Warpcast now uses an ML model to order casts. 

If you have many unread casts, the model decides which ones go at the very top of your feed. 

It's main purpose is to learn your preferences and show you the most interesting stuff first. I'll go into some more details on how it works in the thread below.

Technowatermelon. Elder Millenial. Building Farcaster. 

nf.td/varun

Today's model uses 4 main features to "rank" a piece of content: 

1. How often you like casts from the author 
2. How often the author casts
3. How many interactions the cast has 
4. How old the cast is

If you like someones casts a lot, their stuff will move higher in your feed. This is the primary factor used to rank your feed.

The model's predictive power (y-axis) increases as the number of likes increases (x-axis).

If you cast a lot, the predictive power begins to diminish. 

A high prediction score means that the model will bump the cast up in the feeds of people who like it and down in the feeds of people who wont.

Importantly, this doesn't mean you should cast less! 

Your casts still show up in feeds, the model is just less confident about changing its position in your feed.  

But if you are casting a lot of stuff that doesn't get engagement, trimming some of it might help the model get your content to the right users.

The third factor is engagement - the more likes a cast has, the more the predictive power is. 

Interestingly, the relationship isn't linear. It increases from 1 to 10, then decreases till 50 and then increases again. 

I'm not entirely sure why this happens yet, warrants more investigation.

The fourth important factor is time. 

This acts as a balance to the other factors - even if something is from someone you like, if its many hours or days old it's unlikely to show up at the top of your feed.

And that's a quick overview of how our model decides what casts to show you. 

We expect to be adding in more features over time like language, channel data etc which will make the model even better at finding stuff that is important to you.

Huge shoutout to @akshaan and @cmlad.eth who have built out all of our ML and feed infrastructure!

/frontend dev・founder/decentralized data wrangler /blockhead・ritual.net・UI/UX abstractionist・DeFi/web3 builder・dropout・24・prev /dydx・x.com/darryl__yeo

cc @darrylyeo the magical day we didn't know we were waiting for

glad we're pivoting away from this! I feel like I've been missing out tons of content from other users, just because I only see casts from those I interact with daily.

NFT enjoyooor, crypto student, $DEGEN🎩, intergalactic blockchain explorer. I'm not a moon boi, I'm a space man✨ 👨‍🚀✨ /memestoanend

Your cast is making waves! It's been curated by @spaceman-spiff and showcased on https://casterbites.com/bites. Keep inspiring the Farcaster community!

Remember, any Farcaster user can send and vote for the best casts of the day