A Webinar By Joseph Simonian Abstract: After reviewing some differences between traditional statistics & data science, we present a modular machine learning framework for model validation which blends the two paradigms. Model validation is set up as a sequence of procedures, in which the output from one procedure serves as the input to another procedure within a single validation framework. An econometric model is used in the first module to classify data in an economically intuitive way. Proceeding modules apply data science techniques to evaluate the predictive characteristics of the model components. We apply the framework to the fundamental law of active management, a well-known formal characterization of portfolio managers alpha generation process.

Today's guest is Bret Greenstein, SVP and Global Head of AI at Cognizant, one of the top 5 largest tech consulting companies globally, with 2019 revenue at nearly $17B. What does it look like to interact with a client who has an idea of an AI project, inform their idea of what AI is, and help refine and define the problem to solve it. It is often not the case where a client will immediately have a robust understanding of what they need to do, or they will come in with a granularly very tight and coherent idea of where AI can drive value in their business. Bret goes into tactfully bringing education into the sales and delivery process to add more value to clients. Do you want more keys to success in your own AI consulting career?

The reader of the post must have a basic understanding of Convolutional Neural Networks. If you are unfamiliar with the topic you can refer to this link and if you want to know more about the convolutional operation which is actually derived from basic image processing, you can read this blogpost as well. Convolutional Neural Networks or CNN's, in short, is one of the main causes of the revival of artificial intelligence research after a very long AI winter. The applications based on them were the first ones which showcased the power of artificial intelligence or deep learning to be precise and revived the faith in the field which was lost after Marvin Minsky pointed out that Perceptron just worked on linearly separable data and failed to work on the simplest non-linear functions such as XOR. Convolutional Neural Networks are very popular in the domain of Computer Vision and almost all state of the art applications such as google images, self-driving cars etc are based on them.

Welcome to AI book reviews, a series of posts that explore the latest literature on artificial intelligence. There are a dozen artificial intelligence conferences where researchers push the boundaries of science and show how neural networks and deep learning architectures can take on new challenges in areas such as computer vision and natural language processing. But using machine learning in real-world applications and business problems--often referred to as "applied machine learning" or "applied AI"--presents challenges that are absent in academic and scientific research settings. Applied machine learning requires resources, skills, and knowledge that go beyond data science, that can integrate AI algorithms into applications used by thousands and millions of people every day. Alyssa Simpson Rochwerger and Wilson Pang, two experienced practitioners of applied machine learning, discuss these challenges in their new book Real World AI: A Practical Guide for Responsible Machine learning.

If you don't have enough to worry about already, consider a world where AIs are hackers. Hacking is as old as humanity. We are creative problem solvers. We exploit loopholes, manipulate systems, and strive for more influence, power, and wealth. To date, hacking has exclusively been a human activity.

In the event you get bored waiting for your Audi A6 e-tron to charge its batteries, instead of kicking back to read a newspaper you can play a video game in the car - and have it beamed onto a wall by the headlights. But beneath the fun, froth and frippery there's also some really significant stuff going on as its underpinnings become the basis for a new coupe-style saloon and a whole family of new Audi electric cars. For long distance travellers who want to cruise in style the new Audi A6 e-tron Sportback has a claimed range of more than 434 miles. Audi's electric saloon turned games console on wheels: Bosses say the new Digital Matrix LED headlights on the new A6 e-tron concept are so crisp that they can project'cinematic quality' footage - including video games - onto a wall The matrix LED lights can project images - even the indicator lights project their beam onto the ground as well as into the air, says Audi. Should you get bored while re-charging your car, the new electric A6 e-tron's main digital matrix LED front headlights enjoy a'cinematic quality' that can also be harnessed to play video games.

Jensen Huang, Nvidia's chief executive, says the company's next step is creating a'metaverse', artificially created environments where companies can simulate the future before acting on it. Mr Huang said the company wanted to "create the future" by creating a virtual world that is thousands of times larger than the physical world. This digital space would be recreations of New York City and Shanghai, Mr Huang predicts, with "digital twin[s]" of "every single factory and every single building". "Engineers and software programmers could simulate new software that will ultimately run in the physical version of the car, the physical version of the robot, the physical version of the airport, the physical version of the building", Mr Huang said in an interview with Time magazine. "All of the software that's going to be running in these physical things will be simulated in the digital twin first, and then it will be downloaded into the physical version".

As technology becomes a more intimate part of our everyday lives, artificial intelligence is driving progress and helping solve some of society's greatest challenges. BI Norwegian Business School is researching the impact of technology and artificial intelligence on sustainability, gender equality, health and wellbeing, justice, social responsibility, and responsible investment and education. Matilda Dorotic, an associate professor in marketing at the business school, has been involved in extensive research on the impact of technology and big data on diverse aspects of well-being, civil-mindedness, and smart cities--she's recently been invited by the European Commission to talk about the societal issues of implementing artificial intelligence and its far-reaching impact on citizens. It's something we all need to pay more attention to as, according to Matilda "citizens know so little about the ways in which artificial intelligence is fundamentally changing their everyday lives". According to the WHO, cancer is the second leading cause of death worldwide and is responsible for around 10 million deaths per year.

Artificial Intelligence is a topic which evokes mixed reactions among people. Some consider AI to be a technological revolution which will solve all our problems and transform our planet into a veritable paradise. Others equate AI with robots courtesy of Hollywood movies; not good robots but rather exceedingly intelligent but evil and villainous robots with nefarious plans to wipe out the entire human civilization. As a computer engineer, I have always had an insider view of the technologies and been witness to many technical changes over the decades. From BASIC, to C to C to Java – each iteration produced better and more sophisticated coding mechanisms.

Technology today is evolving at such a rapid pace, enabling faster change and progress, causing an acceleration of the rate of change, until eventually it will become exponential. However, it is not only technology trends and top technologies that are evolving, a lot more has changed this year due to the outbreak of COVID-19 making IT professionals realize that their role will not stay the same in the contactless world tomorrow. And an IT professional in 2020-21 will constantly be learning, unlearning and relearning (out of necessity if not desire). What does this mean for you? It means staying current with new technology trends.