Recommendation Systems
MK and
Recommendation Systems
as a network scales, it is inevitable that you need a way to sort & rank content.
web 2.0 solved it by ranking for popularity but a better approach could be to have a minimal quality threshold but not to try to rank things above that - so the search is not maximization-driven and leaves more room for serendipity.
h/t ken stanley
In the rush to copy TikTok, many Western social networks have misread how easy it is to apply lessons of a very particular short video experience to social feeds built around other formats. If you’re Instagram Reels and your format and interface are a near carbon copy, then sure, applying the lessons of my three TikTok essays is straightforward.... See more
Eugene Wei • How to Blow Up a Timeline
Constructor: Holistic Product Discovery for Ecommerce Results
constructor.io
Status Traps: Learning from Web2 Social Networks - a16z crypto
Andreessen Horowitz (AZ)a16zcrypto.com
