A new update for WhatsApp on iOS will make iPhone users' life easier -- users with iOS 10.3 on their iPhone can get Siri to read out their WhatsApp messages. WhatsApp version 2.17.2 for iOS let you use the new feature by just saying, "Hey Siri, read me my last WhatsApp message." The feature works only with unread messages, so messages you have read once, won't be re-read by Siri. The feature will allow people to go hands free easily -- say, if your phone is connected to the car's infotainment system, but you want to listen to your WhatsApp messages while driving, you will now be able to do that with a simple voice command. The feature has been in the works for some time.

Vizio may have been knocked by LeEco after its $2 billion buyout deal was cancelled, but the company's not going to fall into a grief-stricken funk. The home theater business has announced a new raft of soundbars that work with Google Assistant and come with Chromecast built in. Leading the pack is the SmartCast 36", which packs 5.1 wireless sound, the promise of crystal-clear dialog and a wireless subwoofer. It's on sale right now, setting you back $250, while smaller options in the same range will cost less, obviously. The company has also wheeled out an addition to its Sonos-troubling Crave speakers in the form of the Crave Go.

What is the potential of machine learning over the next 5-10 years? And how can we develop this technology in a way that benefits everyone? The Royal Society's machine learning project has been investigating these questions, and has today launched a report setting out the action needed to maintain the UK's role in advancing this technology while ensuring careful stewardship of its development. Machine learning is a form of artificial intelligence that allows computer systems to learn from examples, data, and experience. Through enabling computers to perform specific tasks intelligently, machine learning systems can carry out complex processes by learning from data, rather than following pre-programmed rules.

Amazon is making its voice-control technology available to all, giving developers access to the same tools that power its digital assistant Alexa. The platform is called Amazon Lex, and bundles in both speech recognition, text recognition, and conversational interactions. It was first announced in a "preview phase" in late 2016, but according to a new report from Reuters, is now rolling out to all developers. Amazon Lex will allow tech companies to quickly make voice or text-based chat interfaces for their apps, making them interactive in the same way as Alexa, Siri, and Google Assistant. A lot of big Silicon Valley firms have seen an opportunity in selling these sorts of easy-to-use AI tools, and both Google and Microsoft also offer their own suite of similar services.

The inventor of the world wide web, Sir Tim Berners-Lee, recently warned that artificial intelligence could develop decision-making capabilities that impact the fairness of economic systems, if allowed to operate at a high level of business. Although data gathered by artificial intelligence is often used to inform decisions made at board-level, such as the predicted growth of demand for a product within a particular industry, AI is a long way from calling the shots. Presently, decision-making AI in offices remains limited to repeatable, mundane tasks like formatting and filing documents. A recent report from PwC predicts that up to 30% of jobs in the UK are at risk of being taken over by AI and robots by early 2030. While this might come as a surprise to some, IT departments will already be aware that they need to prepare their systems for the technology.

AI is all around us, quietly working in the background or interacting with us via a number of different devices. Various industries are using AI for specific reasons such as ensuring that flights arrive on time or irrigating fields better and more economically. Over time, our interactions with AI are becoming more sophisticated. In fact, in the not-too-distant future we'll have personal digital assistants that know more about us than we know about ourselves. For now, there are countless AI projects popping up in commercial, industrial and academic settings.

This is an overview of what a recommendation system in retail is and how we implemented it at a grocery chain. These days, recommendation systems empower social networks, healthcare, finance, and e-commerce. At the end of 2016, Starbucks announced that they will be implementing an AI-based recommendation system in their cafes all over the world. This means that predictive analytics has finally found its way into retail. Like e-commerce entrepreneurs, retailers can now send customers personalized offers based on their behavior.

As a designer, you will be facing more demands and opportunities to work with digital systems that embody machine learning. To have your say about how best to use it, you need a good understanding about its applications and related design patterns. This article illustrates the power of machine learning through the applications of detection, prediction and generation. It gives six reasons why machine learning makes products and services better and introduces four design patterns relevant to such applications. To help you get started, I have included two non-technical questions that will help with assessing whether your task is ready to be learned by a machine. We are expecting a great many things to happen once the big data deluge has been funnelled into a nurturing stream of bits. Data can be used in many ways. One is to build smart products, and another is to make better design and business decisions. The latter also, ultimately, trickle into products. Machine learning is a very promising approach radically shaping future product and service development. Machine learning is a branch of artificial intelligence. It employs many methods: Deep learning and neural networks are two well-known instances.

Artificial intelligence and other technologies will cause people "more pain than happiness" over the next three decades, according to Jack Ma, the billionaire chairman and founder of Alibaba. "Social conflicts in the next three decades will have an impact on all sorts of industries and walks of life," said Ma, speaking at an entrepreneurship conference in China about the job disruptions that would be created by automation and the internet. A key social conflict will be the rise of artificial intelligence and longer life expectancy, which will lead to an aging workforce fighting for fewer jobs. Ma, who is usually more optimistic in his presentations, issued the warning to encourage businesses to adapt or face problems in the future. He said that 15 years ago he gave hundreds of speeches warning about the impact of e-commerce on traditional retailers and few people listened because he wasn't as well-known as he is now.

Whether analyzing the facial expressions of job candidates in video interviews, sorting through multitudes of online applications or keeping job prospects apprised of their hiring status, artificial intelligence (AI) is moving rapidly from experimentation to mainstream use in the talent acquisition world. Many recruiters who get a firsthand look at this rapidly evolving technology are struck by how it can make their lives easier. While artificial intelligence typically conjures up images of futuristic human-like robots, the term can be broadly defined as any so-called smart software--that is, technology with the ability to learn and grow more effective over time. "There's a greater level of maturity in AI tools in the recruiting space than in any other area of HR," says Helen Poitevin, a Paris-based human capital management research director at Gartner, an information technology research firm. Continued advances in AI will make tomorrow's recruiting look much different from today's, but for now recruiters are hailing the technology for its ability to reduce the "grunt work" in their jobs. Among the most evolved AI tools are artificial "assistants" that can improve the job seeker experience.