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Machine learning finds a surprising early galaxy

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New results achieved by combining big data captured by the Subaru Telescope and the power of machine learning have discovered a galaxy with an extremely low 1.6% oxygen abundance, breaking the previous record of the lowest abundance. The measured oxygen abundance suggests that most of the stars in this galaxy formed very recently. To understand galaxy evolution, astronomers need to study galaxies in various stages of formation and evolution. Most of the galaxies in the modern universe are mature galaxies, but standard cosmology predicts that there may still be a few galaxies in the early formation stage in the modern universe. Because these early-stage galaxies are rare, an international research team searched for them in wide-field imaging data taken with the Subaru Telescope.


It's Personal: AI Leader Partners With IBM, Builds New Buy Zone

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As IBM (IBM) and Red Hat team up with Adobe (ADBE) on artificial intelligence and personalization technology, Adobe stock is trying to customize a new base and buy point. The IBD Long-Term Leader is also setting its sights on a fresh all-time high. In July, Adobe, IBM and Red Hat announced a strategic partnership aimed at accelerating the digital transformation and strengthening of real-time data security for enterprises, with a focus on regulated industries such as banking and health care. Building on IBM's acquisition of Red Hat in 2018, the goal of the partnership is to "enable companies to deliver more personalized experiences across the customer journey, driving improved engagement, profitability and loyalty." Having already made its own successful shift to a software-as-a-service model, Adobe has become a major player in cloud-based creative, personalization and analytics products.


The Top 5 Deep Learning Libraries And Frameworks

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Created by the Google Brain team, TensorFlow is an open-source library for numerical computation and large-scale machine learning. TensorFlow provides a collection of workflows to develop and train models using Python, JavaScript, or Swift, and to easily deploy in the cloud, on-premise, in the browser, or on-device irrespective of what language you use. The tf.data API enables you to build complex input pipelines from simple, reusable pieces. TensorFlow can train and run deep neural networks for handwritten digit classification, image recognition, word embeddings, recurrent neural networks, sequence-to-sequence models for machine translation, natural language processing, and PDE (partial differential equation) based simulations. TensorFlow allows developers to create dataflow graphs -- structures that describe how data moves through a graph, or a series of processing nodes.


Eighth grader builds IBM Watson-powered AI chatbot for students making college plans

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While her peers reveled in an unprecedented virtual school year, the self-described "technology enthusiast," Harita Suresh, 13, was bored. She decided on an online course and settled on IBM Skills Network's "AI chatbots without programming." She lacked experience with artificial intelligence, but was eager to learn through the self-paced course. Harita is more than a little familiar with tech, "I have been interested in technology since I was 5," she said. "My first coding challenge was the Lightbot Hour of Code. I was fascinated that the code I wrote could control the actions of the characters on screen. Since then, I pursued coding on multiple platforms like code.org, The more I learned about tech, the more I wanted to know. In fifth grade, I took a Python programming course offered by Georgia Tech."


Top Artificial Intelligence Salaries in India in August 2020

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Applications of artificial intelligence are relentlessly growing, touching every aspect of business operations and society. Today, AI has become integral to diverse industries and revolutionized the way organizations perform and make decisions. As business leaders and innovators race to reach the promise of this disruptive technology to gain a competitive edge, job opportunities in AI are in high demand. This growing need of AI experts from businesses will significantly disrupt economic activity in a big way. As AI has a high learning curve, succeeding in this field requires germane skills and knowledge, and investment of time and energy.


Top 15 AI Articles You Should Read This Month - July 2020

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Usually, every month we write an article about the best and most promising AI research papers from that month. In addition to that, we list fifteen AI articles we have found amazing that month. This collection of articles should give you an overview of what happened that month in the AI industry both from technical, business and from an ethical perspective. Are you afraid that AI might take your job? Make sure you are the one who is building it.


Oxford University Introduces New Commission to Address AI Governance in Public Policy

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A new commission has been formed by Oxford University to advise world leaders on effective ways to use Artificial Intelligence (AI) and machine learning in public administration and governance. The Oxford Commission on AI and Good Governance (OxCAIGG) will bring together academics, technology experts and policymakers to analyse the AI implementation and procurement challenges faced by governments around the world. Led by the Oxford Internet Institute, the Commission will make recommendations on how AI–related tools can be adapted and adopted by policymakers for good governance now and in the near future. The new Commission's inaugural thinkpiece, "Four Principles for Integrating AI & Good Governance" by Lisa-Maria Neudert and Philip Howard examines the procurement and use of AI by government and public agencies. The report outlines four significant challenges relating to AI development and application that need to be overcome for AI to be put to work for good governance and leverage it as a'force for good' in government responses to the COVID-19 pandemic.


Neural Networks Need Naps, Just Like You

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Neural networks would like a day off. Between powering facial recognition systems, filtering email spam, and even aiding in cancer research, the specialized branch of machine learning deserves a bit of rest and relaxation. Yijing Watkins, a computer scientist at Los Alamos, said her team had been studying "spiking neural networks," or systems that learn as much as our own living brains do, when they became inspired to try something a bit unusual. The robots are coming--are you prepared? Learn how to master machines and take control of your world.


Difficult stuff in simple words: Data Science vs Machine Learning vs Artificial intelligence

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Starting learning a new field is always not easy. The best way to learn is to start from the basics because it will make the ground for all your further knowledge. First of all, let's understand what all those buzzwords actually mean. The difficulty in understanding those terms is that they are overlapping and some people mistakenly think that they are also interchangeable, and they are not, of course. But first sings first, let's define what those terms mean one by one.


Introducing 'The AI & Machine Learning Imperative'

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Leading organizations recognize the potential for artificial intelligence and machine learning to transform work and society. The technologies offer companies strategic new opportunities and integrate into a range of business processes -- customer service, operations, prediction, and decision-making -- in scalable, adaptable ways. As with other major waves of technology, AI requires organizations and managers to shed old ways of thinking and grow with new skills and capabilities. "The AI & Machine Learning Imperative," an Executive Guide from MIT SMR, offers new insights from leading academics and practitioners in data science and AI. The guide explores how managers and companies can overcome challenges and identify opportunities across three key pillars: talent, leadership, and organizational strategy.