In this series of exploratory blog posts, we explore the relationship between recurrent neural networks (RNNs) and IoT data. The article is written by Ajit Jaokar, Dr Paul Katsande and Dr Vinay Mehendiratta as part of the Data Science for Internet of Things practitioners course.

California is the first state to adopt efficiency standards for computers and monitors, the state's energy commission announced this week. The commission approved regulations that limit the amount of energy computers and small servers can use when they are idling, asleep or turned off. The regulations for monitors will also limit the amount of energy the apparatus uses when it is turned on. "It's common sense that electronic equipment ought to consume a minimal amount of energy when it is not being used," energy commissioner Andrew McAllister said in a statement. The commission estimates computers and monitors in the state use more than 5,600 gigawatts-hours of electricity.

UNITED NATIONS – The "nightmare scenario" is rising for a hacking attack on a nuclear power plant's computer system that causes the uncontrolled release of radiation, the United Nations' deputy chief warned Thursday. Deputy Secretary-General Jan Eliasson told a Security Council meeting that extremists and "vicious nonstate groups" are actively seeking weapons of mass destruction "and these weapons are increasingly accessible." Nonstate actors can already create mass disruption using cybertechnologies -- and hacking a nuclear plant would be a "nightmare scenario," he said. The open council meeting focused on ways to stop the proliferation of nuclear, chemical and biological weapons by extremist groups and criminals. Members unanimously approved a resolution to strengthen the work of the council committee monitoring what countries are doing to prevent "nonstate actors" from acquiring or using weapons of mass destruction, known as WMDs.

It's no secret that artificial intelligence (AI) is rapidly transitioning out of R&D labs and into the mainstream market for enterprise applications. Leaders in the computer vision space, such as those developing autonomous cars, have continually made headlines as the new technology breaks ground. Applications beyond computer vision are increasingly gaining recognition, as well, including those dealing with non-spatial data, such as text and numbers. The most famous "non-vision" examples include well-known technologies beating the best of the best in highly complex abstract strategy games like Go, which is said to hold more possibilities than the total number of atoms in the visible universe. Do the examples set by industry leaders, like IBM's Watson, mean that AI technology is finally arriving for enterprise applications with the capability to power business transformation?

The California Energy Commission (CEC) on Wednesday passed sweeping energy efficiency standards for computers and monitors in an effort to reduce power costs, becoming the first state in the country to adopt such rules. The regulations promise to reduce energy consumed by computers by about one-third, saving ratepayers some $373 million in utility bills by 2027, and figure to have impacts far beyond California's state lines. Computers and computer monitors in the state use an estimated 5,610 gigawatts-hours of electricity, representing up to 3 percent of residential electricity use and 7 percent of commercial use. ""Such efficiency improvements are good for consumers, good for the electric system, good for the environment and frankly good for the green credentials of the manufacturers," said Andrew McAllister, a CEC commissioner who helped guide the new rules through a four-year process of consultations with industry that culminated in Wednesday's 5-0 vote in Sacramento.

Though artificial intelligence experts may cringe at the portrayals of humanlike AI in science fiction, some researchers are nudging us closer to those visions. "I think it's useful that your user interface not only understand your emotions, your personality, your tone, your motivations, but that it also have a set of emotions, personality, motivations," says Rob High, the CTO of IBM Watson. "I think that makes it more natural for us." Last month, High's company unveiled Project Intu, an experimental platform that allows developers the ability to build internet of things devices using its artificial intelligence services, like Conversation, Language and Visual Recognition. Someday, the system promises to let programmers create a staple character of sci-fi: the gregarious, hyper-connected AI like J.A.R.V.I.S. of Iron Man, KITT of Knight Rider, or Star Wars' C3PO.

The Jevons Paradox suggests that when technological advances increase efficiency of a resource, it results in an overall increase in consumption. Writing on the increased use of coal as a result of technological improvements, 19th-century economist William Stanley Jevons found that these improvements led to the development of new ways to utilize coal. In his session at 19th Cloud Expo, Mark Thiele, Chief Strategy Officer for Apcera, compared the Jevons Paradox to modern-day enterprise IT, examining how the Internet and the cloud has allowed for the democratization of IT, resulting in an increased demand for the cloud and the drive to develop new ways to utilize it. Speaker Bio Mark Thiele's successful career in IT spans 25 years and has focused on both operating roles and on driving cloud adoption across enterprises of all sizes. He has deep industry experience and extensive knowledge of the requirements of policy-driven cloud computing and drives cross-functional strategic initiatives as Chief Strategy Officer for Apcera.

California has become the first state in the U.S. to mandate energy-efficiency standards for monitors and a variety of computers, including notebooks, desktops, workstations and servers. The standards, which come into force starting from from Jan. 1, 2018, focus on the performance of computers in idle, sleep and off modes rather than putting limits on when they are in active operation, said the California Energy Commission, which on Wednesday adopted the new standards. California has more than 25 million computer monitors installed in homes and businesses, and the new standards recommend the use of higher efficiency LED backlights and screen technologies. The state has 21 million desktops, 23 million notebooks, 530,000 workstation computers and 300,000 small-scale servers. As a result of the move, the state hopes to save from the computer and monitor standards the equivalent of the electricity use of all homes in San Francisco and San Luis Obispo counties in 2015, equivalent to nearly 350,000 homes.

Since 2006, deep learning (DL) has become a rapidly growing research direction, redefining state-of-the-art performances in a wide range of areas such as object recognition, image segmentation, speech recognition and machine translation. In modern manufacturing systems, data-driven machine health monitoring is gaining in popularity due to the widespread deployment of low-cost sensors and their connection to the Internet. Meanwhile, deep learning provides useful tools for processing and analyzing these big machinery data. The main purpose of this paper is to review and summarize the emerging research work of deep learning on machine health monitoring. After the brief introduction of deep learning techniques, the applications of deep learning in machine health monitoring systems are reviewed mainly from the following aspects: Auto-encoder (AE) and its variants, Restricted Boltzmann Machines and its variants including Deep Belief Network (DBN) and Deep Boltzmann Machines (DBM), Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). Finally, some new trends of DL-based machine health monitoring methods are discussed.

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