This is not only an important moment for Grass, but also a major event for the entire AI industry.
Author: Grass
Translation: Deep Tide TechFlow
Information Express
Yesterday, we announced that users can now link their Solana wallet addresses to their Grass accounts. This is not only an important moment for Grass, but also a major event for the entire AI industry. Our plan has always been to thoroughly revolutionize the development of artificial intelligence, and the importance of this update lies in:
- ### Users contributing resources will receive corresponding rewards
The Grass network is able to track the data fetched by each node from the network. When this data is used for AI inference or training, there will be a clear link that associates the fetching behavior with the dataset. When each node is associated with a wallet address, we can allocate the value of AI back to the specific nodes that provide the data.
This represents a completely decentralized method of tracking resource usage. These records cannot be manipulated or hidden by any company, which means that AI will be fairer and more just, and individual users can actually benefit from it.
Considering that you have been providing these resources for the company for free, the only difference now is that you will actually receive rewards.
- ### Laying the foundation for transparency in AI training data sources
Through this feature, the network will not only track which node fetched which dataset, but also the specific source of the dataset—i.e., where the data came from on the network. At the moment of dataset fetching, the network will automatically compile the metadata of its source and the node that fetched it, and batch record it on the chain, forming a permanent record of the data source. This is a feature that other data supply solutions do not have, and we believe it is a key link in solving the biggest problems in current AI.
- ### Making AI more transparent and fair, reducing its centralization
Think about the biggest problems currently affecting AI. For developers, you cannot be sure that the dataset you are using has not been contaminated unless you re-fetch it yourself to confirm. For users, you cannot judge whether the agent you are interacting with is biased unless you can see the data that the developer chose to train it with. And for everyone, we face the risk of a few companies dominating AI and forming a monopoly on the most important technologies.
Grass aims to address all of these issues. When developers can unquestionably verify that the dataset comes directly from the expected source, they no longer need to worry about data contamination. When this information can be openly used for individual models, users can unquestionably know whether they are being presented with real information or fake news. Most importantly, when a system is created to distribute the value of AI to millions of people co-operating in the network, rather than a few large companies, we can work together to make it fairer and less exploitative.
Other Progress
In addition to the positive impact on training data acquisition, Grass has also broken through technological barriers by introducing Live Context Retrieval (LCR) for inference. This refers to real-time data fetching during inference to provide context for LLM. This is a feature currently under development and not available elsewhere, and we will soon release more information.
We believe a better world is possible, and the future is right in front of us. There is still time to save AI, and we are committed to it. The mission is ongoing. Thanks to all users for their vision and support for Grass.
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