Source Artificial Intelligence (AI) is one of the few emerging technologies that promise to bring about some striking transformations in the blooming world of Android app development. When it comes to improving business relations, growth, and expectations, this technology has got the highest spotlight that cannot be overlooked by anyone looking to make a meaningful impact in the business world through technology. It is interesting to see how AI is growing rapidly to become the next big thing the world has ever known. Today, many app development companies around the world are not only interested in adopting AI but are also focused on putting the technology into the hands of people. Basically, they are looking to introduce it through apps in their mobile devices. By incorporating Artificial Intelligence (AI) features with Android app development, many smartphones will soon begin to perform some advanced technology roles such as landmark recognition, image labeling, barcode scanning, face recognition, and text recognition. Aside from helping to bring about amazing user experience, building Android applications equipped with in-built AI features can go a long way to simplify work for many smartphone users. Artificial learning ideas for mobile apps There are several ways a mobile app development company can apply Artificial Intelligence in an Android application. Depending on the task on ground, any app developers can learn to incorporate AI into their app development project just to get the help they need. Optimize the searching process It will be more intuitive and less troublesome for mobile users to engage in a searching process, perform suggestions, spelling corrections, and add a voice search when AI is integrated into a...
Black Hat The two penetration testers whose arrest and imprisonment made headlines last year are finally sharing their story, and it is a doozy. Florida man Justin Wynn and Seattle resident Gary DeMercurio, both pentesters at infosec shop Coalfire Systems, said the ordeal they experienced in Iowa last September could have been avoided had they just done a better job of documenting the scope of their audit in writing. That and not running into an ornery sheriff. A favorable judge died suddenly, too, mid-case. The pair were performing a routine penetration test at the Dallas County courthouse at night when they tripped an alarm, were collared by deputies, and, ultimately, charged with felony trespassing – a crime that can lead to up to seven years behind bars. Part of the problem, the two professional attackers told the Black Hat online conference today, was the imprecise terms of the penetration tests Coalfire was hired to perform at the request of the US state of Iowa. Communication, communication – and politics: Iowa saga of cuffed infosec pros reveals pentest pitfalls The two noted that, though, there was some boilerplate language in the contract that limited testing to daytime business hours – 6am to 6pm – they were led to believe by officials early on that the state wanted them to pay specific attention to security late at night. “The reality of that story is when they came to us, they only wanted physical pentesting at night after hours,” said DeMercurio. “The lesson learned from this is: record your calls.” After three nights of successful tests, the pair were approached by deputies...
Announcing .NET Core 3.1 We’re excited to announce the release of .NET Core 3.1. It’s really just a small set of fixes and refinements over .NET Core 3.0, which we released just over two months ago. The most important feature is that .NET Core 3.1 is an long-term supported (LTS) release and will be supported for three years. As we’ve done in the past, we wanted to take our time before releasing the next LTS release. The extra two months (after .NET Core 3.0) allowed us to select and implement the right set of improvements over what was already a very stable base. .NET Core 3.1 is now ready to be used wherever your imagination or business need takes it. You can download .NET Core 3.1, for Windows, macOS, and Linux: ASP.NET Core and EF Core are also being released today. Visual Studio 2019 16.4 was also released today and includes .NET Core 3.1. It is a required update to use .NET Core 3.1 with Visual Studio. For Visual Studio 2019 users, we recommend simply updating Visual Studio to 16.4 and instead of separately downloading .NET Core 3.1. Visual Studio for Mac also supports and includes .NET Core 3.1, in the Visual Studio for Mac 8.4 Preview channel. You will need to opt into the Preview channel to use .NET Core 3.1. Release notes: The changes in .NET Core 3.1 were primarily focussed on Blazor and Windows Desktop, the two new and large additions in .NET Core 3.0. This includes support for C++/CLI, which has been a regular request for developers targeting Windows. Before we take a look at...
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Artificial intelligence reveals previously unrecognised influences between great artists The task of classifying pieces of fine art is hugely complex. When examining a painting, an art expert can usually determine its style, its genre, the artist and the period to which it belongs. Art historians often go further by looking for the influences and connections between artists, a task that is even trickier.So the possibility that a computer might be able to classify paintings and find connections between them at first glance seems laughable. And yet, that is exactly what Babak Saleh and pals have done at Rutgers University in New Jersey.These guys have used some of the latest image processing and classifying techniques to automate the process of discovering how great artists have influenced each other. They have even been able to uncover influences between artists that art historians have never recognised until now.The way art experts approach this problem is by comparing artworks according to a number of high-level concepts such as the artist’s use of space, texture, form, shape, colour and so on. Experts may also consider the way the artist uses movement in the picture, harmony, variety, balance, contrast, proportion and pattern. Other important elements can include the subject matter, brushstrokes, meaning, historical context and so on. Clearly, this is a complex business.So it is easy to imagine that the limited ability computers have for analysing two-dimensional images would make this process more or less impossible to automate. But Salah and co show how it can be done.At the heart of their method, is a new technique developed at Dartmouth College in New Hampshire and...
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