Recommender Systems

Not All RecSys Problems Are Created Equal

The industry’s outliers have distorted our definition of Recommender Systems. TikTok, Spotify, and Netflix employ hybrid deep learning models combining collaborative- and content-based filtering to deliver personalized recommendations you didn’t even know you’d like....

Prompt Fidelity: Measuring How Much of Your Intent an AI Agent Actually Executes

Spotify just shipped “Prompted Playlists” in beta. I built just a few playlists and discovered that the LLM behind the agent tries to meet your request, but fails since it doesn’t know enough but...

How Convolutional Neural Networks Learn Musical Similarity

audio embeddings for music advice? Streaming platforms (Spotify, Apple Music, etc.) must have the power to recommend recent songs to their users. The higher the recommendations, the higher the listening experience. There are various ways...

Why MAP and MRR Fail for Search Rating (and What to Use As an alternative)

often use Mean Reciprocal Rank (MRR) and Mean Average Precision (MAP) to evaluate the standard of their rankings. On this post, we are going to discuss why (MAP) and (MRR) poorly aligned with modern user behavior in...

Scaling Recommender Transformers to a Billion Parameters

! My name is Kirill Khrylchenko, and I lead the RecSys R&D team at Yandex. One in all our goals is to develop transformer technologies inside the context of recommender systems, an objective we’ve...

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