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As Valve's Steam Labs launch three new experimental features today, one has caught the interest of many Steam users: its new algorithm for game recommendations based on Valve's machine learning technology. Valve says the Interactive Recommender uses a "neural-network model that is trained to recommend games based on a user's playtime history, along with other salient data." The data is modified by two sliders that users can edit: one ranges from "popular" to "niche," while the other slider ranges from "older" to "newer" games. Rather than base recommendations around genre or cat
Valve have started a new initiative with PC gaming's flagship application named Steam Labs. As the name might suggest, it is centred around adding experimental new features to Steam for people to test. Steam Labs has started life as three experiments for us to jump into. The first, Micro Trailers, are game trailers limited to just six seconds in length displayed on a single page. The second - and perhaps most eye-catching - experiment is the Interactive Recommender. This is designed to take a look at your Steam preferences determined by your library, wishlist, playtime and other para