So, at the end of the day, we are going to see a fully personalized content everywhere on the Internet.
Everyone will see fully custom versions of all content, that is adapted to the consumer based on his lifestyle, opinions, and history. We all witnessed arousal of this Bubble pattern after latest USA elections and it’s gonna be getting worse. GANs will able to target content precisely to you with no limitations of the medium — starting from image ads and up to complex opinions, tread and publications, generated by machines. This will create a constant feedback loop, improving based on your interactions. And there is going to be a competition of different GANs between each other. Kind of a fully automated war of phycological manipulations, having humanity as a battlefield.
The driving force behind this trend is extremely simple — profits.And this is not a scary doomsday scenario, this actually is happening today.
Companies are now tracking how consumers react on social media to Super Bowl ads. They’re also studying how the brain responds to them. Could personalized Super Bowl ads be on the horizon?
Thirty-nine million Americans now own a smart speaker device, but the voice app ecosystem is still developing. While Alexa today has over 25,000 skills available, a number of companies haven’t yet built a skill for the platform, or offer only a very basic skill that doesn’t work that well. That’s where the startup Storyline comes in. The company is offering an easy to use, drag-and-drop visual interface for building Amazon Alexa skills that doesn’t require you to have knowledge of coding.
Using Google Clips to understand how a human-centered design process elevates artificial intelligence.
As was the case with the mobile revolution, and the web before that, machine learning will cause us to rethink, restructure, and reconsider what’s possible in virtually every experience we build. In the Google UX community, we’ve started an effort called “human-centered machine learning” to help focus and guide that conversation. Using this lens, we look across products to see how machine learning (ML) can stay grounded in human needs while solving for them—in ways that are uniquely possible through ML.
Amazon is in a better position than any other company to dominate ambient computing, the concept that everything in your life is computerized and intelligent. Amazon’s Alexa platform continues to get better while remaining open to third parties, unlike Apple’s Siri. Buying into Alexa now will future-proof your home.
Clips is basically a GoPro with a clip on the back that can also serve as a stand. The unique part is how Google embedded its machine learning skills directly into the camera, so you don’t actually take pictures with it. Instead, you just put Clips somewhere, then go about your day, and the AI will sit back like a voyeur until it sees the perfect shot, which it will then capture as a brief Motion Photo with ideal composition and a sort-of candid feel that you couldn’t get anywhere else.
“Facebook has this amazing business where they don’t even have to troll the Web for content. People just upload their stuff and then they serve it back out with ads attached, and they print money. It’s great to be Facebook,” Domingos said. But its “machine learning has to respond. And if it doesn’t respond, the whole site will be in much worse shape.”
The success of Pokémon Go is demonstrating that augmented reality (AR) is reaching the masses quickly and can be a robust tool to enhance student engagement and learning. Leveraging AR for instructional purposes has the potential to become a powerful medium for Universal Design for Learning (UDL) by providing new tools for multiple means of representation, action and expression, and engagement. One of the advantages of using AR applications and AR platforms is the ability to display context relevant digital information to support students’ needs in real time and in specific contexts. Although many educational AR applications are in their developmental stages, the rapid growth of AR is likely to continue. The examples presented in this article focus on how educators can use mobile devices and AR to apply the principles of UDL. Combining AR with the principles of UDL can help educators create lessons that are accessible, engaging, and powerful for a diverse range of learners.
