The aim of Artificial Intelligence is to create intelligent machines. Creating intelligent agents would be the biggest event in human history or perhaps the very last. This talk will be about the process of creating intelligent machines, some Artificial Intelligence successes and challenges, and the future

Kamal Fataliyev is a software developer and entrepreneur. He is also an adjunct instructor at two universities in Azerbaijan. He has been working with Artificial Intelligence methods and applications for some years.

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

Jos Polflietin presentaatio SFD18-tapahtumassa. Presentaatio ladattavissa PDF-muodossa: https://screenforce.fi/etusivu/sfd18/

Jamal will discuss his research explaining why diversity and collaboration are of utmost importance for machines that learn about our world using AI.

Jamal is passionate about designing artificial intelligence (AI) for real-world applications. His Ph.D. in Computer Science at Michigan State University was focused on designing and investigating Al techniques for medical data analysis. He has presented his research at various national and international venues.

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

Jamal will discuss his research explaining why diversity and collaboration are of utmost importance for machines that learn about our world using AI.

Jamal is passionate about designing artificial intelligence (AI) for real-world applications. His Ph.D. in Computer Science at Michigan State University was focused on designing and investigating Al techniques for medical data analysis. He has presented his research at various national and international venues.

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

Part 01 - Will progress in Artificial Intelligence provide humanity with a boost of unprecedented strength to realize a better future, .

Part 02 - Will progress in Artificial Intelligence provide humanity with a boost of unprecedented strength to realize a better future, .

The ASU Origins Project is a transdisciplinary initiative that nurtures research, energizes teaching, and builds partnerships, offering new possibilities for .

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 https://www.ted.com/tedx

Ten years ago, researchers thought that getting a computer to tell the difference between a cat and a dog would be almost impossible. Today, computer vision systems do it with greater than 99 percent accuracy. How? Joseph Redmon works on the YOLO (You Only Look Once) system, an open-source method of object detection that can identify objects in images and video -- from zebras to stop signs -- with lightning-quick speed. In a remarkable live demo, Redmon shows off this important step forward for applications like self-driving cars, robotics and even cancer detection.

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The TED Talks channel features the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and more.

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Godfather of artificial intelligence Geoffrey Hinton gives an overview of the foundations of deep learning. In this talk, Hinton breaks down the advances of neural networks, as applied to speech and object recognition, image segmentation and reading or generating natural written language.

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Stanford AI in Radiology overview 2018
Dr. Matthew Lungren
aimi.stanford.edu
@mattlungrenMD

This course offers a brief introduction to the multivariate calculus required to build many common machine learning techniques. We start at the very beginning with a refresher on the “rise over run” formulation of a slope, before converting this to the formal definition of the gradient of a function. We then start to build up a set of tools for making calculus easier and faster. Next, we learn how to calculate vectors that point up hill on multidimensional surfaces and even put this into action using an interactive game. We take a look at how we can use calculus to build approximations to functions, as well as helping us to quantify how accurate we should expect those approximations to be. We also spend some time talking about where calculus comes up in the training of neural networks, before finally showing you how it is applied in linear regression models. This course is intended to offer an intuitive understanding of calculus, as well as the language necessary to look concepts up yourselves when you get stuck. Hopefully, without going into too much detail, you’ll still come away with the confidence to dive into some more focused machine learning courses in future.
Who is this class for: This class is for people who would like to learn more about machine learning techniques, but don’t currently have the fundamental mathematics in place to go into much detail. This course will include some exercises that require you to work with code. If you've not had much experience with code before DON'T PANIC, we will give you lots of guidance as you go.
Topic Covered:
Fuctions
Definition of a derivative
Differentiation examples & special cases
differentiate some functions
Time saving rules
Product rule
Chain rule
Variables, constants & context
Differentiate with respect to anything
Jacobians - vectors of derivatives
Jacobian applied
The Sandpit
The Sandpit -2
The Hessian
Multivariate chain rule
Neural Networks
Simple neural networks
Power series
Visualising Taylor Series
Power series derivation
Power series details
Multivariable Taylor Series
Linearisation
Multivariate Taylor
Gradient Descent
Gradient descent in a sandpit
Lagrange multipliers
Constrained optimisation
Simple linear regression
Non-linear regression
******************************************************************
This course is created by Imperial College London
If you like this video and course explanation feel free to take the
complete course and get certificate from: https://www.coursera.org/specializations/mathematics-machine-learning

This video is provided here for research and educational purposes in the field of Mathematics. No copyright infringement intended. If you are content owner would like to remove this video from YouTube, Please contact me through email: ict_hanif@yahoo.com
*******************************************************************

Prediction Machines: The Simple Economics of Artificial Intelligence,” discusses how AI could help business professionals make better decisions. The Inc. Tank is hosted by The Ed Snider Center at the Robert H. Smith School of Business.
You can also catch full episodes of The Inc. Tank at http://www.theinctank.org and on Spotify, Apple, Google Play and Stitcher.

Joshua Gans, Prediction Machines
Joshua Gans is the author of Prediction Machines: The Simple Economics of Artificial Intelligence. He talks with Megan Morrone about how Artificial Intelligence is changing our economy.

Download or subscribe to this show at https://twit.tv/shows/triangulation.

Prediction Machines: The Simple Economics of Artificial Intelligence
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By: Ajay Agrawal, Joshua Gans, Avi Goldfarb
Narrated by: LJ Ganser

"What does AI mean for your business? Read this book to find out." (Hal Varian, Chief Economist, Google)

Artificial intelligence does the seemingly impossible, magically bringing machines to life - driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.

But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.

When AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity - operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete.

Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

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Professor Joshua Gans, Author “Prediction Machines”, Professor of Strategic Management at University of Toronto

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#cogx18 (edited)

An introduction to the thesis and themes in the book, Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal, Joshua Gans and Avi Goldfarb. For more visit predictionmachines.ai.

Professor Walsh is a “rock star” of Australia’s digital revolution and a leading researcher in Artificial Intelligence.

‘Bots behaving badly: In his TEDxBlighStreet talk, Toby speaks about ‘good old-fashioned bad behaviour’ in a thoroughly modern context, and the ethical implications of Artificial Intelligence.

He is Scientia Professor of Artificial Intelligence at UNSW, leads the Algorithmic Decision Theory group at Data61, Australia's Centre of Excellence for ICT Research, and is Guest Professor at TU Berlin. He has been elected a fellow of the Australian Academy of Science, and has won the prestigious Humboldt research award as well as the NSW Premier's Prize for Excellence in Engineering and ICT.
Toby Walsh is a leading researcher in Artificial Intelligence. He was named by the Australian newspaper as a "rock star" of Australia's digital revolution. He is Scientia Professor of Artificial Intelligence at UNSW, leads the Algorithmic Decision Theory group at Data61, Australia's Centre of Excellence for ICT Research, and is Guest Professor at TU Berlin. He has been elected a fellow of the Australian Academy of Science, and has won the prestigious Humboldt research award as well as the NSW Premier's Prize for Excellence in Engineering and ICT. He has previously held research positions in England, Scotland, France, Germany, Italy, Ireland and Sweden. 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

CeBIT Global Conferences - 23 March 2017: Keynote "What AI can (and can't) do" / Toby Walsh, UNSW Australia, Data61, TU Berlin
http://bit.ly/2nqZrDv

Guo talks about how artificial intelligence will revolutionize how we approach the most basic questions of political philosophy. Our history of assumptions about human nature, existence, and civil society will be turned on its head and artificial intelligence will play a drastic role in how our world changes. Chelsea Guo is a senior at Yale completing a four-year joint B.S./M.S. degree in Molecular, Cellular, and Developmental Biology and a B.A. in Political Science. At Yale, she is a first-year counselor in Pauli Murray College, an undergraduate researcher at the Yale Stem Cell Center, the president of the Women's Leadership Initiative, and the AI Discussion Group leader for Yale Effective Altruists. Her interests lie at the intersection of science, technology, philosophy, and political theory. After graduating, she plans to pursue a Ph.D. in political theory and a J.D. in international law. 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

Is the fear of job less going to be an inhibitor in the growth of augemnted and artifical intelligence? Are there any lessons to be learned from augmenting human intelligence?
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James Hewitt is a speaker, author & performance scientist. His areas of expertise include the ‘future of work’, human wellbeing & performance in a digitally disrupted world & methods to facilitate more sustainable high-performance for knowledge workers.

Karina Vold specializes in Philosophy of Mind and Philosophy of Cognitive Science. She received her bachelor’s degree in Philosophy and Political Science from the University of Toronto and her PhD in Philosophy from McGill University. An award from the Social Sciences and Humanities Research Council of Canada helped support her doctoral research. She has been a visiting scholar at Ruhr University, a fellow at Duke University, and a lecturer at Carleton University.

Martha Imprialou is a Principal Data Scientist at QuantumBlack.

Watch the presentations: https://youtu.be/JmUFAGgKqjs

This event was supported by QuantumBlack and was filmed in the Ri at 16 May 2018.

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Ginni Rometty, the Chief Executive Officer of IBM, sits down with Fareed Zakria to discuss artificial intelligence and what it means for the future of work. We should be clear about the purpose of these technologies, says Rometty, and they should be in the service of mankind. The conversation was originally published on January 18, 2017.

augmented reality demo in Virtools
In this demo, each marker has a label with the number id (1,2,3,4), the character runs through all the bases (like baseball game)in numeric order, even if the markers are moved in real-time.
Theres two types of obstacles, one he can jump over , other he can’t, that he can recognize in real-time.

Não consigo passar – I can’t pass through! (english)

http://movlab.ulusofona.pt

Watch my keynote presentation from the Arvato Xperience Day in Berlin in September 2017. It was a great event with participants from leading international fashion brands.

This talk covers:
-consumer expectations in 2018 (frictionless shopping)
-how Amazon is eating all of retail with its Amazon Prime (Now) programme
-how direct to consumer brands like Warby Parker and Away Travel offer much better value for money by cutting out the middlemen
-how offline retail has to change if it doesn't want to die
-how brands have to embrace big data (example: Stitchfix)
-how brands can use Amazon Echo, Augmented Reality and chatbots to improve the customer experience
-the importance of mobile payment methods such as Apple Pay and WeChat Pay

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We interact with the digital world through PCs and smartphone screens. According to Robert Scoble and Shel Israel, renowned authors of the new book “The Fourth Transformation,” that’s about to change dramatically as head-mounted virtual interfaces (VR), powered by artificial intelligence A.I. and machine learning, will immerse us in digital worlds. You’ll rethink every part of your digital strategy once you see the world through Scoble and Israel’s virtual reality goggles.

Michael Krigsman is an industry analyst and the host of CXOTALK

For more information: https://www.cxotalk.com/episode/augmented-reality-artificial-intelligence
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From the transcript:

(04:39) Shel Israel, why does this all matter? What are the implications?

Shel Israel:

(04:48) Well, that gets to the core of the Fourth Transformation. I’m not going to walk through the whole thing, but in the First Transformation, we started with putting words into PCs, on knowledge worker desktops, in the form of personal computers. Then, we went to point-and-click with the McIntosh, and that meant everyone could use these desktop things. Then, we went to touch and mobility, and that brought us into what is now this third transformation where anyone is using digital technology everywhere. Now, we’re going to go to a system which is much more intimate than what we have with phones. We’re going to have things in a few years that look like glasses I’m wearing. And, they are going to allow us to do all the things that I had just named: MR, AR, VR; and we’re not going to look freakish, and we’re not going to be tethered to anything.

(05:56) This means that the customer experience in stores is going to be changed because they can do things in 3D. They will walk into stores, be at home, and have an immersive experience with the product.

Robert Scoble:

(10:48) Sensors that are seen around the world, that is billions of dollars for R&D, right? IM-Sense was bought by Apple. Google Tango is doing the same kinds of research, Meta is doing the same kind of … Everybody who wants to build a mixed reality glass has to build sensors to see the world in 3D and bring it into the glass. Then, you talk about the connectivity that you're going to need, right? Because with mixed reality glasses, you get as many TV screens around you as you want. So imagine being able to watch CNN here; here, ESPN is playing; and over here, you can watch your security cameras from your business; and over here, you can watch Amazon servers; and over here, you can watch Facebook. You just look around, you have dozens of screens all around you, and you don't have to buy more if you want more screens.

(11:42) But, to serve all those screens with hi-res 4K or 8K video, or eventually even more in the future, you’re going to need a lot of bandwidth, and that’s 5G. 5G brings 35 gigabits per seconds down to the glasses, but we don't yet have 5G and we're going to … And, Verizon has to re-do the architecture on a city, because the cell tower needs to be a kilometer and a half from you or closer, and that's not true with today's cell technology. You can be 15 kilometers away. So, they need to put a lot more cell towers into a city and they put fiber into each one of those antennas, so it's going to bring us 5G. That's coming this year, right? Verizon is turning on the first 11 cities this year. And that's really […]

(12:29) You go through the GPU; the GPU is needed to display the polygon. So, when you are seeing virtual things in VR or AR, you're seeing millions of little polygons or little triangles that are underneath what you're seeing; and you'll need a better GPU to process more of those. So, if you want to increase the resolution or increase the frame rates, or increase the experience of being immersed in the media, you need more GPU; or, you need to do a lot of trickery with […] rendering. And you look at the R&D budgets of NVidia, and AMD, and Qualcomm, and [Mallway], and other companies that are building these chips; they are spending billions of dollars per quarter in R&D.

(13:10) Then you keep looking around; there are companies that are building eye sensors. GoogleBot, Eyefluence that’s in our book, Facebook product company called Eye Tribe; there is lots of money spent on that, and particularly in the new user interfaces that you’re experiencing when you get a glass like this. They’re investing that.

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 .

A revolution in AI is occurring thanks to progress in deep learning. How far are we towards the goal of achieving human-level AI? What are some of the main .

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

Stuart Russell argues for a fundamental reorientation of the field artificial intelligence. Click here to watch the full keynote http://oreil.ly/1YSpwEh

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Stuart Russell is a professor of Computer Science at UC Berkeley as well as co-author of the most popular textbook in the field – Artificial Intelligence: A Modern Approach. Given that it has been translated into 13 languages and is used in more than 1,300 universities in 118 countries, I can hardly think of anyone more qualified or more appropriate to discuss issues related to AI or the technological singularity. Unfortunately, we had problems with our internet connection and, consequently, the video recording is among the worst I have ever published. Thus this episode may be a good candidate to listen to as an audio file only. However, given how prominent Prof. Russel is and how generous he was with his time, I thought it would be a sad loss if I didn’t publish the video also, poor quality as it is.

During our 90 min conversation with Stuart Russell we cover a variety of interesting topics such as: his love for physics and computer science; human preferences, expected utility and decision making; why his textbook on AI was “unreasonably successful”; his dream that AI will contribute to a Golden Age of Humanity; aligning human and AI objectives; the proper definition of Artificial Intelligence; Machine Learning vs Deep Learning; debugging and the King Midas problem; the control problem and Russell’s 3 Laws; provably safe mathematical systems and the nature of intelligence; the technological singularity; Artificial General Intelligence and consciousness…

As always you can listen to or download the audio file above or scroll down and watch the video interview in full. To show your support you can write a review on iTunes, make a direct donation or become a patron on Patreon.

https://www.singularityweblog.com/stuart-russell/

How can we harness the power of superintelligent AI while also preventing the catastrophe of robotic takeover? As we move closer toward creating all-knowing machines, AI pioneer Stuart Russell is working on something a bit different: robots with uncertainty. Hear his vision for human-compatible AI that can solve problems using common sense, altruism and other human values.

Recorded August, 2017

Stuart Russell is a computer scientist known for his contributions to artificial intelligence.
Link to the following panel discussion: https://www.youtube.com/watch?v=fIGLvsfgxDg

The National Academies of Sciences, Engineering, and Medicine organized a half-day colloquium on artificial intelligence and its implications for U.S. interests on August 7, 2017.

Presented at the 2016 Colloquium Series on Robust and Beneficial AI (CSRBAI) hosted by the Machine Intelligence Research Institute (MIRI) and Oxford's Future of Humanity Institute (FHI). https://intelligence.org/colloquium-series/

Today, we are looking a the largest artificial intelligence companies in China. You might not know, but China is on the cutting edge of Artificial Intelligence and we wanted to look at some of the leading companies. So, let’s just jump right in with number 5.

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