Loud: Attention Is All You Need

6/3/2025, 8:02:47 AM
Intermediate
Blockchain
The article elaborates on Loud's design philosophy, operational mechanism, and the game theory logic behind it, revealing how the experimental goal of "attention as value" is achieved through its token economic model.

This is not going to be a revolutionary paper on attention in neural networks; Instead this is an experiment on the purest of attention markets. An experiment that runs in perpetuity with no intervention.

A lot of thought has gone into it, so hopefully you read below, but if your attention span is fried, I’ve left a short TL;DR at the end too.

The Inspiration

We’ve often talked about attention economies in Web3 and how@KaitoAI"> @ KaitoAI has essentially built a platform which democratizes access to attention deals, accelerating the whole space as a result. In doing so, it also created one of the best proof of work incentive mechanisms ever existed: mindshare based rewards. This Web3 primitive allows projects to get the best possible output for every dollar put in; it creates a prize pool up for grabs for people willing to put in the work. This is the first piece of the puzzle.

The second piece is inspired by the recent success of@believeapp"> @ believeapp and its long term speculator-creator alignment model which works via volume and fees, subsidizing the creator’s work. Consider: What makes this so important is that the creator is the key driver of generating and maintaining attention for their own project.

Now what happens if we try to extract the best of both systems and create something that aligns incentives to maximize mindshare and outcome for token holders, forever?

Loud is an experiment which takes these crypto primitives in their purest form, distills them, and completely removes the middleman: the product.

It’s time to bring back some 3,3 game theory

The Experiment

What if we combine the best proof of work attention reward model, with one that generates fees in perpetuity for the creator? What happens when you reward people for talking about something, forever?

We get the purest form of 3,3. A bond between speculators and KOLs—completely removing the product in between. A perpetual engine of attention generation subsidized by speculators.

Fees paid by traders go and directly subsidize attention by creating a pot of money to be claimed; yappers in return fight for the top spots in the mindshare rankings, maximizing volume and attention output. I think you get the flywheel.

The goal of the yappers is to incentivize volume; The goal of the traders is to subsidize attention.

This is an experiment on if attention is really all you need to make something valuable. If something has attention, does price follow and vice versa?

How It Works In Practice

  • The $LOUD token will be tradable on Solana via@MeteoraAG"> @ MeteoraAG pools with a fee on each swap, collected in native token (SOL)
  • User can post about Loud to gain mindshare
  • @KaitoAI">@ KaitoAI feeds provide an unbiased view of top mindshare contributors for $LOUD
  • Users are able to check their positions on the leaderboard at stayloud.io, as well as registering their wallets for payouts
  • Once a week, fees (in SOL) get distributed to the top 25 mindshare contributors for the week, proportional to their share of mindshare
  • 20% of fees go to $KAITO stakers to boost the flywheel and align incentives
  • The flywheel continues, forever.

Loud is speculators subsidizing mindshare from KOLs in a symbiotic relationship in its purest form.

The token is completely worthless, but it becomes a proxy to attention.

Why a top 25 cutoff? Because as we said, what traders are paying for on each swap is attention. By creating a smaller pool, yappers are incentivized to work harder for the token holders and fees. Even when they get to top 25 - they are not safe, as the fees are distributed proportionally to mindshare contributions they have to fully maximize their share of attention and output.

*Note: Loud is an experiment, and as such, mechanisms will change and adapt as time goes on based on feedback while trying to minimize intervention. We are running the first large scale decentralized experiment on attention-value systems without external influence.

Disclaimer:

  1. This article is reprinted from [0x_ultra]. All copyrights belong to the original author [0x_ultra]. If there are objections to this reprint, please contact the Gate Learn team, and they will handle it promptly.
  2. Liability Disclaimer: The views and opinions expressed in this article are solely those of the author and do not constitute any investment advice.
  3. Translations of the article into other languages are done by the Gate Learn team. Unless mentioned, copying, distributing, or plagiarizing the translated articles is prohibited.

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