Automation Game' title='Automation Game' />Automation is a car company tycoon game in which you design and build cars from scratch. It is you who designs everything from the very core that is the engine, over. Price 29. 99httpswww. IDSERP,5133. 1Microsoft gets into the home automation game with Insteon. Smart Home Microsoft gets into the home automation game with Insteon partnership. The tech giants set to make its first foray into the smart home next month. A News and Information Resource for the Automation, Security AV Systems Industry Industry. Daily News Stories, Products, Industry Tools, Hundreds of Articles and more. TRACpac The Regional Automation Consortium. Wed, 0. 12. 02. TRAC The Regional Automation Consortium is a partnership of Marigold Library System, Northern Lights Library System, Peace Library System, Yellowhead Regional Library, and their member libraries. Using TRACpac you can search a combined catalogue of over 1. DVDs and other materialOur Expertise. At MODIA, living well isnt about how much we spend on the things we enjoy. From a simple flat panel. EISC is an international life sciences informatics company providing patented scientific software solutions for laboratory data automation. Its universal. Computer, Video Game Console, CCTV, Alarm Systems Repairs, Maintenance and Installations. We specialize in Burglar Alarm Systems, Access Control, Home Automation. Automation and anxiety The impact on jobs. SITTING IN AN office in San Francisco, Igor Barani calls up some medical scans on his screen. He is the chief executive of Enlitic, one of a host of startups applying deep learning to medicine, starting with the analysis of images such as X rays and CT scans. It is an obvious use of the technology. Deep learning is renowned for its superhuman prowess at certain forms of image recognition there are large sets of labelled training data to crunch and there is tremendous potential to make health care more accurate and efficient. Dr Barani who used to be an oncologist points to some CT scans of a patients lungs, taken from three different angles. Red blobs flicker on the screen as Enlitics deep learning system examines and compares them to see if they are blood vessels, harmless imaging artefacts or malignant lung nodules. The system ends up highlighting a particular feature for further investigation. In a test against three expert human radiologists working together, Enlitics system was 5. Another of Enlitics systems, which examines X rays to detect wrist fractures, also handily outperformed human experts. The firms technology is currently being tested in 4. Cooking Mama Iso Palm. Australia. A computer that dispenses expert radiology advice is just one example of how jobs currently done by highly trained white collar workers can be automated, thanks to the advance of deep learning and other forms of artificial intelligence. The idea that manual work can be carried out by machines is already familiar now ever smarter machines can perform tasks done by information workers, too. What determines vulnerability to automation, experts say, is not so much whether the work concerned is manual or white collar but whether or not it is routine. Machines can already do many forms of routine manual labour, and are now able to perform some routine cognitive tasks too. As a result, says Andrew Ng, a highly trained and specialised radiologist may now be in greater danger of being replaced by a machine than his own executive assistant She does so many different things that I dont see a machine being able to automate everything she does any time soon. So which jobs are most vulnerable In a widely noted study published in 2. Carl Benedikt Frey and Michael Osborne examined the probability of computerisation for 7. America had jobs at high risk of potential automation. In particular, they warned that most workers in transport and logistics such as taxi and delivery drivers and office support such as receptionists and security guards are likely to be substituted by computer capital, and that many workers in sales and services such as cashiers, counter and rental clerks, telemarketers and accountants also faced a high risk of computerisation. They concluded that recent developments in machine learning will put a substantial share of employment, across a wide range of occupations, at risk in the near future. Subsequent studies put the equivalent figure at 3. Britain where more people work in creative fields less susceptible to automation and 4. Japan. What determines vulnerability to automation is not so much whether the work concerned is manual or white collar but whether or not it is routine. Economists are already worrying about job polarisation, where middle skill jobs such as those in manufacturing are declining but both low skill and high skill jobs are expanding. In effect, the workforce bifurcates into two groups doing non routine work highly paid, skilled workers such as architects and senior managers on the one hand and low paid, unskilled workers such as cleaners and burger flippers on the other. The stagnation of median wages in many Western countries is cited as evidence that automation is already having an effectthough it is hard to disentangle the impact of offshoring, which has also moved many routine jobs including manufacturing and call centre work to low wage countries in the developing world. Figures published by the Federal Reserve Bank of St Louis show that in America, employment in non routine cognitive and non routine manual jobs has grown steadily since the 1. As more jobs are automated, this trend seems likely to continue. And this is only the start. We are just seeing the tip of the iceberg. No office job is safe, says Sebastian Thrun, an AI professor at Stanford known for his work on self driving cars. Automation is now blind to the colour of your collar, declares Jerry Kaplan, another Stanford academic and author of Humans Need Not Apply, a book that predicts upheaval in the labour market. Gloomiest of all is Martin Ford, a software entrepreneur and the bestselling author of Rise of the Robots. He warns of the threat of a jobless future, pointing out that most jobs can be broken down into a series of routine tasks, more and more of which can be done by machines. In previous waves of automation, workers had the option of moving from routine jobs in one industry to routine jobs in another but now the same big data techniques that allow companies to improve their marketing and customer service operations also give them the raw material to train machine learning systems to perform the jobs of more and more people. E discovery software can search mountains of legal documents much more quickly than human clerks or paralegals can. Some forms of journalism, such as writing market reports and sports summaries, are also being automated. Predictions that automation will make humans redundant have been made before, however, going back to the Industrial Revolution, when textile workers, most famously the Luddites, protested that machines and steam engines would destroy their livelihoods. Never until now did human invention devise such expedients for dispensing with the labour of the poor, said a pamphlet at the time. Subsequent outbreaks of concern occurred in the 1. March of the machine makes idle hands, declared a New York Times headline in 1. John Maynard Keynes coined the term technological unemployment and 1. New York Times referred to the revival of such worries as the renewal of an old argument. As computers began to appear in offices and robots on factory floors, President John F. Kennedy declared that the major domestic challenge of the 1. In 1. 96. 4 a group of Nobel prizewinners, known as the Ad Hoc Committee on the Triple Revolution, sent President Lyndon Johnson a memo alerting him to the danger of a revolution triggered by the combination of the computer and the automated self regulating machine. This, they said, was leading to a new era of production which requires progressively less human labour and threatened to divide society into a skilled elite and an unskilled underclass. The advent of personal computers in the 1. Yet in the past technology has always ended up creating more jobs than it destroys. That is because of the way automation works in practice, explains David Autor, an economist at the Massachusetts Institute of Technology. Automating a particular task, so that it can be done more quickly or cheaply, increases the demand for human workers to do the other tasks around it that have not been automated. There are many historical examples of this in weaving, says James Bessen, an economist at the Boston University School of Law.