The new-user problem

Everything so far needs history. Collaborative filtering needs your co-likes; taste vectors need enough ratings to place your point. So what happens the moment you install an app and the system knows literally nothing about you? This is the cold-start problem, and it bites in three ways: new users, new items, and brand-new apps with no data at all.

Scroll to watch the strategy shift as the very first signals trickle in.

Bridging the gap with content

The escape hatch is to use information you have before any interactions: the content itself.

• Content-based filtering describes each item by its own features — tags, genre, the creator, text or audio analyzed by a model (often into embeddings). A new item can be recommended the instant it's uploaded, because you can match its features to what a user already likes — no co-likes required.
• Popularity / trending is the universal fallback for a new user: with no personal signal, "what's popular right now" is a surprisingly strong default.
• Onboarding shortcuts the cold start by asking — "pick a few topics you like" — manufacturing a little explicit signal up front.

Cold start never fully ends

Even a mature app faces it constantly: every new video, song and product starts cold, and needs content features (or a deliberate burst of exposure) to gather its first ratings. It's not a one-time hurdle but a steady-state fact of life — which is why almost every real system is a hybrid of collaborative and content-based methods.

def score(user, item, n_interactions, k=10):
  alpha = n_interactions / (n_interactions + k)   # 0 when new -> 1 with history
  pop = popularity(item)                           # always available
  pers = personalized(user, item)                  # needs history (CF / vectors)
  return (1 - alpha) * pop + alpha * pers

Where we're headed

We can now recommend to anyone, new or seasoned. But there's a sting in the tail. Every recommendation changes what you do next, which changes the next recommendation. Follow that loop far enough and you get filter bubbles. The finale: the loop you're in.