加密inia
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Bullish
#加密立法新纪元
$TA will be listed on Binance Futures at 15:30 on July 21, and will go live on Alpha at 15:00
Project Introduction:
Trusta's proposed 'AI-driven trust layer' is an attempt to provide a systematic solution to this problem. I have reviewed some relevant materials, and its core idea is to analyze on-chain behavioral data through AI to 'profile' addresses, generating a credit-like evaluation system (such as MEDIA Score). This is no longer a simple DID or identity verification, but a step towards a dynamic, quantifiable 'reputation' system.
This reputation system has several potential values:
1. Reducing screening costs: It provides project parties with a low-cost, scalable tool to identify high-quality early participants. This is significant for scenarios such as airdrop distribution, whitelist qualifications, and community governance voting.
2. Incentivizing positive behavior: When on-chain reputation can be directly converted into economic benefits or governance power, users will be motivated to engage in genuine, constructive interactions, rather than mechanically 'brushing data'. This is a form of positive economic incentive.
3. Building composable trust: If Trusta's scoring can become a widely accepted 'trust oracle', then other DApps can directly integrate this reputation data, creating more complex application scenarios, such as credit lending and decentralized labor markets.
Of course, the challenges are also evident. Firstly, there is the 'black box' issue of the AI model; are its scoring criteria transparent and fair enough? Secondly, this will be an ongoing 'arms race', where attackers will continuously research model vulnerabilities in an attempt to 'deceive' the AI.
$TA will be listed on Binance Futures at 15:30 on July 21, and will go live on Alpha at 15:00
Project Introduction:
Trusta's proposed 'AI-driven trust layer' is an attempt to provide a systematic solution to this problem. I have reviewed some relevant materials, and its core idea is to analyze on-chain behavioral data through AI to 'profile' addresses, generating a credit-like evaluation system (such as MEDIA Score). This is no longer a simple DID or identity verification, but a step towards a dynamic, quantifiable 'reputation' system.
This reputation system has several potential values:
1. Reducing screening costs: It provides project parties with a low-cost, scalable tool to identify high-quality early participants. This is significant for scenarios such as airdrop distribution, whitelist qualifications, and community governance voting.
2. Incentivizing positive behavior: When on-chain reputation can be directly converted into economic benefits or governance power, users will be motivated to engage in genuine, constructive interactions, rather than mechanically 'brushing data'. This is a form of positive economic incentive.
3. Building composable trust: If Trusta's scoring can become a widely accepted 'trust oracle', then other DApps can directly integrate this reputation data, creating more complex application scenarios, such as credit lending and decentralized labor markets.
Of course, the challenges are also evident. Firstly, there is the 'black box' issue of the AI model; are its scoring criteria transparent and fair enough? Secondly, this will be an ongoing 'arms race', where attackers will continuously research model vulnerabilities in an attempt to 'deceive' the AI.
Disclaimer: Includes third-party opinions. No financial advice. May include sponsored content. See T&Cs.
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