ITEM: A researcher at Telenor Group Research says he has developed a machine learning algorithm that uses mobile phone call records to determine literacy rates in developing markets by location. According to MIT Technology Review, researcher Pål Sundsøy says he started with a regular survey – conducted by a professional agency for a mobile operator – covering 76,000 mobile users in Asia that collected the user's mobile number and asked them if they could read. Sundsøy matched that data against the mobile operator's call data records, which enabled him to work out where each user was, who they called, for how long, etc. Then he crunched 75% of the correlated data to detect patterns with illiterate users, and used the remaining 25% to see if those patterns could identify illiterate people and areas where there is a higher proportion of illiterate people. All in all, he says, his machine learning algorithm can spot illiterate individuals with surprising accuracy.

It has been seen that Microsoft is trying to push for development of chatbot or bots. On Friday, it was observed that the company had announced new features such as group chat functionality, visual cards, and for its Skype Bot Platform they announced third-party service sign-in. It was also announced by the company, that to create a single entity called Microsoft Bot Framework V3 they had merged Skype Bot developer tools and Microsoft Bot Framework. Microsoft's latest update states that Skype Bot Platform has around 30,000 developers, which was announced back in March. Apart from presenting users with visual cards such as images and carousels, bots for group conversations can be made by developers with the help of the update to the Skype Bot Platform.

String just means string and number means number," according to Rosenwasser. Synopsys releases Coverity 8.5 Version 8.5 of Coverity, the static analysis tool of Synopsys, has changes and updates to the security analysis and reporting capabilities of the product. Python Serverless Microframework for AWS The AWS Developer Tools team announced the preview of the Python Serverless Microframework for AWS, which makes it possible to run and create API applications without managing any servers. Future changes to Minikube include native hypervisor support for OS X and Windows, improved support for Kubernetes features, and configurable versions of Kubernetes.

Microsoft has rolled out the beta release of TypeScript 2.0. Developers can get it after downloading TypeScript 2.0 Beta for Visual Studio 2015, which will require VS 2015 Update 3. This release includes new features like a workflow for getting TypeScript type definition files. "Null and undefined are two of the most common sources of bugs in JavaScript," and before this release, null and undefined were in the domain of every type. "If you had a function that took a string, you couldn't be sure from the type alone of whether you actually had a string--you might actually have null."

The working-process to accomplish this Forbus explains in the following way: "Given a new situation, the machine will try to retrieve one of its prior stories, looking for analogous sacred values, and decide accordingly."

MIT researchers have developed a computer system that independently adds realistic sounds to silent videos. Although the technology is nascent, it's a step toward automating sound effects for movies. In a series of videos of drumsticks striking things -- including sidewalks, grass, and metal surfaces -- the computer learned to pair a fitting sound effect, such as the sound of a drumstick hitting a piece of wood or rustling leaves. The findings are an example of the power of deep learning, a type of artificial intelligence whose application is trendy in tech circles. With deep learning, a computer system learns to recognize patterns in huge piles of data and applies what it learns in useful ways.

Renewable energy like solar and wind power are changing the way we generate electricity. Our energy production is becoming cleaner and cheaper, and in many countries renewables are starting to overtake fossil fuels as the primary power source. But one of the biggest problems with renewables has yet to be solved: what happens if it's cloudy? More specifically, the problem is that renewable energy sources can never provide a constant source of power. No matter how many solar panels you build, they all provide zero power when the sun goes down.

There's even a subreddit dedicated to adding realistic color to old black and white images. It can be a time-consuming process and you need to be very familiar with Photoshop -- or similar software -- to do it convincingly. However, Algorithmia has implemented the Colorful Image Colorization algorithm created by Richard Zhang, Philip Isola and Alexei A. Efros. This algorithm automates the process of colorization by leveraging Algorithmia's cloud-based GPU network of hosted trained deep learning models. Deep learning is itself a fascinating and challenging field in computing. The idea is to create algorithms which can accurately model high-level abstractions that are typically exclusive to the human brain, such as recognizing and understanding how to accurately color a black and white image based on contextual understanding, for example.

With recent developments like the launch of Facebook's chatbot store, Apple's acquisition of Emotient, and the release of Viv, a virtual assistant from the founders of Siri, there's no doubt that artificial intelligence (AI) has started to quickly proliferate across consumer applications. Nonetheless, many of these new applications are still more novelty than necessity as their functionality is rudimentary at best, though we've come to rely on them daily – from Amazon product recommendations to Facebook facial recognition (auto tagging). Until consumer-facing AI can usher in new technological advancements that provide deeper and more human-like interaction, it still has a long way to go before it reaches its tipping point. Enterprise AI, however, offers immediate applications that help solve problems that many companies and workers face today, such as data overload. Companies across a wide range of industries have already taken advantage of AI capabilities in order to help improve both internal and external processes.

Google has acquired Moodstocks, a Paris-based startup that specialises in smartphone image recognition as part of its continued efforts to boost its own artificial intelligence (AI) research, development and capabilities. Announced in a blog post on 6 July, Vincent Simonet, head of Google's research and development (R&D) centre in Paris, says the tech giant's latest purchase is proof of its commitment to the promising sector. "Many Google services use machine learning to make them simpler and more useful in everyday life such as Google Translate, Smart Reply Inbox, or the Google app," Simonet wrote in French. "We have made great strides in terms of visual recognition: Now you can search in Google Pictures such as'party' or'beach' and the application will offer you good pictures without you needing to categorise them manually. But there is still much to do in this area. And this is where Moodstocks comes in."