The gift will fund the construction of a building, which will be the center of this initiative. It will also enable the creation of six endowed chairs, six endowed professorships and six endowed faculty fellowships, as well as graduate and undergraduate scholarships, including scholarships for high-achieving Hoosier students, to support the initiative. The overall goal of the gift is to accelerate the progress of the school as one of the best of its kind in the world. In recognition of this extraordinarily generous gift and in recognition of Luddy's continued leadership and landmark support of the school's mission, IU trustees have approved naming the school in his honor; it will now be known as the Luddy School of Informatics, Computing and Engineering. The naming and gift were announced Thursday at a meeting of the school's Dean's Advisory Council, of which Luddy is a member.

With Hands-On Neural Networks with TensorFlow 2.0 - 1st Edition, Understand the basics of machine learning and discover the power of neural networks and deep learning, Explore the structure of the TensorFlow framework and understand how to transition to TF 2.0, Solve any deep learning problem by developing neural network-based solutions using TF 2.0 Description TensorFlow, the most popular and widely used machine learning framework, has made it possible for almost anyone to develop machine learning solutions with ease. With TensorFlow (TF) 2.0, you'll explore a revamped framework structure, offering a wide variety of new features aimed at improving productivity and ease of use for developers. Book Details Author(s): Paolo Galeone Publisher: Packt Publishing Published: September 18, 2019 Language: English ISBN-10: 1789615550 ISBN-13: 9781789615555 Number of pages: 358 Get This Book Hands-On Neural Networks with TensorFlow 2.0: Understand TensorFlow, from static graph to eager execution, and design neural networks 1st Edition

GPUs are famously expensive – high end Nvidia Teslas can be priced well above $10,000. Now a New York startup, Paperspace, has announced a free cloud GPU service for machine/deep learning development on the company's cloud computing and deep learning platform. Designed for students and professional learning how to build, train and deploy machine learning models, the service can be thought of as an ML/DL starter kit that helps developers expand their skills and try out new ideas without financial risk. Utilizing Nvidia Quadro M4000 and P5000 GPU's and called "Gradient Community Notebooks," the service is based on Jupyter notebooks and enables developers working with widely used deep learning frameworks, such as PyTorch, TensorFlow, Keras and OpenCV, to launch and collaborate on their ML projects. Similar to GitHub, Gradient Community Notebooks can be shared and "forked" into a user's own account while providing pre-loaded templates with various libraries, dependencies and drivers, the company said.

Abu Dhabi has announced the establishment of the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). Located in Masdar City, MBZUAI is a new graduate-level AI research institution that will enable graduate students, businesses, and governments to advance the artificial intelligence field. The University is named after 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. The AI 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. It 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.

To say that artificial intelligence (AI) is the next step in enterprise would be an understatement. In other words, the so-called "AI revolution" is already here. Join nearly 200,000 subscribers who receive actionable tech insights from Techopedia. According to McKinsey and Company, by 2030, 70% of companies will have adopted at least one kind of AI technology. The expansion of AI also stands to have a significant impact on the world's economy and job-force.

The United Arab Emirates (UAE) will host graduate-level courses in artificial intelligence (AI) at a new university in its capital, Abu Dhabi. The Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) aims to enable students, businesses and governments to increase the use of AI technology. Sultan Ahmed Al Jaber, UAE minister of state, said: "Mohamed bin Zayed University of Artificial Intelligence is an open invitation from Abu Dhabi to the world to unleash AI's full potential. "AI is already changing the world, but we can achieve so much more if we allow the limitless imagination of the human mind to fully explore it." The university, which will be located in Masdar City, Abu Dhabi, is tapping experience from across the world with a board of trustees from respected universities in the UK, the US and China. MBZUAI will offer postgraduate (MSc and PhD) courses in computer vision, machine learning and natural language processing. It is now open for admission to the academic year 2021-2022. Registration will begin in August 2020, with the first students starting the following month. All graduate students admitted will be offered a full scholarship and other benefits, including a monthly allowance, health insurance and accommodation. It will also help graduates find work and internships with local and global companies. MBZUAI has partnered with the Abu Dhabi-based Inception Institute of Artificial Intelligence for the supervision of PhD students and curriculum development, as well as collaborative research. Michael Brady, interim president at MBZUAI, said: "Following decades of research into machine learning and artificial intelligence, we are now at a turning point in the widespread application of advanced intelligence.

Many of these people live in rural areas, where fiber, coaxial cable, DSL or any other kind of broadband infrastructure is scarce or nonexistent. This is a huge issue for rural community administrators and school officials who have been struggling to help their communities. For example, students can use the internet in school, but when they go home to do their homework, they have no access. At Revolution D, I've been working with these local officials to try to help them solve their problems. Technology has changed a lot in the past few years--what's known as fixed wireless technology is becoming more widespread.

I've written several times about how the "economies of learning" are more powerful than the "economies of scale". Through a continuous learning and refinement process, organizations can simultaneously drive down marginal costs while accelerating time-to-value and de-risking projects via digital asset re-use and refinement (see Figure 1). Think about how us lowly humans learn. Whether trying to hit a golf ball or playing the piano or water skiing, we learn though the "feedback loop of failure". And the more real-time, immediate that feedback loop, the more quickly we can assess what we did wrong, adjust and then try again.

But machine learning continues to be one of the toughest skills to acquire. The domain is as vast and as complex as the field of computer science. Developers will have to learn new languages, algorithms, frameworks, tools from an extremely diverse and fragmented ecosystem. They need to learn how to use the cloud to train the models and optimizing those models to integrate with a variety of environments and platforms. The complexity multiplies when we attempt to take the models to the edge.

Machine learning has the potential to support aspects of teaching and learning that are currently time consuming and difficult to manage, such as individual project work, collaboration, tutorials and self-directed learning. In 2018, the global Machine Learning in Education market size was xx million US$ and it is expected to reach xx million US$ by the end of 2025, with a CAGR of xx% during 2019-2025. This report focuses on the global Machine Learning in Education status, future forecast, growth opportunity, key market and key players. The study objectives are to present the Machine Learning in Education development in United States, Europe and China. The key players covered in this study IBM Microsoft Google Amazon Cognizan Pearson Bridge-U DreamBox Learning Fishtree Jellynote Quantum Adaptive Learning Market segment by Type, the product can be split into Cloud-Based On-Premise Market segment by Application, split into Intelligent Tutoring Systems Virtual Facilitators Content Delivery Systems Interactive Websites Others Market segment by Regions/Countries, this report covers United States Europe China Japan Southeast Asia India Central & South America The study objectives of this report are: To analyze global Machine Learning in Education status, future forecast, growth opportunity, key market and key players.