Programmers and developers can tap into a variety of languages to build applications, websites, and other programs. Ultimately, your preferred language is going to be the one with which you're most comfortable and that gets the job done most effectively. But one particular language emerged as the top choice in a study released in September by the IEEE, and that's Python. To gauge the popularity of different languages, the IEEE's study ranked 11 data points from eight different sources: CareerBuilder, Google, GitHub, Hacker News, the IEEE, Reddit, Stack Overflow, and Twitter. Depending on the source, the IEEE looked at such factors as searches, new repositories, posts mentioning each language, and job postings made within the last 30 days.

But increasingly, algorithms have begun to arbitrate fairness for us. They decide who sees housing ads, who gets hired or fired, and even who gets sent to jail. Consequently, the people who create them--software engineers--are being asked to articulate what it means to be fair in their code. This is why regulators around the world are now grappling with a question: How can you mathematically quantify fairness?

One of the most common misperceptions I hear about bias is "If I don't use age, gender or race, or similar factors in my model, it's not biased." Even though the same people holding this opinion know that machine learning can learn relationships between data, they don't understand that there are proxies to biased data types in other features that are captured. These proxies are called confounding variables and, as the term indicates, unintended variables can confuse the model into producing biased results. For example, if a model includes the brand and version of an individual's mobile phones, that data can be related to the ability to afford an expensive cell phone -- a characteristic that can impute income. If income is not a factor desired to use directly in the decision, imputing that information from data, such as the type of phone or the size of the purchases that the individual makes, introduces bias into the model.

Our Machine Learning models gives organizations the room to strategize their business decisions based on insights derived from programs that iteratively learn and develop to make more accurate decisions. Our algorithms help in data-driven decisions that define the retailers' success. Machine learning facilitates the continuous advancement of computing by exposing the models to new situations, testing and adapting, through pattern and trend detections for making improved decisions in future but not identical scenarios. Our focus area is the ability to easily analyze and create prediction models based on huge sets of master data that is business information shared across your entire organization. This includes data sets about the infrastructure including network, storage, and more.

Abu Dhabi has announced that it has established the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) the first graduate level, research-based artificial intelligence university in the world. MBZUAI will enable graduate students, businesses, and governments to advance in the AI field, and will introduce a new model of academia and research to the field of AI. This will provide students and faculty access to some of the world's most advanced AI systems to unleash its potential for economic and societal development, it said. Dr Sultan Ahmed Al Jaber, Minister of State, who has been appointed Chair of the MBZUAI Board of Trustees and is spearheading the establishment of the University, said the university aligns with the vision of the UAE leadership and is based on sustainable development and finding practical solutions based on innovation and state-of-the-art technology. The University will offer Master of Science, MSc, and PhD level programmes in key areas of AI – Machine Learning, Computer Vision, and Natural Language Processing – while also engaging policymakers and businesses around the world so that AI is harnessed responsibly as a force for positive transformation. MBZUAI has partnered with the Abu Dhabi-based Inception Institute of Artificial Intelligence (IIAI), a global force in excellence and leadership of AI research, for the supervision of PhD students and curriculum development.

Abu Dhabi announced the establishment of the Mohamed bin Zayed University of Artificial Intelligence, which will enable graduate students, businesses, and governments to advance the artificial intelligence field. The University will introduce a new model of academia and research to the field of AI, providing students and faculty access to some of the world's most advanced AI systems to unleash its potential for economic and societal development. Dr. Sultan Ahmed Al Jaber, Minister of State, who has been appointed Chair of the MBZUAI Board of Trustees and is spearheading the establishment of the University, said, "Mohamed bin Zayed University of Artificial Intelligence aligns with the vision of the UAE leadership that is based on sustainable development, progress and the overall well-being of humanity. Experts from around the world have been selected for the University's Board of Trustees, WAM reported. They include MBZUAI Interim President, Professor Sir Michael Brady, professor of Oncological Imaging at the University of Oxford, UK; Professor Anil K. Jain, a University Distinguished Professor at Michigan State University, USA; Professor Andrew Chi-Chih Yao, Dean of the Institute for Interdisciplinary Information Sciences at Tsinghua University, Beijing, China; Dr. Kai-Fu Lee, a technology executive and venture capitalist based in Beijing, China; Professor Daniela Rus, Director of Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory, USA, and Peng Xiao, CEO of Group 42. The Board of Trustees will be supported by an Advisory Board, chaired by Omar bin Sultan Al Olama, Minister of State for Artificial Intelligence, and will include Sarah bint Yousif Al Amiri, Minister of State for Advanced Sciences; Dr. Ahmad bin Abdullah Humaid Belhoul Al Falasi, Minister of State for Higher Education and Advanced Skills; Jassim Al Zaabi, Chairman of the Department of Finance, and Dr. Wan Li Min, Chief Machine Intelligence Scientist at Alibaba. Over the next decade, AI is set to have a transformational impact on the global economy, with experts estimating that, by 2030, AI could contribute nearly US$16 trillion to the global economy. Al Jaber added, "The invention of electricity, the railroad, smartphones all transformed the world as we knew it.

ABU DHABI, 16th October, 2019 (WAM) -- Abu Dhabi today announced the establishment of the Mohamed bin Zayed University of Artificial Intelligence, MBZUAI, the first graduate level, research-based AI university in the world. MBZUAI will enable graduate students, businesses, and governments to advance the artificial intelligence field. The University is named after His Highness Sheikh Mohamed bin Zayed Al Nahyan, Crown Prince of Abu Dhabi and Deputy Supreme Commander of the UAE Armed Forces, who has long advocated for the UAE's development of human capital through knowledge and scientific thinking to take the nation into the future. MBZUAI will introduce a new model of academia and research to the field of AI, providing students and faculty access to some of the world's most advanced AI systems to unleash its potential for economic and societal development. The announcement was made at a press conference at the University campus in Masdar City and was immediately followed by the first meeting of the MBZUAI Board of Trustees.

What is optimization Some real-life situations where we need to optimize an objective The mathematical formalism of optimization How discrete optimization (Combinatorics) differs from continuous optimization Different approaches to solve a Combinatorics problem, including-- The simplest, perfect but slow'Brute Force' method. One of the fastest and practicable'Greedy' heuristic.A look-ahead mechanism to refine the greedy approach. Travelling Salesman Problem Other generic problems in discrete optimization, like the Knapsack Problem How metaheuristic approaches compare to heuristic solutions The nature-inspired class of metaheuristic approaches Ant Colony Optimization: its basis, modus operandi, algorithm and flow chart The R library to implement Ant Colony Optimization and other heuristic solutions Examples of Travelling Salesman Problems solved through different approaches ESSENTIAL: A moderate knowledge of Mathematics (High School level) BOOSTER: Familiarity with some programming language (preferably R) BOOSTER: Interest in solving puzzles and games involving logic BOOSTER: Basic knowhow on what Data Science is about Discrete Optimization is something all of us use in our daily activities when say, we order at a restaurant, decide which subject to study, take up a new activity… or look for a change. It comprises of choosing between alternatives that best suit some objective we have in mind. When such things are formalized, i.e. the objective and the ability of each choice to fulfill that objective are quantified, we get a mathematical expression of the problem we would optimize.

With student outcomes being a key performance metric for higher education institutes, many are turning to leverage data to glean insights and drive improved outcomes. "For many institutions, student performance has a direct impact on rankings. AI can be a tool to help better manage outcomes and ensure continued innovation to optimize operations and enhance student engagements, as it reduces resource-intensive work among faculty and administrative staff," said Larry Nelson, Regional General Manager – Education, Microsoft Asia. "In fact, we found that 3 out 4 education leaders agree that AI will be able to drive competitiveness in the next 3 years. However, only 32% of education institutions in Asia Pacific have embarked on their AI journey," added Nelson.

Meta-Learning describes the abstraction to designing higher level components associated with training Deep Neural Networks. The term "Meta-Learning" is thrown around in Deep Learning literature frequently referencing "AutoML", "Few-Shot Learning", or "Neural Architecture Search" when in reference to the automated design of neural network architectures. Emerging from comically titled papers such as "Learning to learn by gradient descent by gradient descent", the success of OpenAI's rubik's cube robotic hand demonstrates the maturity of the idea. Meta-Learning is the most promising paradigm to advance the state-of-the-art of Deep Learning and Artificial Intelligence. OpenAI set the AI world on fire by demonstrating ground-breaking capabilities of a robotic hand trained with Reinforcement Learning.