The benefits of machine translation are easy to see and experience for ourselves, but those practical applications are only one part of what makes the technology valuable. Microsoft and the government of New Zealand are demonstrating the potential of translation tech to help preserve and hopefully breathe new life into the Māori language. Te reo Māori, as it is called in full, is of course the language of New Zealand's largest indigenous community. But as is common elsewhere as well, the tongue has fallen into obscurity as generations of Māori have assimilated into the dominant culture of their colonizers. Māori people make up about 15 percent of the population, and only a quarter of them speak the language, making for a grand total of 3 percent that speak te reo Māori.

This country has something of a love/hate relationship with government jobs. We hate that most government workers are guaranteed overtime and coffee breaks when not working strictly 9-5. But then who wouldn't love being well paid, with early retirement and congressional-level benefits for such effort. Thus, for those of us in the private sector it might seem a bit of career karma that a recent federal study finds automation can eliminate five percent of all government jobs and 30 percent of the work the remaining employees do. I'd like now to offer the perspective I've gained over three decades helping build an industry-leading company designing the information technology systems now automating those government jobs and workloads.

The governments of most countries around the world are willing, if not necessarily eager, to aid in the development of advanced-level assisted driving. Yet, India is not'most countries'. In mid-2017, the country's transportation minister Nitin Gadkari said bluntly that his government "will not allow driverless cars in India." Why? "We are not going to promote any technology or policy that will render people jobless." This categorically states the government's worry.

Technology and banking want to walk hand in hand. For a number of years now, new fintech challengers have been coming up with new proposals and taking every link of the banking value chain to the next level, from payments and loans to financial inclusion, cybersecurity and everything in between. According to'Fintech: the experience so far' – a recent report by the World Bank and the International Monetary Fund (IMF) -developments ranging from artificial intelligence to mobile applications are "providing new solutions that seek to increase efficiency, accessibility and security of financial services provision." In 2017, says the IMF, fintech firms accounted for almost 20 percent of the total $90 billion valuation of new IPO's (at launch) by global financial sector firms. These fintech firms focus on everything from blockchain, to Artificial Intelligence to payments and crypto-currencies.

Thanks to approvals from the Food and Drug Administration (FDA) for applications such as primary disease diagnosis, digital pathology is rapidly becoming the new standard of care. However, this advancement creates challenges that artificial intelligence could help solve. Digital pathology enables capturing pathology information, such as whole slide images (WSI), and working with it digitally using a specialized scanner. Acquiring, studying and managing data in this way allows sharing between parties on a computer or mobile device. According to experts, the global digital pathology market was worth $689.2 million in 2018.

As I read Melanie Mitchell's "Artificial Intelligence: A Guide for Thinking Humans," I found myself recalling John Updike's 1986 novel "Roger's Version.'' One of its characters, Dale, is determined to use a computer to prove the existence of God. Dale's search leads him into a mind-bending labyrinth where religious-metaphysical questions overwhelm his beloved technology and leave the poor fellow discombobulated. I sometimes had a similar experience reading "Artificial Intelligence." In Mitchell's telling, artificial intelligence (AI) raises extraordinary issues that have disquieting implications for humanity. AI isn't for the faint of heart, and neither is this book for nonscientists. To begin with, artificial intelligence -- "machine thinking," as the author puts it -- raises a pair of fundamental questions: What is thinking and what is intelligence? Since the end of World War II, scientists, philosophers, and scientist-philosophers (the two have often seemed to merge during the past 75-odd years) have been grappling with those very questions, offering up ideas that seem to engender further questions and profound moral issues. Mitchell, a computer science professor at Portland State University and the author of "Complexity: A Guided Tour," doesn't resolve these questions and issues -- she as much acknowledges that they are irresolvable at present -- but provides readers with insightful, common-sense scrutiny of how these and related topics pervade the discipline of artificial intelligence. Mitchell traces the origin of modern AI research to a 1956 Dartmouth College summer study group: its members included John McCarthy (who was the group's catalyst and coined the term artificial intelligence); Marvin Minsky, who would become a noted artificial intelligence theorist; cognitive scientists Herbert Simon and Allen Newell; and Claude Shannon ("the inventor of information theory"). Mitchell describes McCarthy, Minsky, Simon, and Newell as the "big four'' pioneers of AI.

The UK's Department for Work and Pensions (DWP) is accelerating its use of automated systems to handle claims for benefits, in a move some fear will disadvantage welfare recipients. The DWP has hired nearly 1,000 new IT staff in the last 18 months, and increased spending to about £8m (US$10.3m) This new'virtual workforce' is to take over some of the jobs of humans. According to an investigation by The Guardian, which has unearthed further detail on the DWP's plans, one recent tender document requested help to build "systems that… can automatically carry out tasks without human intervention". As well as contracts with a number of multinationals, the department is working with UiPath, a New York-based firm co-founded by Daniel Dines, the world's first "bot billionaire", whose machine learning software is being deployed by the DWP to check benefit claims and detect fraud.

In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research.[1] The term was coined by analogy to the idea of a nuclear winter.[2] The field has experienced several hype cycles, followed by disappointment and criticism, followed by funding cuts, followed by renewed interest years or decades later. The term first appeared in 1984 as the topic of a public debate at the annual meeting of AAAI (then called the "American Association of Artificial Intelligence"). It is a chain reaction that begins with pessimism in the AI community, followed by pessimism in the press, followed by a severe cutback in funding, followed by the end of serious research.[2] At the meeting, Roger Schank and Marvin Minsky--two leading AI researchers who had survived the "winter" of the 1970s--warned the business community that enthusiasm for AI had spiraled out of control in the 1980s and that disappointment would certainly follow. Three years later, the billion-dollar AI industry began to collapse.[2] Hype is common in many emerging technologies, such as the railway mania or the dot-com bubble. The AI winter is primarily a collapse in the perception of AI by government bureaucrats and venture capitalists.

Working in partnership with the Scottish Government (SG) and with the assistance of the broader public sector and innovation community, Scottish Enterprise (SE) wishes to procure R&D services to create new products and services that will help in the Government's efforts to address the Climate Emergency. In doing so, we are specifically looking for solutions that exploit Artificial Intelligence (AI) techniques to deliver these solutions. This builds upon the proposition that Scotland has excellent capabilities in the application of AI. Working in partnership with the Scottish Government (SG) and with the assistance of the broader public sector and innovation community, Scottish Enterprise (SE) wishes to procure R&D services to create new products and services that will help in the Government's efforts to address the Climate Emergency. In doing so, we are specifically looking for solutions that exploit Artificial Intelligence (AI) techniques to deliver these solutions.

Artificial intelligence and automation are responsible for a growing number of decisions by pubic authorities in areas like criminal justice, security and policing and public administration, despite having proven flaws and biases. Facial recognition systems are entering public spaces without any clear accountability or oversight. Lawyers must play a greater role in ensuring the safety and accountability of advanced data and analytics technologies, says Karen Yeung at the University of Birmingham. The dream of artificial intelligence stretches back seven decades, to a seminal paper by Alan Turing. But only recently has AI been commercialized and industrialized at scale, weaving its way into every nook and cranny of our lives.