One of the most seasoned and lofty innovation organizations, Indian Institute of Technology (IIT) Kharagpur has picked Hyderabad to set up its Center on Artificial Intelligence and Advanced Manufacturing. Telangana government's emphasis on developing innovations like Artificial Intelligence (AI), Cyber Security, Data Analytics is at long last getting national consideration. "IIT-Kharagpur arranged in one corner of the nation. They don't get an excessive number of visitor personnel and industry pioneers so effortlessly. So they were exploring around to set up their inside in greater city. It has better access from a tech perspective. What's more, that is the point at which they came to Telangana and picked Hyderabad to set up the inside. While the Center of Excellence (CoE) will come up in the long run in AI and Advanced Manufacturing. Before that they intend to offer a multi month program called Foundation in AI and ML which will begin in February. Their board has endorsed the choice. We will sign the formal update of comprehension (MoU) soon," said Jayesh Ranjan, vital secretary, IT Department, Telangana.

Leading enterprise Robotic Process Automation (RPA) software company, UiPath, issued its top five predictions for 2019 in Europe. The predictions are those that the UiPath automation experts believe will have the biggest impact on enterprises in Europe and beyond over the next 12 months. Acceleration of automation emerges as the dominant trend, along with the integration of artificial intelligence (AI) to provide transformative new cognitive capabilities. "We believe enterprise leaders in Europe and the Middle East will accelerate automation to achieve their digital transformation strategies in 2019," said Kulpreet Singh, MD, EMEA, UiPath. "RPA has one of the fastest rates of implementation in the history of technology and 2019 will see that exponential growth continue, diversify and reach new audiences."

In early 2019 leaders of business and government will be meeting to address the challenges presented by technology and changing workforce dynamics. Many governments see the future of industry - Industry 4.0 - as involving a generational change in skills and needing a new vision of the security that comes with full-time employment. For the corporate sector, leadership will need to balance the promise of automation and advanced data with the financial health of the workforce. The Industry 4.0 that Davos attendees will address is, at its core, an issue of workforce transformation, not workforce displacement. It is defined by the intersection of longer lifetimes, new technology, evolving employment models and financial dynamics.

Police in Uttar Pradesh will now be able to solve cases with the help of an application that has a data base of five lakh criminals as well as artificial intelligence, face recognition and a host of other tech features, officials said Thursday. Named'Trinetra' or third eye, it was launched by UP Police chief OP Singh at a conference of senior officers during the annual'police week' celebrations in Lucknow, a senior official said. The database has been created after bringing together criminal records of the state police, the prisons department and the GRP that guards the railway network in the state. A senior official involved in developing the app said the database will help policeman on ground by deploying techniques like face recognition, text search, biometric records analysis, phonetic search, artificial intelligence (AI) and gang analysis to "zero in on the criminal" in a quick and targeted manner. "This app has a database of about 5 lakh criminals of the state and it will provide access of crime files and dossiers to my officers and personnel on the ground in a seamless and reliable fashion. This app is aimed to help them crack a case fast and ensure relief and justice to crime victims," Mr Singh told PTI.

Before you open up the presents under the tree, I've got some geekier gifts. In response to execs and luminaries from across the world of data and analytics sharing their predictions for the next year, I've dutifully compiled and stitched them together. Gather round, and soak up this year's batch, which focus on artificial intelligence, data regulation, data governance, the state of the Hadoop market, open source and "the edge." Predictions about artificial intelligence (AI) are all over the map. They range from optimistic and starry-eyed to a bit more skeptical and jaded.

One of the oldest problems in computer science was just solved by a single cell. A group of researchers from Tokyo's Keio University set out to use an amoeba to solve the Traveling Salesman Problem, a famous problem in computer science. The problem works like this: imagine you're a traveling salesman flying from city to city selling your wares. You're concerned about maximizing your efficiency to make as much money as possible, so you want to find the shortest path that will let you hit every city on your route. There's no simple mathematical formula to find the most efficient route for our salesman.

Going into 2019, the debates around AI and deep learning will shift from human against machine, to human and machine versus real issues. With IoT, virtual assistants, smart algorithms, automation and advanced robotics, HR firms have begun reshaping the workplace and streamlining manpower. A recent study revealed that 75% of 10 lakh registered companies in India have either invested or are going to invest in either AI- or deep learning-based technologies, or a combination of both. So, HR firms will learn to'stay digital' to revisit three important functions in 2019. Technology is at a stage where the engines adapt their guidance to show the patterns that work in the moment; not even two weeks ago.

Going into 2019, the debates around AI and deep learning will shift from human against machine, to human and machine versus real issues. With IoT, virtual assistants, smart algorithms, automation and advanced robotics, HR firms have begun reshaping the workplace and streamlining manpower. A recent study revealed that 75% of 10 lakh registered companies in India have either invested or are going to invest in either AI- or deep learning-based technologies, or a combination of both. So, HR firms will learn to'stay digital' to revisit three important functions in 2019. Technology is at a stage where the engines adapt their guidance to show the patterns that work in the moment; not even two weeks ago.

In this paper we present Meeting Bot, a reinforcement learning based conversational system that interacts with multiple users to schedule meetings. The system is able to interpret user utterences and map them to preferred time slots, which are then fed to a reinforcement learning (RL) system with the goal of converging on an agreeable time slot. The RL system is able to adapt to user preferences and environmental changes in meeting arrival rate while still scheduling effectively. Learning is performed via policy gradient with exploration, by utilizing an MLP as an approximator of the policy function. Results demonstrate that the system outperforms standard scheduling algorithms in terms of overall scheduling efficiency. Additionally, the system is able to adapt its strategy to situations when users consistently reject or accept meetings in certain slots (such as Friday afternoon versus Thursday morning), or when the meeting is called by members who are at a more senior designation.

The International Classification of Functioning, Disability, and Health for Children and Youth (ICF-CY) is a scaffold for designating and systematizing data on functioning and disability. It offers a standard semantic and a theoretical foundation for the demarcation and extent of wellbeing and infirmity. The multidimensional layout of ICF-CY comprehends a plethora of information with about 1400 categories making it difficult to analyze. Our research proposes a predictive model that classify self-care problems on Self-Care Activities Dataset based on the ICF- CY. The data used in this study resides 206 attributes of 70 children with motor and physical disability. Our study implements, compare and analyze Random Forest, Support vector machine, Naive Bayes, Hoeffding tree, and Lazy locally weighted learning using two-tailed T-test at 95% confidence interval. Boruta algorithm involved in the study minimizes the data dimensionality to advocate the minimal-optimal set of predictors. Random forest gave the best classification accuracy of 84.75%; root mean squared error of 0.18 and receiver operating characteristic of 0.99. Predictive analytics can simplify the usage of ICF-CY by automating the classification process of disability, functioning, and health.