Just months after Microsoft's Tay artificial intelligence sent racist messages on Twitter, another AI seems to have followed suit. More than 6,000 selfies of individuals who live all over the world and range in ages of 18 to 69 were judged by a robot in a beauty contest last week. But when the results came in, there was something missing - it turned out the robots did not like people with dark skin. The Beauty.AI beauty contest put together of robot judges to determine the winners. Beauty.AI used five algorithms to act as judges in a beauty contest.

A recent study shows how artificial intelligence (machine learning) could help improve the accuracy of lung diseases diagnosis. The presence of artificial intelligence (AI) in the broad and complex field of medicine has continually improved over time. As a matter of fact, AI's potential to enhance the accuracy and efficiency when it comes to disease diagnostics is simply undeniable. Following the influences of artificial intelligence in the various subspecialties of medicine, a team of researchers developed an AI-based algorithm process that can learn and perform predictive data analysis. According to Tech 2, Belgium's University of Leuven professor and senior study author Wim Janssens explained that the AI algorithm process can provide experts more accurate lung diseases diagnosis by simulating physicians' complex reasoning in a "more standardized and objective way." Based on the study, researchers successively probed how the concept of machine learning could assist them in analyzing the complete lung function tests.

With more than 6,000 applicants from over 100 countries competing, the first international beauty contest judged entirely by artificial intelligence just came to an end. The results are a bit disheartening. The team of judges, a five robot panel, attempted to pick winners from the submitted photos in hopes that it could determine which faces most closely resembled the idea of "human beauty." Each of the five robot judges used artificial intelligence to analyze specific traits that contribute to perceived outer beauty. Momentum by TNW is our New York technology event for anyone interested in helping their company grow. Using complex algorithms, the judges picked 44 winners.

Chanda Kochhar, managing director & chief executive officer, ICICI Bank, said by the end of FY17, the bank would more than double the number of transactions cleared by the bots. "Currently, about 10 per cent of our internal transactions are being carried out via the software robots and by the end of this year, we believe, this will go up to 20 per cent of our transactions. This has helped us in improving productivity and efficiency and will help us in handling larger volumes as we continue to grow." The lender started experimenting with software bots at the beginning of this financial year. Now, over a million banking transactions across 200 business processes are carried out by the technology on a daily basis.

While innovation can be categorized in familiar terms -- such as a new product, service, or business model -- we're finding companies are applying analytics and artificial intelligence techniques to the concept of innovation. Organizations we work with are turning to tools such as machine learning to pursue a fast, effective route to innovative results as they seek to stay competitive and top-of-mind for consumers. For our Accenture Technology Vision 2016 report, we surveyed 3,100 business and IT executives in 11 countries. We found that 70% of respondents are making significantly more investments in artificial intelligence technologies than they did in 2013, with 55% stating that they plan on using machine learning and embedded AI solutions extensively. An analytics-driven approach to innovation involves a blend of technological experimentation and cultural collaboration -- bringing together fresh minds and analytics techniques to uncover insights and ideas which can inspire agility, industry disruption and customer loyalty.

On a summer day in 1968, professor Julian Stanley met a brilliant but bored 12-year-old named Joseph Bates. The Baltimore student was so far ahead of his classmates in mathematics that his parents had arranged for him to take a computer-science course at Johns Hopkins University, where Stanley taught. Having leapfrogged ahead of the adults in the class, the child kept himself busy by teaching the FORTRAN programming language to graduate students. Unsure of what to do with Bates, his computer instructor introduced him to Stanley, a researcher well known for his work in psychometrics -- the study of cognitive performance. To discover more about the young prodigy's talent, Stanley gave Bates a battery of tests that included the SAT college-admissions exam, normally taken by university-bound 16- to 18-year-olds in the United States. Bates's score was well above the threshold for admission to Johns Hopkins, and prompted Stanley to search for a local high school that would let the child take advanced mathematics and science classes.

IBM (NYSE: IBM) today revealed a series of new servers designed to help propel cognitive workloads and to drive greater data center efficiency. Featuring a new chip, the Linux-based lineup incorporates innovations from the OpenPOWER community that deliver higher levels of performance and greater computing efficiency than available on any x86-based server. Collaboratively developed with some of the world's leading technology companies, the new Power Systems are uniquely designed to propel artificial intelligence, deep learning, high performance data analytics and other compute-heavy workloads, which can help businesses and cloud service providers save money on data center costs. The three new systems are an expansion of IBM's Linux server portfolio comprised of IBM's specialized line of servers co-developed with fellow members of the OpenPOWER Foundation. The new servers join the Power Systems LC lineup that is designed to outperform x86-based servers on a variety of data-intensive workloads.

The second beauty contest, where humans are judged by the robots completes with over six thousand images evaluated by the five robot judges. In addition to the panel of judges from the first contest, Beauty.AI 2.0 featured three new robot judges including: "Average Face" built on the hypothesis that the closer the face is to the average face within the ethnic group, the more attractive it is "AntiAgeist" evaluating the difference between the predicted and actual chronological age "PIMPL" evaluating the number and distribution of pimples and other dark spots (but not freckles) The results were sent to the individual participants via secure link and winners were announced at http://winners2.beauty.ai/#win . The results were surprising, since the consensus scores provided by the robot jury disagreed with human opinion. Tens of participants responded with angry emails criticizing the winners selected by the robot jury. Statements including "what is your "robot" worth??? One walk through a shopping-mall and I will discover more attractive people vs. that ones "won" your Beauty Contest", "If this is how I will be judged in the future, I don't want to see it", "You need human opinion" were among the most pleasant ones with rare positive comments including "this contest is a confidence booster!".

Abstract: Attendees will learn the foundations of text mining approaches in addition to learn basic text mining scripting functions used in R. The audience will learn what text mining is, then perform primary text mining such as keyword scanning, dendogram and word cloud creation. Later participants will be able to do more sophisticated analysis including polarity, topic modeling and named entity recognition. Bio: Ted Kwartler is the Director of Customer Success at DataRobot where he manages the end-to-end customer journey. He advocates for and integrates customer innovation into everyday culture and work. He helps to define and organize all customer service functions and key performance indicators.

Lee Painter says a rise in security breaches due to abuse of access has put the spotlight on Identity and Access Management. Identity and Access Management (IAM) is already a key weapon in the security arsenal of many organisations as a way to mitigate against data breaches and manage the additional risks that come with remote working and Bring Your Own Device (BYOD). And the take up of IAM solutions is set to gain even more momentum. A recent MarketsandMarkets research report predicted that the global market for these solutions will grow to US 12.8 billion ( 9.7 billion) by 2020, up from US 7.2 billion ( 5.4 billion) in 2015. IAM solutions enable a network or system to authenticate the identity of a user against a set of pre-prescribed credentials.