By Meg Murphy K. Daron Acemoglu, the Elizabeth and James Killian Professor of Economics at MIT, is a leading thinker on the labor market implications of artificial intelligence, robotics, automation, and new technologies. His innovative work challenges the way people think about these technologies intersect with the world of work. In 2005, he won the John Bates Clark Medal, an honor shared by a number of Nobel Prize recipients and luminaries in the field of economics. Acemoglu holds a bachelor's degree in economics from University of York. His master's degree in mathematical economics and econometrics and doctorate in economics are from the London School of Economics.

Where is China headed in 2018? President Xi Jinping promised "world peace" for the new year - but his 2017 track record suggests otherwise. Remember the singular stain of the July death of 2010 Nobel Peace Prize winner Liu Xiaobo, surrounded by state security? Many condemned China's conduct, but such interventions are fewer and further between these days. Increasingly, abusive Chinese authorities are garnering international support for their principles and policies.

K. Daron Acemoglu, the Elizabeth and James Killian Professor of Economics at MIT, is a leading thinker on the labor market implications of artificial intelligence, robotics, automation, and new technologies. His innovative work challenges the way people think about these technologies intersect with the world of work. In 2005, he won the John Bates Clark Medal, an honor shared by a number of Nobel Prize recipients and luminaries in the field of economics. Acemoglu holds a bachelor's degree in economics from University of York. His master's degree in mathematical economics and econometrics and doctorate in economics are from the London School of Economics.

At the recent Pocket Gamer Connects London 2018 on January 22nd and 23rd, Wappier CEO Alex Moukastook to the stage for his talk entitled: 'Don't do it like a virgin – Automated revenue management in gaming'. In the talk he discussed how the mobile gaming world could experience in-app purchase revenue boosts of as much as 50 per cent by adopting automated revenue management systems and practices. This means using machine learning, predictive analytics and deep data pooling to maximise life time value. To find out more about Wappier and the topic of his talk, we caught up with Moukas to guide us through automated revenue management. Could you please explain what services wappier provides?

Many practical machine learning tasks employ very deep convolutional neural networks. Such large depths pose formidable computational challenges in training and operating the network. It is therefore important to understand how fast the energy contained in the propagated signals (a.k.a. feature maps) decays across layers. In addition, it is desirable that the feature extractor generated by the network be informative in the sense of the only signal mapping to the all-zeros feature vector being the zero input signal. This "trivial null-set" property can be accomplished by asking for "energy conservation" in the sense of the energy in the feature vector being proportional to that of the corresponding input signal. This paper establishes conditions for energy conservation (and thus for a trivial null-set) for a wide class of deep convolutional neural network-based feature extractors and characterizes corresponding feature map energy decay rates. Specifically, we consider general scattering networks employing the modulus non-linearity and we find that under mild analyticity and high-pass conditions on the filters (which encompass, inter alia, various constructions of Weyl-Heisenberg filters, wavelets, ridgelets, ($\alpha$)-curvelets, and shearlets) the feature map energy decays at least polynomially fast. For broad families of wavelets and Weyl-Heisenberg filters, the guaranteed decay rate is shown to be exponential. Moreover, we provide handy estimates of the number of layers needed to have at least $((1-\varepsilon)\cdot 100)\%$ of the input signal energy be contained in the feature vector.

Insights into the new computing model DEEP LEARNING TOP 5 October 6, 2017 DEEP LEARNING IS THE FASTEST-GROWING FIELD IN ARTIFICIAL INTELLIGENCE (AI) AS AI TECHNOLOGIES CONTINUE TO IMPROVE, MORE COMPANIES ADOPT DEEP LEARNING TO ACCELERATE THEIR BUSINESSES… TOP 5 1. Gartner releases the top 10 strategic technology trends for 2018 2. Oracle adds GPU Accelerated Computing to Oracle Cloud Infrastructure 3. Chemistry and physics Nobel Prizes awarded to teams supported by GPUs 4. MIT uses deep learning to help guide decisions in ICU 5. Portfolio management firms are using AI to seek alpha GARTNER RELEASES THE TOP 10 STRATEGIC TECH TRENDS FOR 2018 Gartner, Inc. announced its top strategic tech trends and predictions at the 2017 Gartner Symposium this week. "The first three strategic tech trends explore how AI and machine learning are seeping into virtually everything and represent a major battleground for technology providers over the next five years. READ ARTICLE ORACLE ADDS GPU ACCELERATED COMPUTING TO ORACLE CLOUD INFRASTRUCTURE Oracle announced at Oracle OpenWorld this week it is now offering NVIDIA's P100 GPU instances in its public cloud, with plans to add the more powerful V100 GPUs in the near future. "This is the first time Oracle has offered access to GPU acceleration, reflecting an industry-wide move to provide access to cloud hardware optimized for artificial intelligence and machine learning.

This content is provided by the IBM Center for the Business of Government. The Business of Government Radio Hour, hosted by Michael J. Keegan, features a conversation with a federal executive who is changing the way government does business. The executives discuss their careers and the management challenges facing their organizations. Guests include administrators, chief financial officers, chief information officers, chief operating officers, commissioners, controllers, directors, and undersecretaries. What is artificial intelligence (AI) and how has it evolved?

Japanese manga artist Kazuo Umezu has won an award at one of Europe's largest comic festivals held in France for a comic featuring a robot that develops emotions, his publisher said Tuesday. The 81-year-old author of "Watashi wa Shingo" ("My Name is Shingo") was given the Heritage Award at the 45th Angouleme International Comics Festival held for four days through Sunday. The prize is awarded to the producer of a work that is worthy of being handed down to posterity. He became the third Japanese manga artist to win the award after Shigeru Mizuki and Kazuo Kamimura, according to the comic's publisher, Shogakukan Inc. "This is (an award) from France, which loves manga as art. I'm truly happy!" Umezu said in a statement.

Recently, I've been trying to figure out new and interesting ways to combine deep learning and finance (totally not for my master thesis or anything like that). I've read that CNN and their variations could be applied to predict financial things like stock prices to somewhat decent extent. What do you think about applying regional CNN to predict-stock prices. The idea is quite simple: instead of looking at the whole graph CNN would look at regions who express high heteroscedasticity or have a clear upwards or downwards trend. Based on the amount of differences expressed and how far these regions would be from our prediction point (I guess one could use something like euclidean distance).

What is the meaning of life? This is a uniquely human characteristic – to ponder the meaning of life. I think the meaning of life is to maximise pattern existence. To exist is the meaning itself. What is the difference between right and wrong?