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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).
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
~$2k/month
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).
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
~$2k/month
15 comments
Honest question: How will @farcaster compete with this? https://x.com/elonmusk/status/1978119427536093319
I recall the team thinking along those lines early on and seems from the below read that @dwr was correctly tracking. Grok doing what it’s doing is a massive challenge. https://dwr.email/challenges-with-byoa-and-social-networks
That post was from this thread. https://farcaster.xyz/dwr/0x2396a873
It’s related right? Anything moving this direction?
re: the Jack video quote that Elon tweeted 1. 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. 2. Making a good machine learning feed is hard and requires significant resources to make performant and real-time.
3. 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. 4. TBD if consumers would be willing to pay for your algo, though.
Turned this into a @paragraph: https://dwr.email/challenges-with-byoa-and-social-networks
3. seems doable 4. can monetize through a limited form of ads instead - being able to set who gets distribution is hugely valuable
3. Doable, but does it actually grow retained DAU vs. investing that effort in your default algo. 4. What incentive does the client have to give the attention value via ads to the algo developer. If the algo is good enough, dev just builds own client or client dev builds own algo.
Yes. You’re the expert here. But the fact we now have real Twitter alternatives is already a choice of its own. 👏
The key word is "at-scale". Farcaster isn't there yet. There's definitely a need to clean up feeds and surface engaging content but I don't think FC is at a place for a heavy investment in ML powered algos. PageRank and heuristic based algos should be good enough maybe with some ML sprinkles for classification.
Get Jack as a guest on MoZ 👀
You have interesting and informative posts at the same time. Hoping for more and more success for you
Follow me I'll follow you back
AI machine learning is too important know days for grooming your skills