The PowerShell script now also accepts the names of the source and target workspaces as parameters and a flag to indicate if the target workspace should be created if it doesn't exist. These parameters make the script operate almost like a cmdlet itself. For example, you could use the command .\CopyWorkspaceNew.ps1 -SourceWorkspaceName "My Workspace" -TargetWorkspaceName "My Workspace Copy" to create a copy of the content, except workbooks and dataflows, from your personal workspace in a new workspace called "My Workspace Copy".

Dr. Daniel "Brian" Letort is a Fellow and Chief Data Scientist at Northrop Grumman Corporation. He has held various roles in his 18 year tenure, which have spanned software engineering, systems engineering, systems architecture, and chief architect. Throughout the roles, his interest have surrounded the strategic and forward-thinking use of data. Additionally, Brian serves as an adjunct instructor at both Colorado Tech and Southern New Hampshire University. Additionally, he serves as a lead faculty at Southern New Hampshire University.

Machine learning tools can be useful for historians to analyse large volumes of data and minimize noise, suggests a new study. How do we know if an event is historic? An event's historical significance depends on how it affects subsequent events in the future. But predicting this can be difficult: what may seem historic now may be deemed trivial by future generations. New research suggests that, even with machine learning tools, determining historical significance is difficult but these tools can still help historians.

Powered by AI technologies, businesses are transforming the way they operate. But what is the real opportunity for your business? Where can you implement tech to maximise the benefits and how do you need to adapt to take advantage? These are the questions being addressed at the cutting-edge of business transformation in Africa. Engaging with leading global multinationals as well as regional powerhouses, the AI Summit Cape Town event will uncover the true opportunity AI presents for the most forward-thinking enterprises, tackling the challenges around people-change management, upskilling the workforce, creating deeper relationships with customers and partners as well as understanding the business case.

One of the biggest problems in media today is so-called "fake news," which is so highly pernicious in part because it superficially resembles the real thing. AI tools promise to help identify it, but in order for it to do so, researchers have found that the best way is for that AI to learn to create fake news itself -- a double-edged sword, though perhaps not as dangerous as it sounds. Grover is a new system created by the University of Washington and Allen Institute for AI (AI2) computer scientists that is extremely adept at writing convincing fake news on myriad topics and as many styles -- and as a direct consequence is also no slouch at spotting it. The paper describing the model is available here. The idea of a fake news generator isn't new -- in fact, OpenAI made a splash recently by announcing that its own text-generating AI was too dangerous to release publicly. But Grover's creators believe we'll only get better at fighting generated fake news by putting the tools to create it out there to be studied.

A visit to the doctor seems one-on-one. But how will that feeling change when the data gleaned from that interaction takes on unprecedented value? It's a question that doctors and health regulators are grappling with as algorithms learn how to spot pneumonia, and health data becomes the chaff needed to train artificial intelligence. "Previously, the patient is agreeing to supply their very intimate personal information ... to the doctor to help with the diagnosis and management of their own health," said Jacob Jaremko, an associate professor in radiology and diagnostic imaging at the University of Alberta. You provide, for your own care, for your own benefit ... your data."

Sponsored Some would have us believe that the whole of Internet of Things will soon be artificially intelligent. Not only do we not think that's true, we think the Industrial Internet of Things (IIoT) – the part that does the meaningful work – will take longer than the rest of the connected device industry to acquire those AI features. IDC in November 2016 made a lofty prediction: some form of AI would make its way into all IoT deployments by this year. "By 2019, 40 per cent of all digital transformation initiatives, and 100 per cent of all effective IoT efforts, will be supported by cognitive/AI capabilities." A Skynet crafted from smart kettles and door locks by 2019?

Artificial Intelligence (AI) could help promote the development of material science and accelerate the invention of new materials, according to Chinese experts. Many key and core technologies that need breakthroughs in China are related to the material science, and AI could help in these areas, Zhao Zhongxian, an academician of the Chinese Academy of Sciences (CAS), who won China's top science award, said at a science forum opened in Dongguan, Guangdong Province, Monday. Traditional methods for material composition analysis are time-consuming and expensive. It takes an average of 10 years for a laboratory to develop new materials and 20 years for mass production. With AI technology, the development and application cycle of new materials is expected to be shortened by more than half.

From discovering drugs, to locating black holes, to finding safer nuclear energy sources, high performance computing systems around the world have enabled breakthroughs across all scientific domains. Japan's fastest supercomputer, ABCI, powered by NVIDIA Tensor Core GPUs, enables similar breakthroughs by taking advantage of AI. The system is the world's first large-scale, open AI infrastructure serving researchers, engineers and industrial users to advance their science. The software used to drive these advances is as critical as the servers the software runs on. However, installing an application on an HPC cluster is complex and time consuming.