There is a lot of debate on whether Industry 4.0 with a strong underpinning of artificial intelligence (AI) and machine learning is going to result in large-scale unemployment. This seems a bit odd because neither technology nor automation is a 21st-century phenomenon! They are as old as humanity itself, and if this appears an exaggeration, then they are at least as old as the industrial revolution at least. The battle between man and machines goes back centuries. At one point of time, the worry was what would happen if spinning machines replaced weavers and if steam engines took the place of horse carriages.

Groupe PSA and Inria today announced the creation of an OpenLab dedicated to artificial intelligence. The studied areas will include autonomous and intelligent vehicles, mobility services, manufacturing, design development tools, the design itslelf and digital marketing as well as quality and finance. "Artificial intelligence will quickly become an efficiency factor for the group. The OpenLab will work on artificial intelligence algorithms enabling autonomous vehicles to drive in complex environments for example. It will also work on predictive maintenance, powertrain design optimisation and the modelling of complex systems such as cities, to offer mobility services adapted to people's needs" said Carla Gohin, Groupe PSA's Vice President for Research and Advanced Engineering. Inria's project teams will participate in this OpenLab bringing their high-level algorithmic expertise as part of a fruitful dialogue with Groupe PSA's experts on all the identified topics.

An exhibition of an unattended vending car built by PIX, a start-up based in Guiyang, Southwest China's Guizhou Province Photo: Courtesy of PIX Imagine waking up and making a reservation for a robot-staffed vending car first thing in the morning so you can enjoy a cup of coffee on the way to work. After work, you get some exercise on the way home via a moving gym. Then a mobile grocery store stops right in front of your door when you arrive home. You select fresh vegetables and ingredients to cook a delicious dinner. PIX claims it will be the first in China to make this convenient future possible. The start-up was incubated in Silicon Valley and is based in the Guiyang Hi-tech Industrial Development Area in Southwest China's Guizhou Province.

On-device Artificial Intelligence (AI) chips are fast changing the way Indian users interact with their devices and Taiwanese mobile chipset maker MediaTek on Thursday said it will ensure that the experience reaches millions of feature phone and entry-level smartphone users. Showcasing advancements in smartphone AI here, TL Lee, General Manager, Wireless Communication, MediaTek, told IANS that the company is well aware of the huge mobile handset consumer base. There are nearly 650 million mobile phone users in India and just over 300 million of them have a smartphone, according to Counterpoint Research. "We want to democratise AI. The idea of introducing New-Age chipsets with AI capabilities is to empower all mobile users. India offers a great opportunity across price segments and we'll have AI chips to address all of those soon," Lee emphasised.

E-commerce giant Alibaba Group Holding and lifestyle brand Guess on Wednesday showed off a new artificial intelligence driven concept for future fashion stores, as retailers incorporate technology into offline shopping to improve customer experience and drive sales. A concept store showing off Alibaba's FashionAI technology has been set up on the campus grounds of Hong Kong Polytechnic University, will be open to the public from July 5 to July 7. Users check in to the store with their mobile Taobao QR code and all the items displayed in-store come with corresponding Taobao product listings, so that users can add the items they would like to purchase directly to their Taobao cart. Within the store, each item, whether it's a dress or a pair of heels, comes with an RFID tag. When a customer picks up a product, the smart mirror closest to the user registers the tag and displays an image of the item as well as the product details on the screen. The smart mirror can also provide mix and match suggestions for items in the store and styling suggestions based on previous purchases made by the user.

Sentiment analysis is the automated process of understanding an opinion about a given subject from written or spoken language. In a world where we generate 2.5 quintillion bytes of data every day, sentiment analysis has become a key tool for making sense of that data. This has allowed companies to get key insights and automate all kind of processes. But… How does it work? What are the different approaches? What are its caveats and limitations? How can you use sentiment analysis in your business? Below, you'll find the answers to these questions and everything you need to know about sentiment analysis. No matter if you are an experienced data scientist a coder, a marketer, a product analyst, or if you're just getting started, this comprehensive guide is for you. How Does Sentiment Analysis Work? Sentiment Analysis also known as Opinion Mining is a field within Natural Language Processing (NLP) that builds systems that try to identify and extract opinions within text. Currently, sentiment analysis is a topic of great interest and development since it has many practical applications. Since publicly and privately available information over Internet is constantly growing, a large number of texts expressing opinions are available in review sites, forums, blogs, and social media. With the help of sentiment analysis systems, this unstructured information could be automatically transformed into structured data of public opinions about products, services, brands, politics, or any topic that people can express opinions about. This data can be very useful for commercial applications like marketing analysis, public relations, product reviews, net promoter scoring, product feedback, and customer service. Before going into further details, let's first give a definition of opinion. Text information can be broadly categorized into two main types: facts and opinions. Facts are objective expressions about something. Opinions are usually subjective expressions that describe people's sentiments, appraisals, and feelings toward a subject or topic. In an opinion, the entity the text talks about can be an object, its components, its aspects, its attributes, or its features.

Artificial intelligence (AI) is advancing steadily -- but how can we measure those gains in human terms? To gauge AI's progress, we can point to a handful of milestones: In 1997, Deep Blue defeated grandmaster Garry Kasparov in a chess match. In 2011, IBM Watson challenged "Jeopardy!" In both of these examples, computers were programmed to learn from each defeat, refining their strategy until they could match the very best players. Now, IBM Research has revealed another key moment in AI, a new project that we have been incubating since 2012-- Project Debater. And we asked ourselves, "What's next for AI?" The answer, first proposed by scientists in our research lab in Haifa, Israel, was itself a question, and an irresistible one at that: "Could a machine dialogue with us intelligently?"

Alibaba has debuted its first FashionAI concept store. This will be open from Thursday through to Saturday at Hong Kong Polytechnic University, and will showcase Guess apparel through the likes of smart mirrors. In addition, each item has its own intelligent lock, supported by radio-frequency identification, gyro-sensors and Bluetooth low-energy chips. This allows the mirror to more accurately capture movement and spot the colours, styles and attributes that are most popular among customers.

The newly established Center for the Fourth Industrial Revolution in the Japanese capital aims to update old regulations that hinder effective usage of cutting-edge technologies and accelerate social change by developing appropriate policy frameworks for a rapidly changing society, said Chizuru Suga, who heads the institution. "In short, what we are trying to do is like determining the size of a soccer goal before playing the game. We are trying to set up common policy frameworks that help people play a fair game," she said during a recent interview with The Japan Times. "Today's technology has been advancing so fast that no one could have been able to catch up with the most up-to-date movement and set the rules … to benefit as many people as possible," said Suga, originally from the Ministry of Economy, Trade and Industry (METI). The Tokyo facility, which opened Monday, is the first sister institution of the Center for the Fourth Industrial Revolution in San Francisco.

US universities, especially the big four (MIT, CMU, Stanford, University of California and Berkeley) are already ahead of the pack in machine learning research and artificial intelligence. Not just the US, Canadian universities, especially the University of Toronto and Montreal lead in the computational side of things. In India too, IIT Hyderabad's Department of Computer Science and Engineering offers an MTech in machine learning which prepares students for ML-oriented jobs as well as research areas. IIT-H's CSE department is active in research areas such as networking, distributed systems, algorithms, graph theory and also offers a three year research-oriented MTech programme which enables students to work on sponsored research projects along with the coursework. There is also a two year MTech course in Machine Learning and Computing offered by Mathematics department of Indian Institute of Space Science and Technology (IIST).