Twice a week, we'll be highlighting the latest bot and artificial intelligence news here on the Bot or Not Medium blog. This week, we have bots running countries, companies and social engagements. Will bots eventually rule the world, like in the movies? See below for a summary, and stay tuned for more bots news next week! Real-time bots have grown exponentially smarter in the last decade.

Though research is a slow moving and rigid process, one study shows that the rate of scientific study has exploded in the last 50 years. According to the paper, humanity's scientific output now doubles every nine years. In specific areas like healthcare, the doubling rate is even faster -- as much as every 3 years currently with an expected increase to every 73 days by the early 2020s. For overwhelmed researchers navigating the growing stack of science literature -- the value isn't in having so much new information, but finding relevant insights when they need them. According to Jacobo Elosua, a co-founder of Iris AI -- a Singularity University portfolio company -- the research process is very often tedious and unfruitful.

DeepMind, an artificial intelligence company owned by Google, has attempted to justify why it needs access to millions of NHS patient records for a kidney monitoring app, after a new investigation from New Scientist questioned whether an ethical approval process should have been obtained first. The AI research lab, acquired by Google in 2014 for around 400 million, signed a data-sharing agreement with the Royal Free London NHS Foundation Trust on 29 September 2015. The agreement gives Google DeepMind access to the names, addresses, and medical conditions of the 1.6 million patients that are treated at Barnet, Chase Farm, and the Royal Free hospitals each year, as well as data on all patients treated by the Trust in the past five years. This week, New Scientist questioned why Google DeepMind needs access to so much data on so many people, including those who have never experienced kidney problems, for the app, which is called Streams. Streams -- used by Royal Free clinicians in three separate trials since December 2015 -- is designed to detect acute kidney injury (AKI), a condition that kills more than 1,000 people a month.

Ten years ago, Justin Kan and Emmett Shear had just sold their app company, Kiko, and were itching for another venture. They had a concept -- livestream video -- but no idea how to build it. So they sent an email to the MIT engineering listserv, requesting a "hardware hacker" for an unspecified project. Kyle Vogt, a young student fascinated with robotics, replied. They met over coffee where Kan and Shear pitched their idea before flying out to San Francisco.

A Georgia Institute of Technology research team has devised a novel way to help keep a driverless vehicle under control as it maneuvers at the edge of its handling limits. The approach could help make self-driving cars of the future safer under hazardous road conditions. Researchers from Georgia Tech's Daniel Guggenheim School of Aerospace Engineering (AE) and the School of Interactive Computing (IC) have assessed the new technology by racing, sliding, and jumping one-fifth-scale, fully autonomous auto-rally cars at the equivalent of 90 mph. The technique uses advanced algorithms and onboard computing, in concert with installed sensing devices, to increase vehicular stability while maintaining performance. The work, tested at the Georgia Tech Autonomous Racing Facility, is sponsored by the U.S. Army Research Office.

Prime time television viewers have undoubtedly noticed the slew of recent commercials featuring IBM's Watson computing platform in conversation with celebrities such as Bob Dylan, Carrie Fisher, Serena Williams, and Stephen King. These ads showcase continuing advances in Watson's speech capabilities and intelligence applied to various disciplines, which were initially exhibited in Watson's championship performance on the Jeopardy! The public and much of the press tend to think of such computing capabilities as "artificial intelligence" (a.k.a. AI), although that term can bring with it connotations of technology run amuck, à la HAL 9000 in the film 2001: A Space Odyssey, The Terminator's Skynet, and many other popular depictions. Outside the realm of fiction, technology business leader Elon Musk has tweeted that AI is "potentially more dangerous than nukes," and physicist Stephen Hawking warned "development of full artificial intelligence could spell the end of the human race."

Intel has a plan to become increasingly relevant in the Internet of Things (IoT) and autonomous car market, so it took over Itseez, a startup that specializes in computer vision and machine learning. No official information is available regarding the financial details of the transaction. Itseez started out in San Francisco in 2005 and gained expertise in computer vision algorithms and software. Its advanced driver assistance systems (ADAS) consist of a series of auto algorithms that make sure the car hardware detects and interprets the visual information correctly. Such information could be anything from traffic lights or signs to pedestrians, stray dogs or balls rolling in the middle of the street.

Every day, 730,000 comments and 420 billion statuses are posted on Facebook, 500 billion 140-character tweets are posted and 430,000 hours of new video is uploaded to YouTube. The Internet is a goldmine of data just waiting to be analyzed. Ever since social media crept deeper and deeper into our daily lives, governments and advertisers have been utilizing this data for myriad purposes. Now, a team of researchers at the University of Ottawa, University of Alberta and the Université de Montpellier in France is examining ways to use social media data to detect and monitor people who are potentially at risk of mental health issues. Using computer algorithms, the team will apply social web mining and "sentiment analysis methods" to troves of data generated through social media to detect at-risk individuals. Sentiment analysis is the process of identifying and categorizing opinions expressed in text through a computer program.

The marriage of technology and medicine has already afforded humanity with some pretty phenomenal achievements -- after all, we're closer to becoming bionic than ever before. But despite the numerous advances in the medical field, there's still one critical problem yet to be solved: misdiagnoses. A key component of patient care, reading and diagnosing medical images is becoming more important than ever with an aging global population, and Zebra Medical Vision believes it can help. By teaching computers to help radiologists, Zebra says, its products can help health care providers "analyze millions of imaging records to understand the risk profile of their patients, detect and predict disease, and assist in building and managing preventative care programs." On Tuesday, the Israeli company announced a new collaboration with Intermountain Healthcare, one of the largest health care providers in the U.S., with hopes of accelerating the creation of Zebra's imaging analytics engine and neural networks that will use the tech company's imaging dataset to assist radiologists with automated diagnostic algorithms.

Let me give you little bit of context first. In Whisper there no profiles or connections like in traditional social networks, you simply download the app and post something for everyone to see. This means that people often post things (such as confessions) that they wouldn't post on other social networks. This brings a number of unique challenges with it. Moderation: Because there no social filters there is a big chance of abuse (including inappropriate content, bullying, abusive or illegal).