This paper aims at filling some gaps in the mainstream debate on automation, the introduction of new technologies at the workplace and the future of work. This debate has concentrated, so far, on how many jobs will be lost as a consequence of technological innovation. This paper examines instead issues related to the quality of jobs in future labour markets. It addresses the detrimental effects on workers of awarding legal capacity and rights and obligation to robots. It examines the implications of practices such as People Analytics and the use of big data and artificial intelligence to manage the workforce. It stresses on an oft-neglected feature of the contract of employment, namely the fact that it vests the employer with authority and managerial prerogatives over workers. It points out that a vital function of labour law is to limit these authority and prerogatives to protect the human dignity of workers.

Google search is advancing a reading grade. Google says it has enhanced its search-ranking system with software called BERT, or Bidirectional Encoder Representations from Transformers to its friends. It was developed in the company's artificial intelligence labs and announced last fall, breaking records on reading comprehension questions that researchers use to test AI software. Pandu Nayak, Google's vice president of search, said at a briefing Thursday that the muppet-monickered software has made Google's search algorithm much better at handling long queries, or ones where the relationships between words are crucial. You're now less likely to get frustrating responses to queries dependent on prepositions like for" and "to," or negations such as "not" or "no." "This is the single biggest positive change we've had in the last five years," Nayak said--at least according to Google's measures of how ranking changes help people find what they want.

Sign in to report inappropriate content. Watch Jessica Chobot perform Botnik's AI-created sitcom in front of a live audience in New York City. Does it pass the laugh test? This audience (and you) will decide.

This book contains proven steps and strategies on learning Python Programming quickly and easily. Python is a powerful and flexible programming language. It uses concise and easy-to-learn syntax which enables programmers to write more codes and develop more complex programs in a much shorter time. Python: The Ultimate Beginner's Guide provides all essential programming concepts and information you need to start developing your own Python program. The book provides a comprehensive walk-through of Python programming in a clear, straightforward manner that beginners will appreciate. Important concepts are introduced through a step-by-step discussion and reinforced by relevant examples and illustrations. You can use this book as a guide to help you explore, harness, and gain appreciation of the capabilities and features of Python. Thanks again for purchasing this book, I hope you enjoy it!

Tesla may grant certain customers early access to a "feature complete" version of the company's "full self-driving" (FSD) capabilities by the end of 2019, Elon Musk said in a call with investors Wednesday. Musk said that this wasn't "for sure" -- but that he thinks Tesla is on track for the release. It's a kind of limited beta test, so there won't be a bunch of Tesla vehicles driving around autonomously by the end of the year. Musk later clarified on the call that by "feature complete," he means the car will be able to drive from someone's home to their work without intervention. Drivers will still need to be ready to take control if the car runs into a problem.

Abstract: The phenomenal growth of social media, mobile applications, sensor based technologies and the Internet of Things is generating a flood of "Big Data" and disrupting our world in many ways. Simultaneously, we are seeing many interesting developments in machine learning and Artificial Intelligence (AI) technologies and methods. In this talk I will examine the paradigm shift caused by recent developments in AI and Big Data and ways to harness their power to create a smarter enterprise computing environment. Using examples from health care, smart cities, education, and businesses in general, I will highlight challenges and research opportunities for developing an enterprise of the future. Bio: Sudha Ram is Anheuser-Busch Endowed Professor of MIS, Entrepreneurship & Innovation in the Eller College of Management at the University of Arizona.

While Sweden is trialling inserting microchips into its citizens as a new way to pay, China is opting for a less invasive method -- your face. In Shenzhen, a local subway operator is testing several advanced technologies powered by the 5G network, including facial recognition payments, according to a report by the South China Morning Post. At the Futian station, instead of presenting a ticket or scanning a QR bar code on their smartphones, commuters are now able to scan their faces on a tablet-sized screen mounted on the entrance gate and have the fare automatically deducted from their linked accounts. "To use facial ticketing in the future, passengers will also need preregistration of their facial information and link their payment methods to their accounts," said a staff member at the Futian station's demonstration area in Shenzhen. Passers-by at the demonstration area in Futian station will see their information, including facial photos captured by surveillance cameras, gender, age, and the length of stay in the area, displayed on a big screen.

Artificial intelligence is all about developing intelligent machines which is capable enough to work like humans. Some of the tasks that you can target with artificial intelligence are problem solving, speech recognition, learning and planning tasks. Artificial intelligence has been now implemented by different businesses so as to do things differently. For all this you need complete artificial intelligence software services to automate and maximize your business outcomes. Many of the customer service leaders in the market are now not able to create and continuously deliver the kind of the service that their customers expect from them.

A team of chemistry, life science, and AI researchers are using graph neural networks to identify molecules and predict smells. Models made by researchers outperform current state-of-the-art approaches and the top-performing model from the DREAM Olfaction Prediction Challenge, a competition for mapping the chemical properties of odors. The work was created by researchers from Google, Canadian Institute for Advanced Research, Vector Institute for Artificial Intelligence, University of Toronto, and Arizona State University. The researchers believe progress in machine learning application of molecule identification can help deliver machine intelligence that's able to predict smell similar to the way AI that can imitate other senses like vision and hearing has advanced in recent years. With grasping challenges, researchers are also trying to help robotic hands tackle the human sense of touch as well.

A University of Texas at Austin computer science team, in partnership with researchers from Cornell Tech, Georgia Tech and Facebook AI Research, has developed an artificial intelligence system that can look at a photo of an outfit and suggest helpful tips to make it more fashionable. Suggestions may include tweaks such as selecting a sleeveless top or a longer jacket. "We thought of it like a friend giving you feedback," said Kristen Grauman, a professor of computer science whose previous research has largely focused on visual recognition for artificial intelligence. "It's also motivated by a practical idea: that we can work with a given outfit to make small changes so it's just a bit better." The tool, named Fashion, uses visual recognition systems to analyze the color, pattern, texture and shape of garments in an image.