artificial intelligence News for August 30 2017

Create Artificial Intelligence – EPIC HOW TO

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Robots are NOT going to replace all human accountants or bookkeepers. Given the improvements we have recently seen in computing, many professionals fear for their future as machines threaten to overtake them. Rather than fear changes that machine learning will have on accounting tasks, it’s an opportunity for accounting professionals to be excited. The profession is going to become more interesting as repetitive tasks shift to machines. There will be changes, but those changes won’t completely eliminate the need for human accountants, they will just alter their contributions. Let’s take a look at how machine learning will change accounting. Machine learning is the leading edge of artificial intelligence. It’s a subset of AI where machines can learn by using algorithms to interpret data from the world around us to predict outcomes and learn from successes and failures. As machines infiltrate accounting tasks to take over the more mundane and repetitive tasks, it will free up accountants and bookkeepers to spend more time using their professional knowledge to analyze and interpret the data to provide recommendations for their clients. Machine learning will propel innovation in accounting. When accounting software companies eliminated desktop support in favor of cloud-based services, accounting firms were forced to adapt to life in the cloud. Accounting departments and firms will be forced to adopt machine learning to remain competitive since machines can deliver real-time insights, enhance decision making and catapult efficiency. Rather than eliminate the human workforce in accounting firms, the humans will have new colleagues-machines-who will pair with them to provide more efficient and effective services to clients. Currently, there is no machine replacement for the emotional intelligence requirements of accounting work, but machines can learn to perform redundant, repeatable and oftentimes extremely time-consuming tasks.
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Artificial Intelligence, Automation, and the Economy

Today, in order to ready the United States for a future in which artificial intelligence plays a growing role, the White House released a report on Artificial Intelligence, Automation, and the Economy. This report follows up on the Administration’s previous report, Preparing for the Future of Artificial Intelligence, which was released in October 2016, and which recommended that the White House publish a report on the economic impacts of artificial intelligence by the end of 2016. These transformations will open up new opportunities for individuals, the economy, and society, but they will also disrupt the current livelihoods of millions of Americans. The new report examines the expected impact of AI-driven automation on the economy, and describes broad strategies that could increase the benefits of AI and mitigate its costs. AI-driven automation will transform the economy over the coming years and decades. Positive contributions to aggregate productivity growth; Changes in the skills demanded by the job market, including greater demand for higher-level technical skills; Uneven distribution of impact, across sectors, wage levels, education levels, job types, and locations; Churning of the job market as some jobs disappear while others are created; and. The loss of jobs for some workers in the short-run, and possibly longer depending on policy responses. It is possible that AI will not have large, new effects on the economy, such that the coming years are subject to the same basic workforce trends seen in recent decades-some of which are positive, and others which are worrisome and may require policy changes. At the other end of the range of possibilities, the economy might experience a larger shock, with accelerating changes in the job market, and significantly more workers in need of assistance and retraining as their skills no longer match the demands of the job market. At a minimum, some occupations such as drivers and cashiers are likely to face displacement from or a restructuring of their current jobs. Because the effects of AI-driven automation will be felt across the whole economy, and the areas of greatest impact may be difficult to predict, policy responses must be targeted to the whole economy. The economic effects of AI-driven automation may be difficult to separate from those of other factors such as other forms of technological change, globalization, reduction in market competition and worker bargaining power, and the effects of past public policy choices. Even if it is not possible to determine how much of the current transformation of the economy is caused by each of these factors, the policy challenges raised by the disruptions remain, and require a broad policy response. Continued engagement between government, industry, technical and policy experts, and the public should play an important role in moving the Nation toward policies that create broadly shared prosperity, unlock the creative potential of American companies and workers, advance diversity and inclusion of the technical community in AI, and ensure the Nation’s continued leadership in the creation and use of AI.Beyond this report, more work remains, to further explore the policy implications of AI. Most notably, AI creates important opportunities in cyberdefense, and can improve systems to detect fraudulent transactions and messages.
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Electrical Engineering and Computer Science

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A recent consumer survey indicates that educational tutoring is the human job most expected to be wiped out by Artificial Intelligence in the next five years. Bot.Me: A Revolutionary Partnership by PwC reveals the public’s steady acceptance of AI, particularly in customer service roles. Among 2,500 respondents, 58% saw tutoring by AI bots displacing real people in five years, even more likely than that of human tax preparers, health coaches, or doctors. The report’s lead author, PwC Head of AI, and Data & Analytics, Anand Rao however seeks to reassure that AI will not simply be “Taking our jobs,” in the education industry or beyond. “People will be working with AI, man and machine together. That’s how technologies have evolved in the past, there’s no reason to think it will be any other way in the future. As AI gets better, humans will stay involved, and get better with AI.”. In its various AI briefings, PwC makes the distinction between autonomous intelligence where machines act on their own, and augmented intelligence where people+machines to do things they otherwise couldn’t do. Says Rao, in augmented intelligence, “The human is still in the loop. Both humans and AI are learning, teaching each other. We will see more combination of man and machine in every sector.” He anticipates, “AI can shift human tasks from menial to strategic, freeing up time for innovation and the broader, bigger-picture thinking that can lead to transformation.” The PwC studies do not suggest how many or how extensively humans will be needed as partners in augmented AI systems, that is, what percentage of the disrupted workforce will make it into higher-order creative jobs vs. fall into unemployment. In another study among the myriad emerging on AI’s business and workplace impact, McKinsey & Company last year found that around 30% of tasks in 60% of occupations will be automated. With regard to education particularly, Rao says that university and professional or executive education providers will need to change the way they are educating, and what human roles and skills they are educating for, so students don’t end up qualified for jobs that are AI’d away. His unit at PwC has recently built artificial intelligence applications for university and EdTech client companies, particularly to enhance and personalize the human learning processes. “AI offers the ability to generate insight into how people learn, and to personalize learning to every individual for better results.”As you study, AI will learn from you,” says Rao. Adam Gordon MBA PhD is exec ed faculty in planning and foresight, and analyst in learning innovation.
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Artificial Intelligence

Using Kautz’ system, one can create a knowledge base about a specific domain. These information systems draw upon several areas of artificial intelligence to perform their operations. Knowledge is not always exact, therefore a robust knowledge representation scheme need to have some for of representing ambiguity. Knowledge can be characterized in terms of the “Strength” of the knowledge. The development of meaningful artificial intelligence will require that machines acquire some variant of human consciousness.
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Artificial intelligence takes centre stage in cyber security

Artificial intelligence-led cyber security technology has been in the spotlight at two major industry conferences in Las Vegas, signalling a firm trend in cyber …
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How smart is today’s artificial intelligence?

HARI SREENIVASAN: Artificial intelligence has long captured our imaginations. What concerns you about how artificial intelligence is already being used, or will be used shortly? HARI SREENIVASAN: While the defense industry is one use case of artificial intelligence, how close are we to building robots like the ones in the movies that are truly autonomous? HARI SREENIVASAN: Li is director of Stanford University’s artificial intelligence lab. HARI SREENIVASAN: How to infer meaning is not easy to teach a machine, even for this highly advanced dog robot.
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A.I. Artificial Intelligence YIFY

“AI – Artificial Intelligence” is the hardest kind of movie to review-but it’s also the most enjoyable kind of movie to watch. If Kubrick were in charge, the movie would have called it quits about twenty minutes earlier in an unsettling sequence that takes place in the ocean. The movie before the conclusion is so complex, moving, and involving in so many different ways the last twenty minutes didn’t even come close to spoiling the movie for me. The movie’s opening scene has a female robot begin to undress in a public office. Obvious, the filmmakers toned the aspects of “AI” down to warrant a gutless PG-13 rating-but why? The movie isn’t appropriate for children anyway, and it’s far too complex.
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