How to build the TikTok recommendation engine, AKA, the worlds most addictive algorithm. (instructions in comments)

I’m totally building this.

This system is designed to continuously learn from user interactions to deliver personalized content recommendations.

Key components include:

– User interaction data being used as targets for training examples.
– A joiner that combines user features with these targets for online training.
– A model server and a serving parameter server that synchronize to maintain model consistency.
– Training workers that process batch training data and synchronize with a training parameter server.
– Techniques like collisionless hashing and dynamic size embeddings for user data.
– Frequent partial model updates to ensure the model reflects the latest data.

See comments for prompts to easily build and deploy on Azure.