In hopes of luring skilled workers both at home and form abroad with a chance to reside in Japan's ancient capital of Kyoto, Line Corp., a popular messaging app service, opened a new development base in the heart of the city in June. The firm plans to raise the number of engineers to 3,000, from around 2,100, in the near future. At present, the Kyoto office has 19 engineers of which 10 are from overseas. While more tech staffers are needed, "we won't lower our hiring bar," said Ryohei Miyota, who oversees the hiring of engineers at Line's Kyoto branch. Still, Line has shown it is willing to be flexible with other conditions.

Learning management systems are not new to corporate learning; they have been around for quite some time and each year more and more are released. What an LMS basically does is host, distribute, record and report on all learning that goes on within an organization. Apart from that, there are many more additional features that companies ask for and expect today. Probably the most difficult one to incorporate is tracking all informal learning and using the information to provide highly personalized learning. The LMS is the critical component to the entire e-learning program, acting both as the foundation (by incorporating all the modules) and as the engine (by providing the environment in which learners can access them and suggesting various topics based on curriculum and personal interest).

The elite team of engineers and medical specialists assembled by IBM's Watson Health division had the innocuous code name "Project Josephine," but its mission could not have been more urgent: to fix the artificial intelligence software at the core of the company's campaign to tackle the $7 trillion global health care market. The predicament faced by IBM officials, STAT has found, was that it could not get its software to reliably understand and analyze language in patient medical records. That was critical for the company to deliver on multimillion-dollar contracts with hospitals and drug companies. Unlock this article by subscribing to STAT Plus and enjoy your first 30 days free! STAT Plus is a premium subscription that delivers daily market-moving biopharma coverage and in-depth science reporting from a team with decades of industry experience.

Around one in nine men in America will develop prostate cancer in their lifetime, according to the report which has been revealed and around more than 3 million patients have been diagnosed with it at the same point are still even alive today. And just from seeing a cancer perspective, it tends to be so much problematic prostate cancer is nonaggressive which makes it difficult to determine that which procedures might be going to be necessary. Google has now made headway in diagnosing it, with the help of Machine Learning and Artificial Intelligence. Google researchers have described a system which uses the Gleason Score, which is a grading system which classifies cancer cells which is moreover based on how closely they resemble some of the normal prostate glands to detect the problematic masses in samples. The goal which is more according to the technical lead Martin Stumple and Google artificial Intelligence healthcare product Manager Craig Marmel was to develop AI which could easily perform the Gleason grading objectively and much more precisely.

If the robots are going to inherit from humans not just our minds, but our filthy little souls too, then we're all probably doomed. Ongoing research from Google's DeepMind AI project reportedly indicates that game-playing artificial intelligence is developing a nasty cheating habit, if cheating's what it takes to finish atop the leaderboard. Setting an AI loose on a video game with the simple instruction to rack up as many points as possible, it turns out, is basically an invitation to have it find and exploit every loophole it can. Even if it means hurling yourself over a ledge, kamikaze-style, in a self-sacrificing loop, or pausing the game just at the moment your victory's in doubt, AI is learning how to win at all costs – or at least make sure that nobody else does. One AI that was learning how to play Q*bert, reports Kotaku, "Even took to killing itself to boost its score. After discovering a pattern of movement by which it could get enemies to follow it off a cliff in order to gain more points and an extra life, it continued to do just that for the rest of the session."

One employee traveling for work checked his dog into a kennel and billed it to his boss as a hotel expense. Another charged yoga classes to the corporate credit card as client entertainment. A third, after racking up a small fortune at a strip club, submitted the expense as a steakhouse business dinner. These bogus expenses, which occurred recently at major U.S. companies, have one thing in common: All were exposed by artificial intelligence algorithms that can in a matter of seconds sniff out fraudulent claims and forged receipts that are often undetectable to human auditors -- certainly not without hours of tedious labor. AppZen, an 18-month-old AI accounting startup, has already signed up several big companies, including Amazon, International Business Machines, Salesforce.com and Comcast, and claims to have saved its clients $40 million in fraudulent expenses.

On October 19, a Waymo Pacifica struck and injured a motorcyclist in California. As is often the case, the collision was caused by a human - in this instance, the safety driver in the Waymo vehicle. In an unusual twist, however, Waymo CEO John Krafcik revealed that if the safety operator had not taken control of the autonomous minivan, then the self-driving software would have avoided a collision. Our simulation shows the self-driving system would have responded to the passenger car by reducing our vehicle's speed, and nudging slightly in our own lane, avoiding a collision." Waymo Autonomous Vehicle ("WaymoAV") was traveling at approximately 21 MPH westbound in Lane 2 of El Camino Real in Mountain View in self-driving mode. A passenger vehicle in Lane 1, to the left of the Waymo AV, began to change lanes into Lane2 to avoid a box truck blocking two lanes of traffic, Waymo's test driver took manual control of the AV out of an abundance of caution, disengaged from self-driving mode, and began changing lanes into Lane 3. A motorcycle, traveling at approximately 28 MPH behind the Waymo AV, had just entered Lane 3 to overtake the Waymo AV on its right. The motorcyclist reported injuries and was transported to the hospital for treatment. The Waymo AV sustained minor damage to the rear bumper."

A collective eyebrow was raised by the AI and robotics community when the robot Sophia was given Saudia citizenship in 2017 The AI sharks were already circling as Sophia's fame spread with worldwide media attention. Were they just jealous buzz-kills or is something deeper going on? Sophia is not the first show robot to attain celebrity status. Yet accusations of hype and deception have proliferated about the misrepresentation of AI to public and policymakers alike. In an AI-hungry world where decisions about the application of the technologies will impact significantly on our lives, Sophia's creators may have crossed a line.

At VentureBeat's recent VB Summit event, I headed a session on whether enterprises should build or buy AI. Between comments from the panelists and a group of about 20 business leaders, a good decision tree emerged for how to answer this question. Given how important the question is, I wanted to share that decision tree more widely. As you can see, at the top of the tree is the question "Do you even need AI?" I believe AI can positively impact any and all businesses, so the correct answer should always be yes. The next question to ask is if AI is in your company's DNA.

Visual object recognition, speech recognition, machine translation – these are among the "holy grails" of artificial intelligence research. But machines are now at a level that the benchmark performance for these three areas has reached, and even surpassed, human levels. Moreover, in the space of 24 hours, a single program, AlphaZero, became by far the world's best player in three games – chess, Go, and Shogi – to which it had no prior exposure. These developments have provoked some alarmist reporting in the media, invariably accompanied by pictures of Terminator robots, but predictions of imminent superhuman AI are almost certainly wrong – we're still several conceptual breakthroughs away. On the other hand, massive investments in AI research, several hundred billion pounds over the next decade, suggest further rapid advances are not far away.