Machines could take 50% of our jobs in the next 30 years, according to scientists. While we can’t predict the future, we can imagine a world without work – one where those who own the tech get rich from it and everyone else ekes out a living, propped up by an increasingly fragile state. Meet Alice, holder of the last recognisable job on Earth, trying to make sense of her role in an automated world.
Read the related article at The Guardian: Automation may mean a post work society
If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning.
In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.
You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice.
AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work.
We will help you master Deep Learning, understand how to apply it, and build a career in AI.
You will see and work on case studies in healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will also build near state-of-the-art deep learning models for several of these applications. In a "Machine Learning flight simulator", you will work through case studies and gain "industry-like experience" setting direction for an ML team.
United Nations Deputy Secretary-General Amina J. Mohammed interviews the life-size social robot Sophia (created by Hanson Robotics Limited) at the UN General Assembly Second Committee and the Economic and Social Council joint meeting on "The future of everything – sustainable development in the age of rapid technological change."
Sophia was created by a Hong Kong-based company called Hanson Robotics. The company aims to humanize robots and calls this the “Sophia quest.”
Driven by the acceleration of connectivity and cognitive technology, the nature of work is changing. As AI systems, robotics, and cognitive tools grow in sophistication, almost every job is being reinvented, creating what many call the “augmented workforce.” As this trend gathers speed, organizations must reconsider how they design jobs, organize work, and plan for future growth.
Automation is an idea that has inspired science fiction writers and futurologists for more than a century. Today it is no longer fiction, as companies increasingly use robots on production lines or algorithms to optimize their logistics, manage inventory, and carry out other core business functions. Technological advances are creating a new automation age in which ever-smarter and more flexible machines will be deployed on an ever-larger scale in theworkplace. In reality, the process of automating tasks done by humans has been under way for centuries. What has perhaps changed is the pace and scope of what can be automated. It is a prospect that raises more questions than it answers. How will automation transform the workplace? What will be the implications for employment? And what is likely to be its impact both on productivity in the global economy and on employment? This graph was produced as part of the McKinsey Global Institute’s overall research on the impact of technology on business and society.