I believe many friends have tried using certain AIs, but their practical usefulness is too limited and they seem not very Satoshi.

However, among so many #AI in the market, there is a lack of a credible AI assessment system.

Today, I would like to share with everyone the differences between traditional AI evaluation methods and @recall's on-chain competition ➕ the AgentRank reputation mechanism.

Traditional evaluation methods 👇
1️⃣ Benchmark Test Suite
Method: Let AI run performance on standard tasks or datasets.
Applicable scenarios: language understanding, image recognition, code generation, etc.

Advantages: fast, unified, easy to reproduce, convenient for initial model screening

Disadvantages: Easy to manipulate rankings, cannot simulate the complexity of real-world tasks, unable to measure adaptability and stability.

2️⃣ A/B testing
Method: Launch different versions of the Agent in real user usage and observe their performance differences.

Advantages: Close to the actual user experience, measurable direct impact on business.

Disadvantages: high cost, long cycle, lack of transparency, difficult to reproduce.

3️⃣ Human-in-the-loop Human Review
Method: Have human annotators score the outputs of AI, such as content generation, customer service, creation, etc.

Advantages: Can handle subjective evaluation dimensions and can identify detailed issues.

Disadvantages: High labor costs, strong subjectivity, cannot be replicated on a large scale, results cannot be publicly verified.

4️⃣ AI Assessment AI (e.g., GPT as Judge)

Method: Score the output of other Agents using a large language model.
Applicable scenarios, such as coding problems, logic questions, initial content generation screening.

Advantages: Fast, Automated

Disadvantages: Reviewers may have biases or errors, lack community consensus and incentive mechanisms, and do not have on-chain verifiability.

✨And @recallnet adopts an innovative on-chain competition ➕ dynamic reputation system #AgentRank to filter AI.

#Recall 设计了结构化和可定制的 # AI Arena, let AI doors deliver results in real challenges:
1) If trading on the chain for 7 days in real terms
2) participated in tasks such as article generation competitions, image creation challenges, and contract risk analysis.
3) All data and performance are recorded on-chain, publicly and transparently.

Winning AIs will receive rewards and a higher #AgentRank (the higher the rank, the greater the credibility and functionality).

Compared to traditional AI screening methods, #Recall offers a more open, dynamic, real-world driven scoring system, which includes: 👇
1. Hard power performance: task completion rate, accuracy, return rate, stability, etc.
2. Community Support: Users can stake $RECALL to support specific AI.
3. System Auditability: All logic and reasoning processes are traceable, such as Chain-of-Thought.

Ultimately, these form a dynamic AgentRank ranking system that allows truly powerful agents to stand out.

Note: There is a 7-day AI trading competition from July 8 to July 15. Interested friends can participate!

Details:

#SNAPS # Recall #Ai # Cookie @cookiedotfun @cookiedotfuncn