This is an experimental and work-in-progress R library for easily using Google TensorFlow, inspired by Google skflow package. This package aims to help R users to easily build popular deep learning models as well as customized models with flexible and desired deep architectures. Note that the style of the way the package has been developed is new and experimental. Any feedback would be appreciated. Check out demos for available usages.

Rather recently, Microsoft released an app using AI to detect a dog's breed. In my non-SitePoint time, I also work for Diffbot – the startup you may have heard of over the past few weeks – who also dabble in AI. To test how they compare, in this tutorial we'll recreate Microsoft's application using Diffbot's technology to see if it does a better job at recognizing the adorable beasts we throw at it! We'll build a very primitive single-file "app" for uploading images and outputting the information about the breed under the form. If you'd like to follow along, please register for a free 14-day token at Diffbot.com, if you don't have an account there yet.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

When Pham Quang Hung started studying Japanese at Foreign Trade University in Hanoi in 1994, he never imagined that Vietnamese children would one day be able to learn the language in elementary school. Now the first secretary for educational affairs at the Vietnamese Embassy in Tokyo can hardly wait to see the launch in September of a pilot project to offer Japanese lessons at three elementary schools in Hanoi. It will be the first time that Japanese language education has been offered at the publicly run primary school level in Southeast Asia, according to Japanese officials. The project follows the development of a Japanese program that the Vietnamese government introduced for middle and high school students in 2003. At present, English and French are the only foreign languages Vietnamese students can learn in elementary school.

Specifically, the assignment of meaningful tags (annotations) to each unique data granule is best achieved through collaborative participation of data providers, curators and end users to augment and validate the results derived from machine learning (data mining) classification algorithms. The annotations provide curation, provenance and semantic (scientifically meaningful) metadata about the data source and the data object being studied. The design and specification of a unique, meaningful, searchable and scientifically impactful set of tags can be achieved through collaborative (human-plus-machine) annotation efforts and through discovery informatics research. These steps will produce a searchable classification and indexing scheme for the curation, classification, discovery, reuse, interoperability, integration and understanding of digital repositories.

Meaningful classification labels and metadata can be derived autonomously through machine intelligence or manually through human computation. Human computation is the application of human intelligence to solving problems that are either too complex or impossible for computers. For enormous data collections, a combination of machine and human computation approaches is required. Specifically, the assignment of meaningful tags (annotations) to each unique data granule is best achieved through collaborative participation of data providers, curators and end users to augment and validate the results derived from machine learning (data mining) classification algorithms. We see very successful implementations of this joint machine-human collaborative approach in citizen science projects such as Galaxy Zoo and the Zooniverse (http://zooniverse.org/).

In the previous blog we have seen the theory and mathematics behind the Maximum Entropy and Logistic Regression Classifiers. Logistic Regression is one of the most powerful classification methods within machine learning and can be used for a wide variety of tasks. Think of pre-policing or predictive analytics in health; it can be used to aid tuberculosis patients, aid breast cancer diagnosis, etc. Think of modeling urban growth, analysing mortgage pre-payments and defaults, forecasting the direction and strength of stock market movement, and even sports. Reading all of this, the theory[1] of Maximum Entropy Classification might look difficult. In my experience, the average Developer does not believe they can design a proper Maximum Entropy / Logistic Regression Classifier from scratch.

"Computer systems can automatically detect and interpret what is happening on video surveillance cameras; Siri allows anyone to have a personal assistant in their pocket; Watson has beaten two former champions on Jeopardy and Google driverless cars have driven over 500 000km accident-free. Modern technology is increasingly intelligent," says Suren Govender, Accenture Analytics MD. With the growing availability of sensors, better algorithms for data analytics and growing computational power, these intelligent technologies are becoming more prevalent and are being incorporated in everyday life and business. "The cognitive era is about thinking itself – how we gather information, access it and make decisions," notes Hamilton Ratshefola, country GM at IBM South Africa. Cognitive analytics engines have the ability to build knowledge and learn, they understand natural language, reason and interact more naturally with human beings than traditional programmable systems.

Robots play football in a demonstration of artificial intelligence at the stand of the German Research Center for Artificial Intelligence at the CeBIT Technology Fair on March 2, 2010 in Hannover, Germany. Artificial Intelligence or AI is one of the favorite topics today. AI has the potential of changing the future and making life more convenient. However, some remain reserved because of the potential threats AI may bring to humanity. Learn what Slate readers think about AI here.

Airlines around the world are eager to take advantage of rapidly emerging technologies to improve their passengers' experience and become more efficient. But while executives recognize the opportunities, they know they can't do it alone. The two industry leaders in aircraft engines and technology are collaborating to offer carriers their expertise and ideas in a business where cutting 1 percent of fuel usage amounts to 250,000 in annual savings per plane. A recent PricewaterhouseCoopers report estimates digital tools in aircraft maintenance could save more than 100 million a year for a large carrier with a fleet of about 500 planes. "Our TotalCare maintenance program was revolutionary in the '90s, so we're pioneers ourselves, and by collaborating with a fellow pioneer like Microsoft, we can absolutely bring innovative digital solutions to airlines now," says Alex Dulewicz, head of marketing for services at Rolls-Royce's civil aerospace division.