🧠 Codatta @codatta_io AI learns to respect knowledge——

Following Jason @jason_chen998's article, an interesting discussion has emerged:

AI is still the hot topic and the center of attention; since OKX has already taken over Binance's Sahara, is it possible for Binance to seize Codatta, which OKX has invested in?

AI is constantly evolving, and no one knows who the future king will be, especially as we notice that large models are increasingly resembling exam experts.

As long as the "question bank" is extensive, emojis are plentiful, and answers are lengthy, it can score high on the leaderboard, harvesting a wave of "smart illusions."

But do we really need this kind of model ranking game?

What we want is not for AI to be better at exams, but for it to truly understand our questions, genuinely know how to solve problems, and understand what we really want.

At this point, the question arises:

Who should AI "learn from"? How can human expertise become a reliable, traceable, and incentivized infrastructure for AI?

1️⃣ What truly makes AI smarter is not more parameters, but human knowledge itself——

In the past three years, we have witnessed the leap from GPT-2 to Claude-3, with everyone frantically increasing parameters and stacking computing power, trying to squeeze out the limits of intelligence.

But a consensus is forming: the ceiling of AI is no longer computing power or models, but knowledge.

And true knowledge is held by millions of human experts.

Doctors, financial analysts, traders, pathologists, on-chain security researchers; this knowledge can never be "generated" out of thin air by GPT.

The problem is: these experts have no incentive to appear in OpenAI's training set.

3️⃣ What Codatta aims to solve is the issue of "silent experts in the AI world."

Many may ask what the relationship between Codatta and Sahara is:

If Sahara makes data "usable," then what Codatta does is make data "understandable."

Codatta is a decentralized knowledge protocol built on Web3 infrastructure,

Through on-chain proof, DID identity systems, staking endorsement mechanisms, and usage-based revenue distribution, it makes professional knowledge a truly "tradeable asset" and continuously rewards contributors.

The project can be summarized in one sentence: "Let AI subscribe to human knowledge and allow knowledge producers to own data assets."

It is not about creating another crowdsourcing platform, but about reconstructing the supply and demand relationship of knowledge assets:

1) Every piece of data/every evaluation will be recorded on-chain, auditable and traceable;

2) Professionals have DID reputation and data ownership, and can receive continuous rewards for contributing valuable data;

3) You can stake to support the data labels you recognize, and even combat cheating;

4) Data assets can be traded like NFTs, and even packaged into "knowledge funds";

5) Model evaluations are no longer "vendor black-box operations," but "user random questioning, on-chain voting," leaving no room for cheating.

In short: let AI learn to pay for knowledge, learn from humans, rather than learn from rankings.

4️⃣ Problems Codatta addresses:

The trust crisis in model evaluation: Existing evaluation platforms like Chatbot Arena have serious "ranking manipulation" issues, where model vendors can test multiple times and select the best version for release, lacking transparency;

The incentive gap in data supply: High-quality knowledge (e.g., medical image annotation, legal text labeling) still relies on expert labor, while traditional platforms (like MTurk) cannot provide continuous value distribution;

The ambiguity of knowledge data ownership: Professional data is privatized by platforms, and original contributors cannot enjoy its derivative value;

The disconnection of professional identity: Experts cannot transfer their reputation and achievements across different platforms, leading to repeated certifications and "information silos."

5️⃣ This is not a new platform, but a new order——

As a pioneer in the integration of AI and Web3, Codatta not only creates fair earning opportunities for data contributors but also provides high-quality, reliable data solutions for enterprises and institutions.

When AI no longer belongs only to a few large companies,

When every contributor can be recorded, rewarded, and respected, and when knowledge can participate in collaboration, circulation, and profit-sharing like an asset, we will truly begin to build a "future where humans tame AI."

6️⃣ Basic activities and entry points

Participation entry: https://app.codatta.io/referral/i696622t

You can find related tasks on the main page;

It might be good to get started, TGE is approaching, and it's a good opportunity to take advantage of it!

免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。