Instagram’s Explore Recommender System

It can go pretty wrong - look at a picture of a gun one time and IG will start shoving gun pictures down your throat, it's horribly non-forgiving and can't be tuned by the end user easily. You learn pretty quick to never look even once at something you don't want a whole lot of that same thing force-fed to you - on the other hand, start looking at huskies and you'll get tons of puppers filling your explore. :)

If instagram&#x27;s product KPIs were more inline with what I wanted as a user, this would be great...but they&#x27;re not and my explore feed is frequently filled with models, child musical prodigies, and other popcorn-esque content.<p>Compared that to Spotify, whose goal I presume is to get me to listen to more music and buy tickets and merch through their occasional marketing.<p>I&#x27;m a music snob but damn does Spotify get me great recommendations on new releases, my discover weekly, and more. Not only that, I&#x27;ve bought tickets through their frequent listener promotions probably more than 10 times at this point.

It&#x27;s so interesting how powerful word embeddings (or in this case account embeddings) are. This reminds me a bit of the 538 article[1] about doing math on subreddits - I&#x27;d be interested to see what sort of math you could do on instagram account embeddings. What happens when you subtract two celebrities from each other?<p>Also, I&#x27;m curious about the tradeoffs of revealing this information - does knowing this make it easier to game the instagram algorithm? From this article I&#x27;d think that having a more narrowly targeted account (for example someone putting selfies on one account and landscape photos on another) might make their embedding more similar to others. Another thought is that maybe someone liking a bunch of things unrelated to their content would make them wrongly appear in certain explore pages.<p>[1] <a href="https:&#x2F;&#x2F;fivethirtyeight.com&#x2F;features&#x2F;dissecting-trumps-most-rabid-online-following&#x2F;" rel="nofollow">https:&#x2F;&#x2F;fivethirtyeight.com&#x2F;features&#x2F;dissecting-trumps-most-...</a>

Is this really AI? This seems like simple classification and ranking. Honestly I didn&#x27;t see anything new in there that hasn&#x27;t been around for the past 10 years. KNN? NDCG? That&#x27;s entry level ML. TFA does throw around neural networks a bit, but doesn&#x27;t go into any detail.<p>EDIT: Maybe I&#x27;m just thrown off by the &quot;Powered by AI&quot; part of the article title. I was expecting more I suppose.

I&#x27;ve worked at a large e-commerce company before and it&#x27;s surprising how many of the basic techniques like embedding, seed accounts, round robin diversification are exactly the same. I used to wonder if some of the apparent idiosyncrasies in our system were shared by other companies. It&#x27;s uncanny how much of it is industry standard.

So IG ins&#x27;t using collaborative filtering? The whole process starts w&#x2F; simple NN search in the account embedding space. Those candidates are then passed to the ranking stack.<p>This makes sense w&#x2F; what I see in IG recs: past behavior is strongly reinforced w&#x2F; littler diversity. Filter Bubble&#x2F;Pigeon Hole problem.<p>So in conclusion, I would argue that the IG explore tab doesn&#x27;t have ANY explore at all!

Interesting, and looks like the present choices have evolved over time.<p>Seems like they are moving towards a structured RL implementation. There are elements of it, a follow-up post on some components would be interesting.

Honestly...it feels pretty standard stuff.