Junior Austin Imperial and Senior Alex Hodge play with companion robot PARO at the School of Informatics & Computing's Intelligent Systems Open House event Friday afternoon at Georgian Room in the Indiana Memorial Union. The open house featured students presenting their research, live demonstrations, and the introduction of different types of robots in computing.

High-quality, low-cost online courses could be used to shift schools away from being "exam factories" and help students keep pace with the threat of automation, according to a new report by the Institute of Directors. The report argues that the internet allows schools to be more flexible and adapt learning towards "a future in which more and more work is taken over by robots or computers". Related: Welcome to the robot-based workforce: will your job become automated too? "The cost savings, convenience and flexibility that online learning offers has the potential to revolutionise education provision, but only if businesses and the education sector work together to capitalise on the potential of computer-based teaching applications to support employees in their pursuit of lifelong learning," the report said. Last year the CBI's director general also called for GCSEs to be scrapped and A-levels to be augmented by vocational courses. The report also calls for new tax incentives to encourage people to return to education, and to make it easier for employers to invest in their staff.

Mark Zuckerberg thinks you suffer from app overload, and last week he unveiled his solution: chatbots. Over the next few years, they may boost the bottom line of Facebook Inc. and other Internet companies while changing the way you use your smartphone. But first, they'll need to get a lot smarter. Chatbots--or bots, for short--are stripped-down software agents that understand what you type or say and respond by answering questions or executing tasks. Apple's Siri is a bot, and so is Amazon's Alexa.

Recent research has identified independent predictors of dementia to include age at diagnosis, transient ischemic attack and stroke status, and years of education, with vascular factors playing a greater role in disease pathogenesis than previously thought. The findings were presented at the 2016 annual meeting of the American Academy of Neurology (AAN). In the abstract, the researchers wrote that dementia encompasses a broad set of neurologic diseases, producing progressive declines in memory and/or thinking faculties, sometimes alongside personality and emotional disturbances. "Worldwide, approximately 35.6 million people have dementia, and this number is only expected to grow due to an aging population," they wrote. "Unfortunately, it is exceedingly difficult to predict who will develop dementia, let alone what type. This makes it difficult to mobilize various preventive strategies supported by mounting evidence."

John Searle is the Slusser Professor of Philosophy at the University of California, Berkeley. His Talk at Google is focused on the philosophy of mind and the potential for consciousness in artificial intelligence. This Talk was hosted for Google's Singularity Network. John is widely noted for his contributions to the philosophy of language, philosophy of mind and social philosophy. Searle has received the Jean Nicod Prize, the National Humanities Medal, and the Mind & Brain Prize for his work.

Sony will produce the new artificial intelligence with the user's ear and whispered. Spot news man seemed a little horse whispering, but it is not. Thank you for following us the development of the technology. Sony Xperia E is called the device aims to whisper into the ear of the user with artificial intelligence. When the device is placed in the ear phone owner put it on the news this veriyor.tek

If this were Jeopardy, the correct answer would be, What are some indicators that a patient will cancel their doctor's appointment? The answer to that question is the kind of information for which physicians and hospitals are prepared to pay. The machine learning engine that helps generate these answers propelled Arsenal Health's acquisition by athenahealth last week. In an interview with Arsenal Health CEO Chris Moses, he talked about how its business and product development plans fit into athenahealth's machine learning aspirations. Although the company started life in 2012 as Smart Scheduling, it recently changed its name to allow for wider applications of its approach. Moses co-founded the company with Joel Sutherland.

A downside of K-Nearest Neighbors is that you need to hang on to your entire training dataset. The Learning Vector Quantization algorithm (or LVQ for short) is an artificial neural network algorithm that lets you choose how many training instances to hang onto and learns exactly what those instances should look like. In this post you will discover the Learning Vector Quantization algorithm. This post was written for developers and assumes no background in statistics or mathematics. The post focuses on how the algorithm works and how to use it for predictive modeling problems.

In TensorFlow, during the training process of the models, the parameters are maintained in the memory as variables. When a variable is created, you can use a tensor defined as a parameter of the function as an initial value, which can be a constant or a random value.

Welcome to the 8th part of our machine learning regression tutorial within our Machine Learning with Python tutorial series. Where we left off, we had just realized that we needed to replicate some non-trivial algorithms into Python code in an attempt to calculate a best-fit line for a given dataset. Before we embark on that, why are we going to bother with all of this? Linear Regression is basically the brick to the machine learning building. It is used in almost every single major machine learning algorithm, so an understanding of it will help you to get the foundation for most major machine learning algorithms. For the enthusiastic among us, understanding linear regression and general linear algebra is the first step towards writing your own custom machine learning algorithms and branching out into the bleeding edge of machine learning, using what ever the best processing is at the time.