Naver and LINE Corp. unveiled their artificial intelligence (AI)-based assistant platform Clova at the Mobile World Congress (MWC) 2017 in Barcelona, the companies reported Thursday. According to Naver and its mobile service subsidiary, Clova, which stands for "cloud virtual assistant," aims at an AI platform that works based on the five human senses. "Clova is a platform that incorporates various AI technologies including vocal, visual and conversational engines," LINE Corp. CEO Idezawa Takeshi said in his keynote at the MWC 2017, Wednesday. The two companies are jointly developing Clova by improving Naver Labs' voice-recognizing assistant service AMICA. They said it will expand the system to have more cognitive capabilities to make it more humanlike.

That's what keeps me going.

Automation is reaching into a vast range of professions, and my own is certainly no different. Through this blog and various other means, I try to locate interesting research and practices from around the world, and bring them together into some kind of narrative. With so much going on around the world, it stands to reason that a computer could be trained to do a similar task, and that's certainly the aim of Semantic Scholar, a new tool launched by The Allen Institute for Artificial Intelligence. The tool offers users a means of hunting for papers in specific fields, and then filter your search by date, publication and so on. The developers believe that Semantic Scholar stands above the likes of Google Scholar due to the smarter way in which it hunts down relevant papers.

Data mining is the process of analysing data from different perspectives and summarizing it into useful information; information that can be used to increase revenue, cuts costs, or both. Data mining helps a company to predict the behaviour of its customers, based on its data, so the company can determine the impact on sales or profit or customer satisfaction. It also helps a company to suggest something to its customers proactively, based on patterns that emerges out from customer data. There are various sectors where data mining can be useful. In market analysis: With data mining, a company can understand the purchase behaviour of the customer.

Unlike more traditional monolithic DL networks, PathNet reuses a network that consists of many neural networks and trains them to perform multiple tasks. In the authors experiments, they have shown that a network trained on a second task learns faster than if the network was trained from scratch. This indicates that transfer learning (or knowledge reuse) can be leveraged in this kind of a network. PathNet includes aspects of transfer learning, continual learning and multitask learning. These are aspects that are essential for a more continuously adaptive network and thus an approach that may lead to an AGI (speculative).

Here's a quick story you've probably heard before, followed by one you probably haven't. In 1979 a young Steve Jobs paid a visit to Xerox PARC, the legendary R&D lab in Palo Alto, California, and witnessed a demonstration of something now called the graphical user interface. An engineer from PARC used a prototype mouse to navigate a computer screen studded with icons, drop-down menus, and "windows" that overlapped each other like sheets of paper on a desktop. It was unlike anything Jobs had seen before, and he was beside himself. "Within 10 minutes," he would later say, "it was so obvious that every computer would work this way someday." As legend has it, Jobs raced back to Apple and commanded a team to set about replicating and improving on what he had just seen at PARC. And with that, personal computing sprinted off in the direction it has been traveling for the past 40 years, from the first Macintosh all the way up to the iPhone.

If news, polls and investment figures are any indication, Artificial Intelligence and Machine Learning will soon become an inherent part of everything we do in our daily lives. Backing up the argument are a slew of innovations and breakthroughs that have brought the power and efficiency of AI into various fields including medicine, shopping, finance, news, fighting crime and more. TNW Conference won best European Event 2016 for our festival vibe. See what's in store for 2017. But the explosion of AI has also highlighted the fact that while machines will plug some of the holes human-led efforts leave behind, they will bring disruptive changes and give rise to new problems that can challenge the economical, legal and ethical fabric of our societies.

To understand how advances in artificial intelligence are likely to change the workplace -- and the work of managers -- you need to know where AI delivers the most value. Major technology companies such as Apple, Google, and Amazon are prominently featuring artificial intelligence (AI) in their product launches and acquiring AI-based startups. The flurry of interest in AI is triggering a variety of reactions -- everything from excitement about how the capabilities will augment human labor to trepidation about how they will eliminate jobs. In our view, the best way to assess the impact of radical technological change is to ask a fundamental question: How does the technology reduce costs? Only then can we really figure out how things might change. To appreciate how useful this framing can be, let's review the rise of computer technology through the same lens.

Diagnosis is one of the most important parts of medicine since doctors can hardly do anything to cure a patient if they don't know what the illness is. When it comes to tumors, the process is lengthy and complicated, increasing the chances of death. With the help of artificial intelligence, doctors can now cut the time needed for diagnosing tissue by 90 percent with considerable accuracy. Normally, diagnosing something like a brain tumor takes about 30 to 40 minutes, during which, doctors would need to leave the operation room in order to put the samples through the rigorous process for analysis, Futurism reports. With the help of advanced AI, however, this time can be cut down to a measly 3 to 4 minutes.

The words evoke images of sterile science-fiction environments, sleek robots and future-gazing articles from the past 20 years promising that, this time, AI is really taking over. The change has been more subtle than that – not a sudden revolution where we're servile to robots, but an undeniable shift in how AI is increasingly embedded in our technology, altering our lives as a result. This month, alongside our other regular coverage, we'll be paying special attention to AI with a number of interviews, features and other stories about this most exciting of technological advancements. Below, three of our writers give their thoughts on why it's so damned important. Way back in the 1990s, I spent a great deal of time thinking about AI.