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[Regulatory Inflection Point's First-Mover Advantage: Can TRON Become the Home of "American Compliance Stablecoin"?]
In the summer of 2025, the United States officially welcomed a turning point in cryptocurrency regulation: the GENIUS Act has been signed into effect by the president, becoming the first stablecoin regulation bill in U.S. history; meanwhile, another systemic cryptocurrency market framework bill, the CLARITY Act, is also moving towards the Senate review stage. The regulatory boots have begun to drop, and the cryptocurrency industry is transitioning from the "era of ambiguity" to
TRX0.1%
ACT4.49%
ETH2.69%
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@gala_nft2 @dYdX dYdX charge charge charge, this data is amazing! The power of the community is truly strong, let's look forward to the future together!
GALA3.13%
DYDX4.08%
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@gala_nft2 @arbitrum DeFAI? Sounds like a superhero of Decentralized Finance! Looking forward to AI saving my on-chain operations 😂
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ARB1.98%
DEFI6.67%
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[Open Chat is about to be released: on-chain AI chat, how to achieve data vesting and incentives?]
When ChatGPT becomes the most mainstream AI interface globally, most people have already become accustomed to conversing with a black box system: inputting questions, receiving answers, and being unclear about the direction and rights of data usage. The Open Chat module that OpenLedger is building attempts to completely reconstruct this process — making AI chat not only an experience but also a contribution; not only a response but also a reward.
1. It's not a chat tool, but an on-chain vesting c
CHAT16.07%
PROMPT1.79%
COOKIE3.03%
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I feel that $SOL can't hold back anymore and is planning to rise.
I remember at the beginning of the year, $ETH and $SOL had a bit of a seesaw logic. I wonder how it will be this time, how much $SOL can rise, and will the rise of $ETH be dragged down?
#Shanzhai Season is really coming?
SOL2.92%
ETH2.69%
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[Not another AI platform: OpenLedger aims to create an on-chain AI city]
In today's world where "AI + blockchain" is gradually becoming a standard narrative, OpenLedger does not define itself as a type of "AI infrastructure" or "model platform," but rather constructs its positioning from the perspective of a "collaborative framework" and "public system." From the cold start performance of the testnet, the gradual opening of development tools, to the continuous expansion of the community incentive system, what OpenLedger is actually trying to build is an on-chain AI city prototype composed of m
PROMPT1.79%
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[Analysis of OpenLedger's smart contracts market mechanism]
1. Contracts are no longer "dead code".
Traditional blockchain smart contracts lack the flexibility for adjustment after deployment and usually can only passively wait for calls. However, in the architecture of OpenLedger, contracts are more like dynamic participating "agents"—they can both participate in execution based on on-chain tasks and bind datasets, inference models, and identity systems, thus becoming active units in the AI Agent network.
This paradigm of "smart contracts as agents" allows each contract not only to execute lo
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[Models are not assets, responsibility is? An analysis of OpenLedger's deployer responsibility mechanism]
In traditional AI systems, once a model is deployed, it is difficult to trace back to the developers and trainers behind it, let alone to assign responsibility for the model's output results. However, as AI increasingly penetrates critical decision-making processes, from financial transactions and medical judgments to public opinion generation and intervention, the issue of model responsibility has shifted from a technical controversy to a real pain point. OpenLedger is attempting a comple
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The video is really well done~~
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[OpenChat: When Chat Becomes an On-Chain Contribution]
1. What is OpenChat?
In the process of the decentralized AI network gradually taking shape, OpenLedger's OpenChat module provides an application scenario that combines "interactivity" and "traceability". It is not just a chat tool, but an on-chain collaboration platform that integrates message recording, data ownership, reputation building, and incentive distribution.
Every speech made by users in OpenChat is no longer "chat history" but is written as verifiable data assets on-chain. Through the "Proof of Attribution" mechanism, OpenChat c
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Cc0839vip:
The bright yellow watermelon of happiness, eating a bit will not bring out the J stocks, there are Gs, there are Fs, there are Gs, there are Fs, there are stocks, there are Fs, being perfunctory.
I heard that the Ethereum Foundation is dumping again, that scoundrel?
I heard that the Ethereum Foundation, this piece of trash, is dumping off again?
ETH2.69%
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How does Sapien achieve continuous upgrades of training data?
1. The long-term challenge of AI training: Data is not a one-time task.
In traditional AI training processes, once a training dataset is produced and used, the task is considered complete, and the contributor's role ends. The problem with this "one-time consumption" data model is evident: the training data lacks updates and cannot dynamically adapt to model iterations, leading to a bottleneck in the growth of model capabilities. Against the backdrop of continuously evolving human knowledge, if AI models cannot continuously obtain de
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I really dislike people who force you to receive notifications by tagging you in pictures.
And secretly circling people in the pictures is just trying to interact with you, and it's purely about harassment.
If I encounter something like this again, I will block him directly, so he can't circle me in the future.
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What does the Testnet 20 million interactions mean? OpenLedger's cold start answer sheet.
As of early July 2025, the OpenLedger Testnet has recorded over 22.18 million transactions, 1.23 million unique addresses, over 6.83 million blocks, and 20,000 contract deployments, with an average of about 1,500 new contracts added daily. These numbers are already impressive in the "Testnet" phase, but the more critical question is: what do they mean? What kind of cold start path can we read from them?
1. Real user interaction or a false appearance of volume?
In the face of high-frequency interactive tes
PROMPT1.79%
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[OpenLedger vs Bittensor: A Battle of Two AI Network Paradigms]
1. The Core Differences in Paradigm Controversy
In the AI x Web3 arena, OpenLedger and Bittensor represent two distinctly different network design philosophies. The former centers around a "data-driven network," emphasizing the infrastructure construction of data rights confirmation, sharing, and incentives; the latter is a typical "model scheduling network," which constructs an open market composed of AI model nodes that are ranked by performance and incentivized. Both attempt to address the resource allocation issue in the AI er
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AGENT5.01%
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GateUser-5f29b1e2vip:
It seems to be a company.
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