Gaming retailer Steam will continue to allow controversial content on its online store, the company has confirmed. The announcement comes less than a month after Steam was heavily criticised for allowing a school shooting simulator, which allowed players to take on the role of a gunman on a murderous rampage inside a school, on its online store. Steam eventually pulled the video game, dubbed'Active Shooter', after more than 271,900 people signed an online petition calling for its removal. The move appears to have prompted the online retailer, which is owned by Valve, to review its screening policy. Steam has now confirmed that it will not remove any content from its online store simply because some users deem it to be in bad taste.

At its heart, AI is computer programming that learns and adapts. It can't solve every problem, but its potential to improve our lives is profound. At Google, we use AI to make products more useful--from email that's spam-free and easier to compose, to a digital assistant you can speak to naturally, to photos that pop the fun stuff out for you to enjoy. Beyond our products, we're using AI to help people tackle urgent problems. A pair of high school students are building AI-powered sensors to predict the risk of wildfires.

It goes without saying that Natural Language Processing, or NLP, is one of the most important and demanded technologies of the present day. You can find it everywhere as people communicate almost everything in language: it is present in web searches, advertisement, emails, customer service, language translation, summaries, etc. On my first acquaintance with NLP, I remember watching an online lecture where a lady was saying: "NLP is easy. Just install the NLTK library and with a minimum experience in Python you can start experimenting". Time flies, as our QA engineers like saying in their test logs.

On June 10 Michael Royzen, 18, will don his cap and gown and graduate from The Bush School in Seattle, Washington. Like many of his classmates, the soon-to-be high school grad has been busy finishing up projects and finals, celebrating, and preparing for the big day. He admits, however, that he has been slightly distracted by the recent launch of his seventh app for iOS, Apple's mobile operating system. SmartLens, designed to turn your phone into a search box, is Royzen's most sophisticated app yet, and is fittingly launching at a time when the teen software developer is considering future prospects and the shape of his life after high school. That will definitely involve entrepreneurship, but not before he first heads to college. KWHS caught up with Royzen to discuss his latest fascination with artificial intelligence (human intelligence exhibited by machines) and find out what's in store for a kid who has caught the eye of media outlets like GeekWire (he was the featured'Geek of the Week' in February 2017) and companies like Apple and Microsoft. An edited version of our interview appears below. Knowledge@Wharton High School: How does your SmartLens app operate?

If you're involved in technology, you have almost certainly been hearing a lot about artificial intelligence (AI) and machine learning (ML) recently. Digital Reality partners Google, Microsoft, Facebook, Apple and NVIDIA have all begun working on projects in this space. Google has announced the development of new purpose-built chips, Microsoft is offering online classes about how to use and develop AI solutions, Facebook and Apple are developing their own AI technology and companies like Intel and NVIDIA are releasing new hardware to support AI. These technologies seem to be pervasive across all industries, but two questions many organizations are asking are "What does it mean to me?" and "How do I use it?" The combinations of advanced algorithms and massive quantities of data promise to transform every industry by pushing businesses to new levels of efficiency and enabling distinct competitive advantages.

Your smartphone, smartwatch, and automobile (if it is a newer model) have AI (Artificial Intelligence) inside serving you every day. In the near future, more advanced "self-learning" capable DL (Deep Learning) and ML (Machine Learning) technology will be used in almost every aspect of your business and industry. So now is the right time to learn what DL and ML is and how to use it in advantage of your company. This course has three parts, where the first part focuses on DL and ML technology based future business strategy including details on new state-of-the-art products/services and open source DL software, which are the future enablers. The second part focuses on the core technologies of DL and ML systems, which include NN (Neural Network), CNN (Convolutional NN), and RNN (Recurrent NN) systems.

Patrick Winston's computer is learning about revenge, ambition, and murder. It knows that victory can make you happy. But it also knows you can't be happy if you're dead. The computer had to learn these things in order to read "Macbeth" -- or, rather, an extremely truncated version of Shakespeare's blood-soaked Scottish tragedy. At just 37 sentences, the rough summary reduces the Bard's immortal poetics to such clunkers as, "Witches had visions and danced" and "Lady Macbeth has bad dreams."

In this course you will build MULTIPLE practical systems using natural language processing, or NLP - the branch of machine learning and data science that deals with text and speech. This course is not part of my deep learning series, so it doesn't contain any hard math - just straight up coding in Python. All the materials for this course are FREE. After a brief discussion about what NLP is and what it can do, we will begin building very useful stuff. The first thing we'll build is a spam detector.

Make your first mobile app and game here. Learn how to code and make games in the popular Unreal Engine 4. Learn by building 6 actual games. Make next-level apps that use machine learning with Java, Android, TensorFlow Estimator, PyCharm, and MNIST. By taking this course you will make 3 complete mobile machine learning models and apps. We will build a simple weather prediction project, stock market prediction project, and text-response project.

Just last week, the CEO of this company announced that this system will be installed, for the first time ever, in an American high school and an American university. The names of the institutions have not been made public for obvious reasons, but in these pilot programs for this disruptive new technology, the exposure to real-world environments will serve to further hone and refine the algorithms. Why not just start installing them everywhere, you might ask? The reason is simple: Given the sensitive nature of this technology and the panic a false alarm may bring (just imagine a SWAT team rushing to the scene), it is of utmost importance that the algorithms are as refined as possible before a mass rollout can be effected. And there's nothing besides natural environment exposure that can do that. Think of machine learning as no different than human learning. You need constant stimulus from a variety of seemingly chaotic environmental factors for true artificial intelligence to be achieved.