
Crypto Squirtle/机灵的杰尼君|Mar 16, 2025 06:55
The next round of Crypto X AI will not just stay on the Memecoin track. A bear market is more suitable for in-depth research and understanding of more feasible narratives in order to reach the top of the wave in the future.
While organizing various reports on the AI track these days, I reminisced about the Crypto+AI stack released by Coinbase Ventures @ cbventures.
The ideal scenario for JK @ jonathankingvc to combine Crypto and AI is for AI agents to interact on various Crypto Infras. The software code (smart contracts) created by AI has led to a surge in the number of Dapps and enhanced user experience, allowing users to own and manage their own AI models and profit from them. And divide it into
1. A decentralized computing power provider dominated by Aethir as the main computing power layer
2. Expand the data layer of AI big models with the training dataset as the core
3. Various new AI based Infra (training/privacy inference/Agnet platform) middleware layers
4. Application layer
Nowadays, it seems that there are very few Crypto+AI application layer products that can be directly felt by retail investors, and the experience is not good. The most direct reason is that the foundation of several layers of the stack below the application layer has not been established yet.
Recently, starting from the model itself, decentralized AI and model training have been promoted through on chain incentives// (((((((FLock.io))))))) @flock_io , Realizing that training large models specifically for the Crypto track is necessary to prove oneself. Although the narrative of training a larger decentralized AI model is being developed, the feasibility of validating the roadmap through prominent product validation in segmented domains in the early stages of the project can be summarized as follows:// ((((((FLock. io))))) has accumulated more early supporters, so http://www.FLock. io)// The Web3 Agent Model for ((((FLock. io)))) has emerged.
If the Crypto AI Agent at the application layer is your intelligent assistant, then its large model is equivalent to your assistant's brain. Only with profound experience and knowledge can we handle every interaction and execute every instruction correctly for you.
The most prominent metric of the Web3 AI Agent model for http://((((FLock. io))) is the 75.93% FC precision matching accuracy. Simply put, it is easier to understand the Web3 AI model. Instructions that other models cannot recognize or speak incoherently, the Web3 AI Agent large model uses and http://IO.net By collaborating with industry partners and utilizing the AI Arena Task 1 collaboration framework, decentralized training can be used to reduce bias from a single data source, making AI agents based on Web3 AI Agent Model calls more practical and accurate.
At this point, we have to mention http:// ((((((FLock. io)))) is an ecological growth flywheel derived from the natural incentive attribute of Crypto products.
By incentivizing more high-quality model trainers through basic FLock, higher quality data and training skills have been achieved.
1. These contributions help build better AI models;
2. More powerful AI models can attract more feature rich and practical agents and Dapps to call;
3. Practical DApps and AI agents have strong market competitiveness and generate more revenue with the support of the Web3 model;
4. More calls from agents and Dapps will generate more model incentives for trainers;
5. These new data and usage feedback can further optimize and enhance AI models, while the prosperity of the ecosystem will also attract more high-quality model trainers to join through rewards and recognition.
Through this continuous cycle of positive feedback, the http://(((((FLock. io))))) ecosystem can achieve sustained growth and self enhancement.
AI Infra is still in its early stages, let alone the Crypto AI field. We look forward to seeing industry players like http:// ((((((FLock. io)))) With more infrastructure BUIDLER, only by laying the foundation of the model can we see a more stable and diverse explosion of application layers.
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