What if smartphones had a robotic limb? Many inventions start with a question that nobody else had ever thought to ask. Few of them end up being quite as creepy as MobiLimb. Created by Marc Teyssier at the University of Paris-Saclay in France and his colleagues, MobiLimb looks like a mechanical finger, with knuckles that let it bend and beckon. The appendage plugs into the USB port on your smartphone or tablet and can be used as an additional way to interact with your device.

A new report published by the TUC today has argued that the economic gains from digitisation, robotics and artificial intelligence (AI) will benefit working people. For example, by reversing policies to raise the state pension age. The report delves into the impact of the technological revolution on jobs and wages. Previous technological changes, like the Industrial Revolution, have not led to an overall loss of jobs, but have disrupted the types of job people do. Nevertheless, it is a concern for people.

To summarize epochs, we either computed the 80% trimmed mean, or the standard deviation (SD). The sensor dimension was then summarized using a mean or the standard deviation, yielding four combinations in total (Figure 1A).

The financial services industry is undergoing a massive transformation. Financial technology companies, fintechs, are challenging traditional enterprises and players from other sectors such as retail and technology are entering their turf. Data is at the center of this transformation. Like all sectors, the power of data in financial services helps institutions across the industry – from retail banks to mortgage brokers – offer products, services and experiences that exceed customer expectations. A recent McKinsey study showed that data flows now exert a larger impact on a countries GDP growth than the centuries-old trade in goods.

Consumer identity is just one of many areas where artificial intelligence (AI) can be helpful in analysing vast amounts of data from millions of sources to gain business insights, according to Hans-Peter Gϋllich, CEO and founder of AI-assisted risk management firm Dydon. Security technologist Bruce Schneier's insights and warnings around the regulation of IoT security and forensic cyber psychologist Mary Aiken's comments around the tensions between encryption and state security were the top highlights of the keynote presentations at Infosecurity Europe 2017 in London. You forgot to provide an Email Address. This email address doesn't appear to be valid. This email address is already registered.

How do you approach customer service and policy administration within your organization? In this blog post, I'll demonstrate how artificial intelligence (AI) and a raised AIQ can help you get the most out of your data. To do this, I'll discuss how insurers can use machine learning to analyze texts. Intelligent technologies are reshaping the way insurers approach the customer service and policy administration function. AI enables more efficient administration processes.

The difference between regression machine learning algorithms and classification machine learning algorithms sometimes confuse most data scientists, which make them to implement wrong methodologies in solving their prediction problems. Andreybu, who is from Germany and has more than 5 years of machine learning experience, says that "understanding whether the machine learning task is a regression or classification problem is key for selecting the right algorithm to use." Let's start by talking about the similarities between the two techniques. Regression and classification are categorized under the same umbrella of supervised machine learning. Both share the same concept of utilizing known datasets (referred to as training datasets) to make predictions. In supervised learning, an algorithm is employed to learn the mapping function from the input variable (x) to the output variable (y); that is y f(X).

LONDON – Ireland's data regulator has launched an investigation of Facebook over a recent data breach that allowed hackers access to 50 million accounts. The probe could potentially cost Facebook more than $1.6 billion in fines. The Irish Data Protection Commission said Wednesday that it will look into whether the U.S. social media company complied with European regulations that went into effect earlier this year covering data protection. It's the latest headache for Facebook in Europe, where authorities are turning up the heat on dominant tech firms over data protection. Last month, European Union consumer protection chief Vera Jourova said that she was growing impatient with Facebook for being too slow in clarifying the fine print in its terms of service covering what happens to user data and warned that the company could face sanctions.

According to a 2017 report from PwC, 2018 marks the year artificial intelligence (AI) can finally be applied widely. The report warned that 30 per cent of the country's jobs might be under threat from the technology, but predicted the UK could see productivity boosted by up to 30 per cent and savings generated of up to 25 per cent. Steering the right path forward is going to be hugely complicated, although Greg Clark, Secretary of State for Business, Energy and Industrial Strategy, and the minister in charge of the UK government's AI strategy, is resolutely upbeat. "We are at the cusp of one of the most exciting times in our lives and, if we get our strategy for AI right, then the UK will be able to reap the rewards for our economy for decades to come," he argues. "To secure the huge potential of AI, we need to be strategic and focused, recognising the increasing convergence of technologies and focusing on the areas where we can compete globally."

Fake news continues to rear its ugly head; in March of this year, half of the U.S. population reported seeing deliberately misleading articles on news websites. A majority of respondents to a recent Edelman survey, meanwhile, said that they couldn't judge the veracity of media reports. And given that fake news has been shown to spread faster than real news, it's no surprise that almost seven in ten people are concerned it might be used as a "weapon." Researchers at the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Lab (CSAIL) and the Qatar Computing Research Institute believe they've engineered a partial solution. In a study that'll be presented later this month at the 2018 Empirical Methods in Natural Language Processing (EMNLP) conference in Brussels, Belgium, they describe an artificially intelligent (AI) system that can determine whether a source is accurate or politically prejudiced.