# Challenges with BYOA and social networks

Source: https://dwr.email/challenges-with-byoa-and-social-networks
Kiwi News: https://news.kiwistand.com/stories/Challenges-with-BYOA-and-social-networks?index=0x6661e41ca9e3eff5fc98850258d0d6926e86e9ce43a62ea946873cac69f3a9f62b6d3728
Submitted by 0xluo.eth on 2024-06-06 UTC, 7 upvotes, 1 comment

## Summary

Discussion of bring-your-own-algorithm (BYOA) for social networks raises several challenges, according to the article. It notes that world-class consumer apps in 2024 use machine learning based feeds, which consumers prefer by time spent, and that building a good ML feed requires significant resources. A feed marketplace would likely need a backend where developers upload models that clients run, raising privacy concerns. A developer building a Farcaster client, Kartik, reported that feed performance was much harder than expected and that running the backend cost about $2k per month for a few hundred active users.

## Article

There has been discussion recently about bring your own algorithm (BYOA) for social networks. Here are some challenges:

At-scale, world-class consumer apps in 2024 use machine learning (AI) based feeds. This is overwhelming consumer revealed preference in terms of time spent.

Making a good machine learning feed is hard and requires significant resources to make performant and real-time.

If you want to do a feed marketplace with good UX, you'd likely need to create a backend where developers would upload their models and the client runs the model in their infra. This obviously has privacy concerns, but maybe possible.

TBD if consumers would be willing to pay for your algo, though.

The likely outcome is a marketplace of clients, where each have a different algorithm that uses inputs (both public from the protocol and private from app usage) to tailor a model for each user.

PS — here are two data points from a developer who was building a Farcaster client: 1) feed performance is a challenging engineering problem and 2) running the backend is expensive (the client had a few hundred active users).

Kartik on Warpcast

1. building a mobile app, we rebuilt it 3x before we grokked it 2. feed latency/performance, much harder problem than we initially realized, hence scrapping custom feeds beyond lists

Farcaster

Kartik on Warpcast

~$2k/month

Farcaster

## Comments

**0xluo.eth**: Yes, building recommendation algorithms presents numerous challenges. That's why many are eager for Warpcast, with its vast user base and strong development capabilities, to excel in this area. These algos can also combat spam and bots while uncovering hidden high-quality users, making everyone's feed more engaging.