Working on Farcaster and Warpcast. Longer thoughts at https://dwr.email

Daimo Pay. Build once, distribute everywhere

Founder @farquest & @wieldlabs.eth, investing @ miy.com // Previously Meta, Coinbase // cryptojcdenton.twitter // FID #251

i dabble with ai using open data from crypto https://alexpaden.tech @unbias

BDFL of Quilibrium, Eng @ Farcaster, ex-Coinbase, always opinionated, never hydrated

/quilibrium

Working on a ML model which will output an 'address score' similar to how credit scores work (~low is 300-500, mid 500-650, high 650+)

some interesting data:

me: 529.52
@alexpaden: 567.79
@cassie: 685.06
@jc: 698.19
@dwr.eth: 663.29
@dcposch.eth: 752.81

Founder far.quest & @wieldlabs.eth. Investing miy.com ventures. FID #274. Previously Square/Cash App. https://hiimnico.xyz/

I am planning to open-source the model. My training data and scoring system depend on a dozens of factor, notably num_transactions_score, transaction_frequency, total_value

Goal: decentralized consumer reports anyone?

I am training the model based on dozens of factors, like address age, unique counterparties, frequency, recipient distribution

I will open-source the model once it is trained. You can easily self-host

are you interested in a particular use cases?

Would be interested in the algo, how do you arrive at those numbers?

this is really great! amazing to have ->  a dummy frontend where you put an address and get the score.