“I’m hungry for more. What are companies doing in Prod?”

We’ve come so far, but there’s so much more! RecSys moves fast, and it’s worth knowing the concepts you’ll see at next year’s conferences. These ideas are already proven to some extent–none of them are pure science fiction–but they’ve not settled yet into their final forms.

Before we get into these few very modern ideas, it’s also worth noting all the things we’ve not covered in this book. The most heinous omission from this book is probably reinforcement learning techniques, and ideas related to conformal methods. Both of these are deeply important aspects of recommendation systems that you barely see present here. Both of these areas require a significantly different background and treatment, and thus were ill-suited to fit into the structure here. Additionally, neither are well introduced to the JAX ecosystem, and thus a much harder lift to scaffold.

When your scale is big enough, and the previous chapters are no longer buttering your toast, the following chapters will show you how to level up. At the time of writing, all of these methods are in production at 10B+ Valuation, Fortune 500 companies. Learn these concepts and then go build the next TikTok.