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
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.
Part 01 - Will progress in Artificial Intelligence provide humanity with a boost of unprecedented strength to realize a better future, .
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.
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.
Stanford AI in Radiology overview 2018
Dr. Matthew Lungren
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.
Definition of a derivative
Differentiation examples & special cases
differentiate some functions
Time saving rules
Variables, constants & context
Differentiate with respect to anything
Jacobians - vectors of derivatives
The Sandpit -2
Multivariate chain rule
Simple neural networks
Visualising Taylor Series
Power series derivation
Power series details
Multivariable Taylor Series
Gradient descent in a sandpit
Simple 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
Jordan Etem: Driving Innovation
Jordan Etem: Driving Innovation
Jordan Etem: Driving Innovation
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.
Prediction Machines: The Simple Economics of Artificial Intelligence
Affiliate link Amazon UK - https://amzn.to/2LgIeUI
Professor Joshua Gans, Author “Prediction Machines”, Professor of Strategic Management at University of Toronto
Professor Walsh is a “rock star” of Australia’s digital revolution and a leading researcher in Artificial Intelligence.
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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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.
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.
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.
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
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.
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.
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.