Google’s latest experiment is Keen: Automatic Version of Pinterest based on machine learning

Area 120, Google’s new creative incubator, launched a new project called Keen on Thursday to help users track their interests,media reported. The app is like a modern reflection on Google Alerts services, which allow users to monitor specific content on the web. In addition to not sending emails about Google’s search for new results, Keen uses a combination of machine learning technology and human collaboration to help users plan content around a topic.

Google's latest experiment is Keen: Automatic Version of Pinterest based on machine learning

Every area of personal interest is called “Keen” — a term commonly used to refer to a quick-thinking person. The idea came after co-founder C.J. Adams realized he had spent too much time unconsciously browsing feeds and pictures on his phone to fill his break. He realized that time could be used to better learn more about the subject spent on the subject he was interested in — perhaps he had been trying to study more, or the skills he wanted to learn.

To explore the idea, he and four of His Google colleagues teamed up with the company’s human-centric machine learning-focused human-focused human-focused human-based research program, the AI Research Program, to create what is now Keen.

Keen can be used either on the web or on Android, where users first log in with their Google account and then enter a topic they want to study. Adams suggests in an announcement about new projects that it could be like learning to bake bread, watching birds, or learning typography.

Google's latest experiment is Keen: Automatic Version of Pinterest based on machine learning

Keen may suggest other topics related to the user’s interests. For example, by typing Dog Training, Keen can suggest Dog Training Courses, Dog Training Books, Dog Training Tips, Dog Training Videos, and so on. When users click on the suggestions to track, their Keen will be created.

When the user returns to the keen interface, they will find a picture layout that links to web content that matches their interests. In the dog training example, Keen found articles and YouTube videos, blog posts, featured resource planning lists, and more. For each collection, the service uses Google Search and Machine Learning to help discover more content that is relevant to a given interest. The more users add to their favorite content, the more they organize, and the better these recommendations will be.

In fact, it’s like an automatic version of Pinterest. Once a “Keen” has been created, users can selectively add to their favorites, delete unwanted items, and share Keen with others so they can add content. The resulting collection can be public or private. Keen can also send users email alerts when new content is available.

Google's latest experiment is Keen: Automatic Version of Pinterest based on machine learning

To some extent, Google has used similar technology to drive its News Feed in Google apps. In this case, the News Feed will combine the user’s Google search history and their explicit topics to find news and information, and will be available directly to the user on the main screen of the Google app. However, Keen did not enter the user’s search history. It simply gets content based on the interests that the user enters directly.

And unlike News Feed, Keen doesn’t have to focus on recent projects. Any kind of information, useful information about the topic, can be returned. This can include related websites, events, videos, and even products. But as a Google project — and one that requires users to log in with Google — the data it collects is shared with Google. Keen, like google, is governed by the company’s privacy policy.

Although Keen is a small project within a large company, it represents another step in the continued personalization of the network. Technology companies have long recognized that connecting users to more of the content they’re interested in can increase their engagement, session duration, retention, and positive feelings about related services.