Most of us already know that adopting new cloud applications can boost a business's productivity by enabling organizations to be more agile and ready to change course in our fast-moving and connected digital world. But the rapid adoption of cloud apps and services also brings with it profound security threats, including visibility and control challenges that aren't present in traditional on-premises environments. At the same time, the cloud - because of its interconnected, flexible and adaptable nature - can also provide new possibilities for addressing cloud security problems. By leveraging the power of the cloud with a data science and machine learning cloud-based solution, security and risk professionals can solve many of the traditional security challenges found in popular apps like Office 365, Google Drive, Salesforce and Box. In her session at 19th Cloud Expo, Deena Thomchick, Senior Director of Cloud Security at Symantec, detailed how cloud-based data science, machine learning, computational analysis and intelligent algorithms can work together to help to deliver truly intelligent and responsive security and compliance for the cloud.

As we look to a New Year, it is hard to say what 2017 has in store thanks to the level of uncertainty that 2016 leaves in its wake. One thing for certain, however, is that 2017 is set to be an eventful and thrilling ride for FinTech with many factors and potential obstacles on the horizon which still challenge the sector. In today's society people are effectively running their whole lives from their mobiles: reading the news, online banking, heating their home and maintaining relationships. Payments are a part of that so it is expected that the numbers to climb further next year. Smartphone sales are reaching saturation point in developed markets, and the growth of technology adoption today are now firmly fixated on emerging and developing nations.

Daniel Tran is an IBM Co-op Student working as a Technical Curriculum Developer in Toronto, Ontario. He develops courses to improve the education of customers who seek knowledge in the Big Data field. He has also reworked previously developed courses, updating them to be compatible with the newest software releases, as well as work at the forefront of recreating courses on a newly developed cloud environment. He has worked with various components that deal with Big Data, including Hadoop, Pig, Hive, HBase, MapReduce & YARN, Sqoop, Oozie, and Phoenix. He has also worked on separate courses involving Machine Learning.

Google's DeepMind is teaming up with the makers of the StarCraft video game to train its artificial intelligence systems. The AI systems "playing" the game will need to learn strategies similar to those that humans need in the real world, DeepMind said. Its ultimate aim is to develop artificial intelligence that could solve any problem. It has previously taught algorithms to play a range of Atari computer games. StarCraft II, made by developer Blizzard, is a real-time strategy game in which players control one of three warring factions - humans, the insect-like Zerg, or aliens known as the Protoss.

Mathematicians have long wondered at the logical structure of Johann Sebastian Bach's music, attempting to distill it into fractals or understand his "rational and consistent system" of composition. In particular, Bach's chorale harmonizations are ripe for systems like artificial intelligence to understand: They always consist of four parts (a melody and three harmonies), are short in duration (about a minute long), and are based off simple melodies that were popular in Lutheran hymns. These consistent traits allowed a deep neural network built by Sony's Computer Science Laboratories to break down the patterns found between 352 of Bach's chorales and generate new harmonies. The machine's goal isn't to make an original melody, but instead generate the thee supporting harmonies around a supplied melody. It writes each harmony separately, its goal to predict which note Bach himself would write given the preceding note, the notes adjacent in the melody and other harmonies, and the beat the note lands on. Its prediction is made by looking at what Bach did in similar situations, the 352 chorales used to train the AI.

Many people have found the table above to be useful for understanding two conceptual distinctions in the practice of data analysis. The article that discusses the table, and many other issues, is now in press. The in-press version can be found at OSF and at SSRN. Abstract: In the practice of data analysis, there is a conceptual distinction between hypothesis testing, on the one hand, and estimation with quantified uncertainty, on the other hand. Among frequentists in psychology a shift of emphasis from hypothesis testing to estimation has been dubbed "the New Statistics" (Cumming, 2014).

Many current fears around AI and automation center around the idea that superintelligence could somehow "take over," turning streets around the globe into scenes from The Terminator. While there is much to be gained from discussing the safe development of AI, there's another more imminent danger: Autonomous weapons. On Friday, after three years of negotiations, the UN unanimously agreed to take action. At the Fifth Review Conference of the UN Convention on Certain Conventional Weapons, countries around the world agreed to begin formal discussions--which will take place for two weeks at the 2017 UN convention in Geneva--on a possible ban of lethal, autonomous weapons. Talks will begin in April or August, and 88 countries have agreed to attend.

Though Intel is the leader in data centers microprocessor market, with more than 90% market share, it has more recently lagged in the market for coprocessors, where Nvidia has generated momentum. Whereas Intel is dominant in the microprocessor market at large, Nvidia has successfully identified this coprocessor niche where it has garnered significant market share. This is reflected in their recent growth rates. While Intel witnessed a mere 13% year over year growth in its revenue from the Data Center Group in Q3 2017, Nvidia data center revenues nearly tripled during the same period. Of course, Intel's data center revenues are a vast multiple of Nvidia's.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. At least they have robots to get some actual work done. If anyone can use some automation to boost production, it's Santa: That must have taken a ridiculous amount of helium.

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