[tsergiu]

Training a new model for each category is already possible today, but doesn't achieve the goal (mass-specialization).

The problem is that when you pre-train a model, you can only solve for the lowest common denominator of what every customer might want.

In ecommerce, for example, you might pre-train to get price, product name, reviews, and a few other things that are general to all ecommerce. But you won't pre-train it to get the mAh rating of batteries, because that's not common to the vast majority of customers (even within ecommerce). It turns out that most customers need at least a few of these long-tail properties that are different than what almost every other customer wants, even if most of the properties they need are common.

And so the challenge is to dynamically train a model that generalizes to all "battery sites" based on the (very limited) input from a customer making a few clicks on a single "battery site".