How Recommendation Algorithms Actually Work | Future - https://future.com/forget-open-source-algorithms-focus-on-experiments-instead

“We need to open up and be transparent around how our algorithms work and how they’re used, and maybe even enable people to choose their own algorithms to rank the content or to create their own algorithms, to rank it. To be that open, I think, would be pretty incredible.”

Understanding how the algorithm achieves its accuracy matters even if you’re not interested in TikTok or the short video space because more and more, companies in all industries will be running up against a competitor whose advantage centers around a machine learning algorithm.

There have been hundreds of investigative reports, technical analysis, research whitepapers, statistical studies, PhD dissertations, and more about how TikTok’s secretive recommendation algorithm works. TikTok’s recommendation system is without a doubt incredibly complex and impressive, but so too are the recommenders that Facebook, Instagram, and ... See more

A central challenge for any recommendation algorithm is the tradeoff between safe but somewhat boring recommendations that are similar to recommendations that worked well in the past (“exploitation”), and risky recommendations that are unlikely to be good but have a high payoff if they do turn out to be good (“exploration”). Explorat

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I like the way Instagram co-founder Kevin Systrom put it when discussing the recent launch of his news recommendation app Artifact. “[B]uilding the algorithm is enormously editorial. Because what you choose to train your algorithm on—the objective function, the data you put in, the data you include, the data you don’t include—is

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