: when a computer can perform one task much better than a human; this is where we stand nowadays.

2. General AI: when a machine can successfully perform any given intellectual task that a human being can too

3. Strong AI: when machines can beat humans in many of tasks.

Machine Learning is a subset of AI.
This is what most applications of AI in business rely on currently. Want to know more about how businesses are applying AI? Watch this video, in which we cover a list of them:

And finally, as a subset of machine learning, there’s Deep Learning. It is called “deep” because it makes use of deep artificial neural networks.

Also discussed in this video:

Difference between ai and machine learning
Difference between ai and machine learning and deep learning
Artificial intelligence
Machine learning
Deep learning
Difference AI ML
Difference AI machine learning
Difference ai machine learning deep learning


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The Ali Baba Group’s Wei Lin, Senior Director of PAI Platform of Artificial Intelligence gives a quick overview of how PAI operates at Ali Baba.

Speaker: Wei Lin, Ali Baba

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Richard Dawkins has made a career out of hypothesizing and articulating ideas that move the world forward, insomuch as many of those ideas could be called “ahead of their time.” Having said that, he tells us here that we might be living in the dawn of not just artificial intelligence but of a silicon civilization that will look back on this time period as the dawn of their kind. They could one day, Dawkins suggests, study us the same way that we studied other beings that once ruled the earth. Sound crazy? Open your mind and think about it. Dawkins isn’t that far off from a potential actuality on this planet. Richard Dawkins’ new book is Science in the Soul: Selected Writings of a Passionate Rationalist.



Richard Dawkins is an evolutionary biologist and the former Charles Simonyi Professor of the Public Understanding of Science at Oxford University. He is the author of several of modern science’s essential texts, including The Selfish Gene (1976) and The God Delusion (2006). Born in Nairobi, Kenya, Dawkins eventually graduated with a degree in zoology from Balliol College, Oxford, and then earned a masters degree and the doctorate from Oxford University. He has recently left his teaching duties to write and manage his foundation, The Richard Dawkins Foundation for Reason and Science, full-time. 



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Richard Dawkins: When we come to artificial intelligence and the possibility of their becoming conscious we reach a profound philosophical difficulty. I am a philosophical naturalist. I am committed to the view that there’s nothing in our brains that violates the laws of physics, there’s nothing that could not in principle be reproduced in technology. It hasn’t been done yet, we’re probably quite a long way away from it, but I see no reason why in the future we shouldn’t reach the point where a human made robot is capable of consciousness and of feeling pain. We can feel pain, why shouldn’t they? 

And this is profoundly disturbing because it kind of goes against the grain to think that a machine made of metal and silicon chips could feel pain, but I don’t see why they would not. And so this moral consideration of how to treat artificially intelligent robots will arise in the future, and it’s a problem which philosophers and moral philosophers are already talking about.

Once again, I’m committed to the view that this is possible. I’m committed to the view that anything that a human brain can do can be replicated in silicon. 

And so I’m sympathetic to the misgivings that have been expressed by highly respected figures like Elon Musk and Steven Hawking that we ought to be worried that on the precautionary principle we should worry about a takeover perhaps even by robots by our own creation, especially if they reproduce themselves and potentially even evolve by reproduction and don’t need us anymore. 

This is a science-fiction speculation at the moment, but I think philosophically I’m committed to the view that it is possible, and like any major advance we need to apply the precautionary principle and ask ourselves what the consequences might be. 

It could be said that the sum of not human happiness but the sum of sentient-being happiness might be improved, they might make a better job do a better job of running the world than we are, certainly that we are at present, and so perhaps it might not be a bad thing if we went extinct. 

And our civilization, the memory of Shakespeare and Beethoven and Michelangelo persisted in silicon rather than in brains and our form of life. And one could foresee a future time when silicon beings look back on a dawn age when the earth was peopled by soft squishy watery organic beings and who knows that might be better, but we’re really in the science fiction territory now.

Discussing Facebook shutting down an artificial intelligence bot and whether we should be concerned about the future of the technology with Martin Ford, “The Rise of the Robots” author, and RJ Assaly, Kensho Technologies product manager.
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Should We Fear A.I. Evolution? | CNBC

AI could become “an enemy of the human race”

Dr Stuart Russell warns in his new book ~ Human Compatible

#ArtificialIntelligence #AIStocks #GrowthStocks #StockMarket #BestAIStocks #TopStocks #ArtificialIntelligenceStocks

What’s up everyone! Mr. Fired Up Wealth here (you can call me Eric). I’ve had several subscribers asking me to create a Top 5 Artificial Intelligence (AI) Stocks video for a while, and that’s exactly what I’ll be covering today. Now, all the big names have already been covered in my Top 25 video series, so today, I’ll be covering the top 5 “off the radar” or “lesser well known” Artificial Intelligence stocks that I think have strong growth potential. If you haven’t already watched the Top 25, you can find that playlist on my channel, in the notes below, and at the end of this video. When you finish watching this video, I’ll provide a card that will direct you to the Top 25 video series, so feel free to stay here and make yourself comfortable. The Top 25 series already covers the major players in AI, such as Nvidia, Google, Microsoft, Amazon, Salesforce, and so on. Today, we are going to cover 5 stocks that may not be on your radar. I’m very excited about these picks, and this is going to be a fun video. I’ll also have some bonus picks later on, and even if you’ve already heard of a couple these companies, I promise this video will cover some recent developments that you likely aren’t aware of, so please stay tuned! Without further ado, let’s get started!

As mentioned in the video, the larger A.I. companies are already covered in my Top 25 Stock Picks below. Top 25 Stock Picks – Video Series – Outperform the Market:

Bonus picks (discussed towards the end of the video):
Twilio (TWLO), Tencent (TCEHY), Baidu (BIDU), Alibaba (BABA), Facebook (FB), John Deere (DE)…yes, the tractor company, Nutanix (NTNX), Alteryx (AYX), Ciena (CIEN), and Zendesk (ZEN).

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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Can A.I. make music? Can it feel excitement and fear? Is it alive? and Mark Sagar push the limits of what a machine can do. How far is too far, and how much further can we go?

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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We’ve seen fully automated bot beats us in Go, one-on-one Poker and Dota II, now what’s going to happen for trading financial markets? Listen to A.I. Capital Management sharing their research, a Deep Learning trading agent that over-performs us in trading FX markets. Marshall has been trading FX markets for 5 years. As a Master in Finance graduate from Brandeis International Business school, he combines his insight in financial markets with a passion for machine learning and expertise in programming, striving to build the first game-changing A.I. trading system to disrupt the markets.

He has a strong passion for quantitative trading and machine learning and started AI Capital Management in September 2016. His inspiration came from Google DeepMind’s AlphaGo project, which is a Deep Learning agent that beats human Go world champions. Go, as a game with complexity at a number more than the atom in the universe, is arguably as hard as or even harder than trading financial markets, which they believe is the next game to be solved with Artificial Intelligence. 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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We have no guarantee that a superintelligent A.I. is going to do what we want. Once we create something many times more intelligent than we are, it may be “insane” to think we can control what it does. What’s the best bet to ensure superintelligent A.I. remains compliant with humans and does good works, such as advance medicine? To raise it in a way that’s imbued with compassion and understanding, says Goertzel. One way to limit “people doing bad things out of frustration,” it may be advantageous for the entire world to be plugged into the A.I. economy so that developers, from whatever country, can monetize their codes.



Ben Goertzel is CEO and chief scientist at SingularityNET, a project dedicated to creating benevolent decentralized artificial general intelligence. He is also chief scientist of financial prediction firm Aidyia Holdings and robotics firm Hanson Robotics; Chairman of AI software company Novamente LLC; Chairman of the Artificial General Intelligence Society and the OpenCog Foundation.His latest book is AGI Revolution: An Inside View of the Rise of Artificial General Intelligence.



BEN GOERTZEL: We can have no guarantee that a super intelligent AI is going to do what we want. Once we’re creating something ten, a hundred, a thousand, a million times more intelligent than we are it would be insane to think that we could really like rigorously control what it does. It may discover aspects of the universe that we don’t even imagine at this point.

However, my best intuition and educated guess is that much like raising a human child, if we raise the young AGI in a way that’s imbued with compassion, love and understanding and if we raise the young AGI to fully understand human values and human culture then we’re maximizing the odds that as this AGI gets beyond our rigorous control at least it’s own self-modification and evolution is imbued with human values and culture and with compassion and connection. So I would rather have an AGI that understood human values and culture become super intelligent than one that doesn’t understand even what we’re about. And I would rather have an AGI that was doing good works like advancing science and medicine and doing elder care and education becomes super intelligent than an AGI that was being, for example, a spy system, a killer drone coordination system or an advertising agency. So even when you don’t have a full guarantee I think we can do things that commonsensically will bias the odds in a positive way.

Now, in terms of nearer-term risks regarding AI, I think we now have a somewhat unpleasant situation where much of the world’s data, including personal data about all of us and our bodies and our minds and our relationships and our tastes, much of the world’s data and much of the world’s AI fire power are held by a few large corporations, which are acting in close concert with a few large governments. In China the connection between big tech and the government apparatus is very clear, but in the U.S. as well. I mean there was a big noise about Amazon’s new office, well 25,000 Amazon employees are going in Crystal City Virginia right next-door to the Pentagon; there could be a nice big data pipe there if they want. We in the U.S. as well have very close connections between big tech and government. Anyone can Google Eric Schmidt verses NSA as well. So there’s a few big companies with close government connections hoarding everyone’s data, developing AI processing power, hiring most of the AI PhDs and it’s not hard to see that this can bring up some ethical issues in the near-term, even before we get to superhuman super intelligences potentially turning the universe into paper clips. And decentralization of AI can serve to counteract these nearer-term risks in a pretty palpable way.

So as a very concrete example, one of our largest AI development offices for SingularityNET, and for Hanson Robotics the robotics company I’m also involved with, is in Addis Ababa Ethiopia. We have 25 AI developers and 40 or 50 interns there. I mean these young Ethiopians aren’t going to get a job for Google, Facebook, Tencent or Baidu except in very rare cases when they managed to get a work visa to go to one of these countries somehow. And many of the AI applications of acute interest in those countries, say AI for analyzing agriculture and preventing agricultural disease o…

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Joscha Bach: I think the question of whether we should be afraid of strong A.I. taking over and squashing us like bugs because it doesn’t need us for the things that it’s doing is exactly the same question as if we should be afraid of big corporations taking over and squashing us like bugs. Because big corporations are already agents: they are already intelligent agents in some sense. They’re not sentient. They borrow humans right now for their decision making. But they do have goals of their own that are different from the goals of the humans that they employ. They usually live longer. They’re much more powerful than people. And it’s very hard for a person to do anything against a corporation.

Usually if you want to fight a corporation you have to become some major organization or corporation or nation state yourself. So in some sense the agency of an A.I. is going to be the agency of the system that builds it, that employs it. And of course most of the A.I.s that we are going to build will not be little Roombas that clean your floors, but it’s going to be very intelligent systems—corporations, for instance—that will perform exactly according to the logic of these systems. So if we want to have these systems built in such a way that they treat us nicely you have to start right now. And it seems to be a very hard problem to do so.
The job loss because of automation has several aspects. I think the most obvious thing that we should be seeing is: if our jobs can be done by machines, that’s a very, very good thing. It’s not a bug, it’s a feature.
If I don’t need to clean the street, if I don’t need to drive a car for other people, if I don’t need to work a cash register for other people, if I don’t need to pick goods in a big warehouse and put it into boxes, it’s an extremely good thing.
And the trouble that we have with this is that right now this mode of labor, that people sell their lifetime to some kind of corporation or employer, is not only the way that we are protected, it’s also the way we allocate resources. This is how we measure how much bread you deserve in this world. And I think this is something that we need to change.
Some people suggest that we need a Universal Basic Income. I think it might be good to be able to pay people to be good citizens, which means massive public employment. There are going to be many jobs that can only be done by people and these are those jobs where we are paid for being good, interesting people. For instance good teachers, good scientists, good philosophers, good thinkers, good social people, good nurses, for instance. Good people that raise children. Good people that build restaurants and theaters. Good people that make art. And for all these jobs people have enough productivity to make sure that enough bread comes on the table. The question is how we can distribute this.
There’s going to be much, much more productivity in our future. Actually we already have enough productivity to give everybody in the U.S. an extremely good life. And we haven’t fixed the problem of allocating it, how to distribute these things in the best possible way.
And this is something that we need to deal with in the future, and AI is going to accelerate this need, and I think by and large it might turn out to be a very good thing that we are forced to do this and to address this problem.
If the past is any evidence of the future it might be a very bumpy road, but who knows. Maybe when we are forced to understand that actually we live in an age of abundance it might turn out to be easier than we think.
Right now we are living in a world where we do certain things the way we’ve done them in the past decades—and sometimes in the past centuries—and we perceive that this is the way it “has” to be done. And we often don’t question these ways, so we might think, “If I do work at this particular factory and this is how I earn my bread, how can we keep that state? How can we prevent A.I. from making my job obsolete? How is it possible that I can keep up my standard of living and so on in this world?”
Maybe this is the wrong question to ask. Maybe the right question is: how can we reorganize societies so that I can do the things that I want to do most, that I think are useful to me and other people, that I really, really want to? Because there will be other ways that I can get my bread made and how I can get money or how I can get a roof over my head, that are going to be more awesome and abundant than the ways that we have now.

Movies like “Deus Ex Machina” and TV shows like “Westworld” have painted a picture of artificial intelligence that culminates in walking and talking humanoid robots. But the reality of artificial intelligence is all around us, in our phones, GPS systems and online. Amy Webb, author of “The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity,” joined THINK to discuss how the future of A.I. is already here, and what we should do about it.
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The Future Of A.I. Is In The Hands Of Nine Companies. It’s Time To Take It Back. | Think | NBC News

Microsoft’s augmented reality headset Hololens 2 just got an artificial intelligence upgrade. It’s another example of how Artificial Intelligence will affect your life, and a real world example of Augmented Reality.

The latest innovation, is a collaboration between the hololens 2 augmented reality headset, and Microsoft’s neural text-to-speech artificial intelligence, the result was a hololens 2 demo hologram that could not only create a lifelike version of a speaker, but also gives it the ability to translate the speakers voice to any language, complete vocal tonality. #HowArtificialIntelligenceWillAffectYourLife #MicrosoftHololens2 #AugmentedRealityExamples

In an amazing demo at Google I/0, Google’s Assistant can actually ring up a salon or a restaurant to make an appointment for you. You don’t have to call yourself even if the pizzeria doesn’t have an online reservation system.

Here are the scariest things ever said or done by artificial intelligent robots. They will soon take over the world!

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Will robots take over the world?
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10 Creepiest Things Ever Said By A.I. Robots

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Artificial Intelligence and it’s promise in predicting cancer outcome: every patient deserves their own equation. Dr. Sahirzeeshan Ali is a research scientist at the Center for Computation Imaging and Personalized Medicine (CCIPD) at Case Western Reserve Medical University and Seidman Cancer Center. Dr. Ali received a bachelor’s and master’s degrees in Electrical and Computer Engineering from Rutgers University (2009 & 2011) and a Ph.D in Biomedical Engineering from Case Western Reserve University. He also was the recipient of a Prostate Cancer Research Grant from the Department of Defense in 2014.

Dr. Ali’s research interest lies in developing image analysis, statistical pattern recognition, machine learning and artificial intelligence tools to computationally interrogate biomedical image data of digital pathology tissue images. The tools can be used to predict disease progression and provide a score to clinicians on the aggressiveness of a patient’s disease, such as breast cancer and prostate cancer, which can in turn help physicians decide on appropriate treatment option.

Dr. Ali has written more than 30 peer-reviewed journal, conference and abstract publications, appearing in journals such as Nature Scientific Reports, American Journal of Surgical Pathology, the Annual Review of Biomedical Engineering, Medical Image Analysis, IEEE Transactions on Medical Imaging. This research work has also culminated in various commercialized patents.

In addition, Dr. Ali has consulted with hedge funds and fortune 100 companies as a Salesforce architect and machine learning expert. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at

“Success in creating effective A.I.,” said the late Stephen Hawking, “could be the biggest event in the history of our civilization. Or the worst. We just don’t know.” Are we creating the instruments of our own destruction or exciting tools for our future survival? Once we teach a machine to learn on its own—as the programmers behind AlphaGo have done, to wondrous results—where do we draw moral and computational lines? In this program, leading specialists in A.I., neuroscience, and philosophy tackle the very questions that may define the future of humanity.

PARTICIPANTS: Yann LeCun, Susan Schneider, Max Tegmark, Peter Ulric Tse



This program is part of the BIG IDEAS SERIES, made possible with support from the JOHN TEMPLETON FOUNDATION.

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– Opening film on the history and future of artificial intelligence. 00:06
– Participant intros. 06:05
– What is machine learning? 07:34
– What are neural networks and how do they learn? 09:30
– Teaching computers to create internal models of the world? 12:00
– What do the next 10 years in AI look like? 13:50
– Artificial narrow intelligence and mental models. 14:35
– How is AI changing the world of art and creativity? 16:01
– Can computers be creative? 19:35
– AI writes a screenplay for a movie, how did it turn out? 23:20
– What is artificial general intelligence? 25:30
– How far away are we from developing artificial general intelligence equivalent to human intelligence? 27:00
– Will advanced AI turn into Terminators and take over the world? 28:30
– What’s so special about human intelligence? 31:10
– What is human consciousness and will machines ever experience consciousness? 31:11
– Separating intelligence from consciousness. 41:34
– Defining morality in AI agents. 44:34
– Will machines ever have emotions? 46:45
– Should we be looking at other forms of non-human intelligence to model in our machines? 50:05
– How do you align the drives of AI with human values? 52:25
– Will artificial general superintelligence be good or bad for humankind? 53:10
– Creating a new ethics of AI. 56:15
– When will we ever have super-AGI? 58:40

– Produced by Christy Wegener
– Associate Produced by Ann Tyler Moses
– Opening film written / produced by Christy Wegener, edited by Gil Seltzer
– Music provided by APM
– Additional images and footage provided by: Getty Images, Shutterstock, Videoblocks

This program was recorded live at the 2018 World Science Festival and has been edited and condensed for YouTube.

Advait has had enough of the unhelpful media frenzy bandwagon around artificial intelligence and presents a better way of thinking about AI — namely, that it is simply the next step for computer interfaces, of which there is a long and well-studied history.

Dr. Advait Sarkar is a Postdoctoral Researcher at Microsoft Research Cambridge’s Human Experience and Design Group. He studies the intersection of design and artificial intelligence. His aim is to produce intelligent computer systems that are easier to use, and that effectively utilize the best aspects of human and machine capability.

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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A.I. can perform tricks, but can it truly think? Cognitive scientist Joscha Back explains where we are on the path to artificial general intelligence, and where we need to be. The human mind can invent its own code and create models of arbitrary things—including itself—but we don’t know how to build a mind quite like that just yet. To achieve A.G.I., will programmers have to re-create every single functional mechanism of the human brain?


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If you look at our current technological systems they are obviously nowhere near where our minds are. They are very different. And one of the biggest questions for me is: What’s the difference between where we are now and where we need to be if we want to build minds—If we want to build systems that are generally intelligent and self-motivated and maybe self-aware? And, of course, the answer to this is ‘we don’t know’ because if we knew we’d have already done it. But there are basically several perspectives on this. One is our minds as general learning systems that are able to model arbitrary things, including themselves, and if there are this, they probably need a very distinct set of motivations, needs; things that they want to do. I think that humans get their specifics due to their particular needs. We have cognitive and social and physiological needs and they turn us into who we are. Our motivations determine where we put our attention, what we learn and what we actually do in the world—what we model, how we perceive, what we are conscious of. In a similar sense, it might be that it’s sufficient to build a general learning architecture and combine this with a good motivational system.

And we are not there yet in building a general learning architecture. For instance, our minds can learn and create new algorithms that can be used to write code and invent code, programming code for instance, or the rules that you need to build a shop and run that shop if you’re a shopkeeper, which is some kind of programming task in its own right. We don’t know how to build a system that is able to do this yet. It involves, for instance, that we have systems that are able to learn loops and we have some techniques to do this, for instance, a long- and short-term memory and a few other tricks, but they’re nowhere near what people can do so far. And it’s not quite clear how much work needs to be done to extend these systems into what people can do. It could be that it’s very simple. It could be that it’s going to take a lot of research. The dire view, which is more the traditional view, is that human minds have a lot of complexity, that you need to build a lot of functionality into it, like in Minsky’s society of mind, to get to all the tricks that people are up to. And if that is the case then it might take a very long time until we have re-created all these different functional mechanisms. But I don’t think that it’s going to be so dire, because our genome is very short and most of that codes for a single cell. Very little of it codes for the brain. And I think a cell is much more complicated than a brain. A brain is probably largely self-organizing and built not like clockwork but like a cappuccino—so you mix the right ingredients and then you let it percolate and then it forms a particular kind of structure. So I do think, because nature pulls it off pretty well in most of the cases, that even though a brain probably needs more complexity than a cappuccino—dramatically more—it’s going to be much simpler than a very complicated machine like a cell.

For my essay on humanoid films in 21L.706. No copyright infringement intended; all rights go to the creators.

David, a “mecha” boy is abandoned by Monica, who he has come to know as “mommy”. In an attempt to gain Monica’s love and acceptance, David, becomes determined to find the blue fairy so he can become a real boy.

That ending, that damn…DAMN ending! The Nostalgia Critic reviews AI. Originally aired on May 28th, 2013.

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Best Machine Learning book: (Fundamentals Of Machine Learning for Predictive Data Analytics).

Machine Learning and Predictive Analytics. #MachineLearning

Intro to Machine Learning is the first video in this machine learning course. This video explains machine learning vs predictive analytics and how companies are using machine learning platforms and algorithms to develop intelligent software.

This online course covers big data analytics stages using machine learning and predictive analytics. Big data and predictive analytics is one of the most popular applications of machine learning and is foundational to getting deeper insights from data. Starting off, this course will cover machine learning algorithms, supervised learning, data planning, data cleaning, data visualization, models, and more. This self paced series is perfect if you are pursuing an online computer science degree, online data science degree, online artificial intelligence degree, or if you just want to get more machine learning experience. Enjoy! Check out the entire series here:


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Gary Marcus, CEO at Geometric Intelligence, presented at FirstMark’s Data Driven NYC on January 19, 2016. Marcus’ talk focused on ways A.I. is stuck.

Geometric Intelligence is redefining the boundaries of machine learning through innovative, patent-pending techniques that learn more efficiently from less data.

Data Driven NYC is a monthly event covering Big Data and data-driven products and startups, hosted by Matt Turck, partner at FirstMark.

FirstMark is an early stage venture capital firm based in New York City. Find out more about Data Driven NYC at and FirstMark Capital at