Machine learning

episodes

thinkers

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terms defined

The neighbourhood: machine learning and the ideas it travels with. Drag to roam, click a star for the episode, click a neighbour to travel.

Drag to roam · scroll to zoom · click a neighbour to travel · click a star for the episode

From foundational to frontier

Climb the spectrum. The most accessible conversations come first.

Start here

ACCESSIBLECOREFRONTIER

1h 30m

05-28-26

Coming soon

Every term the guests lean on, in plain language. Read one in full, or filter to find it.

collaborative filtering

A recommendation system method that suggests items based on user behavior patterns.

self-supervised learning

A type of machine learning where the system learns to predict parts of the input data from other parts.

The throughline across every conversation that touches this idea.

YouTube's recommendation system processes over 500,000 hours of new video daily, more than a human could watch in a lifetime.

YouTube uses collaborative filtering and clustering to offer diverse content recommendations, such as suggesting jazz to science viewers.

User interactions like likes, dislikes, and comments are key signals in YouTube's algorithm to gauge satisfaction and improve recommendations.

A-B testing on YouTube involves hundreds of variables to refine viewer experience and optimize algorithm changes.

Self-supervised learning is seen as a future pathway for video intelligence, but summarizing video content remains largely unsolved.

For the specialist

3 expert-level takeaways for a specialist reader.

At the frontier

1 open questions flagged across these conversations.

Who takes this idea on, by how often they return to it.