It is reasonable to expect that AI capabilities will eventually exceed those of humans across a range of real-world-decision making scenarios. Should this be a cause for concern, as Alan Turing and others have suggested? Will we lose control over our future? Or will AI complement and augment human intelligence in beneficial ways? It turns out that both views are correct, but they are talking about completely different forms of AI. To achieve the positive outcome, a fundamental reorientation of the field is required. Instead of building systems that optimize arbitrary objectives, we need to learn how to build systems that will, in fact, be beneficial for us. I will argue that this is possible as well as necessary. The new approach to AI opens up many avenues for research and brings into sharp focus several questions at the foundations of moral philosophy. Introduction This conference – organized under the auspices of the Isaac Newton Institute “Mathematics of Deep Learning” Programme — brings together leading researchers along with other stakeholders in industry and society to discuss issues surrounding trustworthy artificial intelligence. This conference will overview the state-of-the-art within the wide area of trustworthy artificial intelligence including machine learning accountability, fairness, privacy, and safety; it will overview emerging directions in trustworthy artificial intelligence, and engage with academia, industry, policy makers, and the wider public.
( Machine Learning & Deep Learning Specialization Training: ) This CloudxLab Machine Learning Project tutorial helps you to understand how to work on a Machine Learning Project end-to-end in detail. Below are the topics covered in this tutorial: 1) Machine learning projects for beginners 2) Checklist for Machine Learning Projects 3) Root Mean Square Error 4) Variables in Statistics 5) Normal Distribution 6) Skewed Distribution 7) What are the Measures of Central tendency 8) Mean, Median and Mode 9) Box Plot Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Machine Learning & Deep Learning tutorial playlist here: #MachineLearningAlgorithms #Datasciencecourse #DataScience #CloudxLabMachineLearning #MachineLearningCourse #DeepLearningCourse How does it work? 1. This is a 100+ hour online instructor-led course 2. With the course, you get access to real-time distributed production cluster so that you can learn by doing hands-on 3. Each topic consists of videos, assessments, questions and case studies to make sure you master the topic 4. We have a 24×7 support and discussion forum to answer all your queries throughout your learning journey 5. At the end of the training, you will work on real-life projects on which we will provide you a grade and a verifiable certificate! 6. Optionally, subscribe to 1:1 mentoring sessions and get guidance from industry leaders and professional – – – – – – – – – – – – – – About the Course CloudxLab’s Machine Learning & Deep Learning Specialization Training is designed to [More]
Dr. Anima Anandkumar, Professor at the California Institute of Technology, delivered a talk titled “Infusing Structure into Machine Learning Algorithms” on March 15, 2019 in Ann Arbor, Michigan as part of the Michigan Institute for Data Science(MIDAS) Seminar Series.