Law
Azure/mmlspark
MMLSpark provides a number of deep learning and data science tools for Apache Spark, including seamless integration of Spark Machine Learning pipelines with Microsoft Cognitive Toolkit (CNTK) and OpenCV, enabling you to quickly create powerful, highly-scalable predictive and analytical models for large image and text datasets. MMLSpark requires Scala 2.11, Spark 2.1, and either Python 2.7 or Python 3.5 . See our notebooks for all examples. Below is an excerpt from a simple example of using a pre-trained CNN to classify images in the CIFAR-10 dataset. See other sample notebooks as well as the MMLSpark documentation for Scala and PySpark.
Amazon considers multi-story hives for its busy drones
The multi-level tower allows drones a place to take off and land. Welcome to the drone hive. Amazon has applied for a patent that gives more insight into the infrastructure it may be planning for its drone delivery program, Amazon Prime Air. In this case, the drones would take off, land and pick up deliveries from a tower placed in densely populated cities that would house the drones. It looks a lot like a bee hive.
Uber admits it knew ex-Google engineer kept trade secrets
Uber admitted that it hired a former Google employee despite being warned that he possessed sensitive documents from the Silicon Valley giant, adding a new twist to a court battle over trade secrets. Waymo, the self-driving car developer created by Alphabet's (GOOGL) Google, has accused Uber of using stolen trade secrets in its own software that would serve as the backbone of autonomous vehicles. Uber has denied the charges. However, the ride-sharing company fired Anthony Levandowski, the ex-Google engineer and Uber executive, for failing to cooperate with an internal investigation. Waymo's lawsuit maintains that Uber then transplanted the intellectual property allegedly stolen by Levandowski into its own fleet of self-driving vehicles -- a charge that Uber has adamantly denied since Waymo filed its complaint in federal court four months ago.
Artificial Intelligence -- Transforming the Legal Services Landscape
Clients are demanding more efficient and improved delivery of legal services. Automation opportunities that were previously limited are now a reality based on robust pattern recognition, in documents in particular. Artificial Intelligence is fast becoming a game changer in the delivery of legal services across multiple disciplines.
Amazon's delivery drones could soon live in giant hives
While you might expect a hive to be full of bees, a new patent filed by Amazon suggests that giant versions of the structures could soon be used to house drones. A patent published today shows a nine-story hive with space for hundreds of drones. While Amazon has not said when, or if, it plans to create the hives, the patent suggests that they could be used in'downtown districts' or'urban areas' where there is little space to build outwards. While you might expect a hive to be full of bees, a new patent filed by Amazon suggests that giant versions of the structures could soon be used to house drones. The hive is designed to accomodate landing and takeoff of unmanned aerial vehicles in urban settings.
Inspector gadget: how smart devices are outsmarting criminals
Richard Dabate told police a masked intruder assaulted him and killed his wife in their Connecticut home. His wife's Fitbit told another story and Dabate was charged with the murder. James Bates said an acquaintance accidentally drowned in his hot tub in Arkansas. Detectives suspected foul play and obtained data from Bates's Amazon Echo device. Bates was charged with murder.
Rise of AI-assisted art raises challenges notions of proprietary rights
Artificial intelligence is finding its way into the world of music, literature and art, raising never-before-considered questions about a creators' role. A team led by Shigeki Sagayama, professor of mathematical engineering and information physics at Meiji University, has created software that can compose a melody to accompany any given lyric. Available for use online, the automatic composition software, named Orpheus, has produced hundreds of thousands of pieces of music since its launch in 2007. Sagayama has developed a method to produce melodies based on the cadence of the Japanese language. He said AI works well in the field of musical composition as the established theories, rules and systems -- such as harmonics -- make programming feasible. Orpheus users can set the parameters to their preferences, ensuring various aspects like pitch and beat patterns reflect the character of the music they wish to produce, he said.
Why Your Brain Hates Other People - Issue 49: The Absurd
As a kid, I saw the 1968 version of Planet of the Apes. As a future primatologist, I was mesmerized. Years later I discovered an anecdote about its filming: At lunchtime, the people playing chimps and those playing gorillas ate in separate groups. It's been said, "There are two kinds of people in the world: those who divide the world into two kinds of people and those who don't." And it can be vastly consequential when people are divided into Us and Them, ingroup and outgroup, "the people" (i.e., our kind) and the Others. The core of Us/Them-ing is emotional and automatic. Humans universally make Us/Them dichotomies along lines of race, ethnicity, gender, language group, religion, age, socioeconomic status, and so on. We do so with remarkable speed and neurobiological efficiency; have complex taxonomies and classifications of ways in which we denigrate Thems; do so with a versatility that ranges from the minutest of microaggression to bloodbaths of savagery; and regularly decide what is inferior about Them based on pure emotion, followed by primitive rationalizations that we mistake for rationality. But crucially, there is room for optimism. Much of that is grounded in something definedly human, which is that we all carry multiple Us/Them divisions in our heads. A Them in one case can be an Us in another, and it can only take an instant for that identity to flip.
Uber Waymo Lawsuit: Court Filing Reveals Travis Kalanick Knew Fired Engineer Had Google Information
Alphabet's self-driving unit Waymo said ousted Uber CEO Travis Kalanick knew the company's engineer had Google information, lawsuit documents uploaded by TechCrunch show. Waymo sued Uber earlier this year claiming the startup benefited from stolen self-driving car technology from the Alphabet company. Legal action was taken after Google employees Anthony Levandowski and Lior Ron quit to start their own self-driving vehicle company, Otto. Uber bought Otto three months after it launched for $680 million in August 2016. Waymo claims both engineers stole autonomous technology secrets before they departed the company.
Will big data create a new untouchable business elite?
Will the ascent of artificial intelligence (AI) and machine learning built by big data create an unstoppable inequality of innovation? Last week we interviewed veteran investor Bill Janeway, and it was fascinating. Janeway described the way AI could allow an elite group of firms to innovate at speeds the rest of the world could only dream about. When I listened to his interview with Kenneth Cukier, it made me wonder whether economic ideas could be applied to the world of big data. In the spring of 2014, all my friends were suddenly holding copies of the same book.