WhatsApp is working on a new feature that businesses can use to contact customers directly, according to a new report. The feature, which is being tested by a number of Y Combinator startups, is designed as a way for the the messaging app to make money. Businesses could end up paying WhatsApp for the ability to get in touch with potential customers, according to Reuters, which adds that the Facebook-owned firm is wary of spam potentially becoming an issue. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, ...

While personalisation remains the most popular place for innovation among US retailers, there is clear evidence that AI has started to gain traction. According to a new report from SailThru called the Digital Retail Innovation Report, "Although marketers have been able to leverage artificial intelligence (AI) for some time, adoption is still limited." "Of the two thirds of marketers (66 per cent) who leverage AI for marketing purposes, the most common applications are in search (37 per cent) and product recommendations (33 per cent), which are employed by at least one third of marketers," the report said. Among the other common responses were application through programmatic advertising (26 per cent) and data science (26 per cent). The authors said, "AI use alone wasn't enough to guarantee marketing success: Marketers leveraging AI in one or more of the listed channels/methods weren't significantly more likely to have met or exceeded their 2016 marketing goals, suggesting that not all applications and methods are equally useful, and that simply employing AI-based solutions is not sufficient for marketing success."

As manufacturing businesses are increasingly on the lookout for opportunities to boost automation, it is clear that big data and machine learning are set to revolutionize the future of production. Companies are already collecting huge amounts of data from various resources, including industrial machinery, and monitoring precise details of the production process in the hope of improving quality at every stage. When companies have gathered enough of the right data, predictive technologies can allow businesses to manage the servicing of machinery based on sensor data and advanced analytics, rather than on a fixed schedule. For a piece of machinery or an autonomous vehicle, for example, these technologies can help predict when and how they are likely to break down. Businesses can then service the equipment before it starts to be a problem and generate losses.

One question that always pops up in any machine learning problem: Which algorithm should I use? What do the algorithms do anyways? After briefly going over a typical machine learning process, we have a closer look at third step, i.e. building the model: What algorithms are out there? Which one should we use? One of Microsoft's Data Scientist, Brandon Rohrer, has written a nice three-part blog series on introducing data science with no jargon: Furthermore, there is one really neat cheat sheet created by Microsoft's Data Science team on when to use which algorithm: Finally, one last resource that I hihgly recommend: Top 10 data mining algorithms in plain English.

Ahead of'The future of litigation' on Thursday, RPC's Daniel Wyatt tells Tom Connelly how the Pyrrho case is redefining what it means to be a litigation lawyer Everyone's talking about artificial intelligence (AI), about what it can actually do, about how far it will go, and about whether trainee lawyers and paralegals' jobs are at risk. Daniel Wyatt, a litigation and arbitration specialist at RPC, has witnessed the rise and rise of AI within the legal sector first-hand. Wyatt -- who joined RPC as an associate in 2012 -- recognises that AI's impact on litigation and the legal sector is hugely important but stresses that it is more about a change in focus, not the death knell for junior posts. There will always be a need for junior lawyers. I suspect that the impact of AI will be more a case of re-distributing the work that paralegals and trainees undertake.

As the ancient Roman orator Cicero once put it, "The face is the index of the soul." In 2017, our faces are more index.html Nearly 250 million video surveillance cameras have been installed throughout the world, industry researcher IHS Insight estimated, and the global video surveillance market revenue is estimated to triple over a seven-year period, increasing to $42 billion in 2020 from $14 billion in 2013, according to industry predictions. Add to that surreptitious recording technology like drone cameras, Google Glass, Snapchat video glasses. Market researcher IBISWorld estimated the revenue for advertising agencies last year reached $44 billion, up 4% on the previous year. Face-reading technology can also now detect your emotions -- even those you don't realize you're projecting.

Artificial intelligence ("AI") is a technical field of computer science that includes machine learning, natural language processing, speech processing, expert systems, robotics and machine vision. The term "artificial intelligence" is sometimes challenged in favor of machine intelligence or machine learning. Machine learning automates decision making using programming rules and in some cases training data sets. Human subject matter experts can provide feedback on results as part of a training process. Machine learning can adapt its programming based on the training process and feedback.

Last December, Starbucks announced "My Starbucks Barista," a virtual barista for its mobile app that enables customers to place orders via voice command or messaging interface. This led me to consider the current perception of artificial intelligence and where it stands in relation to the current reality of the technology. Are chatbots the real deal or yet another victim of hyped technology? If you ask me, chatbots are still in the hype phase within the public eye and don't deserve a fraction of the attention they currently receive. While this may sound harsh, it's important to understand the difference between potential and intrinsic value, just like with any other new technology. You may be asking, if a brand as large as Starbucks is launching a chatbot, how can AI and chatbots still be considered hype?

For the most part conversations on the topic tend to revolve around loss of jobs and the redundancy of human labour. The Sunday Times has even gone as far as producing a list of the jobs most likely to become automatised in the coming years due to artificial intelligence. While some jobs are at a higher risk than others, it's estimated that those in advertising have only a 3.8% chance of being replaced by a machine. In reality, AI will actively work with us, not against us, making our business processes more streamlined and efficient. Infosys, a global leader in technology services, published a report that establishes a clear link between the revenue and implementation of AI technology in businesses. Although there have been cases of job loss due to automation, such as the recent layoffs at General Electric.

My wife used to love reading but since her stroke has aphasia, no speech, limited vision and limited dexterity in her left hand only. She can select TV channels on a remote but she cannot read a short news story let alone a novel, so she listens to the radio and watches a lot of TV. I thought of getting her a Kindle e-reader but they don't seem to do text to speech any more. A shop assistant suggested a tablet with a text-to-speech app. It needs a really simple interface or my wife will not be able to use it without assistance.