Yesterday, the DeAI training platform Flock in the Web3AI field officially announced a partnership with Alibaba's Qwen large language model. If I remember correctly, this should be considered the first integration collaboration initiated by web2 AI towards web3 AI. It not only allows Flock to truly break out of its niche but also revitalizes the morale of the web3 AI sector, which has been under pressure. Let me elaborate:
1) I have previously explained in the pinned tweet that the web3 AI Agent has been trying to stimulate the landing of Agent applications through Tokenomics and has also engaged in a rapid deployment competitive paradigm. However, after a wave of asset issuance FOMO, everyone realized that web3 AI has almost no chance of winning in terms of practicality and innovation compared to web2 AI.
Thus, the emergence of web2 innovative AI technologies like Manus, MCP, and A2A has directly or indirectly burst the bubble in the Web3 AI Agent market, leading to a bloodbath in the secondary market.
2) How to break the deadlock? The path is quite clear: web3 AI urgently needs to find an ecological niche that complements web2 AI to address issues that centralized AI in web2 cannot solve, such as high computing costs, data privacy issues, and fine-tuning of vertical scene models.
The reason is simple: purely centralized AI models will inevitably face concentrated problems in terms of computing resource acquisition channels and costs, as well as data resource privacy issues. In contrast, the distributed architecture attempted by web3 AI can utilize idle computing resources to reduce costs, while also protecting privacy through technologies like zero-knowledge proofs and TEE. Additionally, it can promote the development and fine-tuning of models in vertical scenes through data ownership and incentive contribution mechanisms.
Regardless of the criticisms, the decentralized architecture and flexible incentive mechanisms of web3 AI can have an immediate effect on solving some of the existing problems in web2 AI.
3) Speaking of the collaboration between Flock and Qwen, Qwen is an open-source large language model developed by Alibaba Cloud. Its outstanding performance in benchmark tests and the flexibility it allows developers for local deployment and fine-tuning have made it a popular choice among some developers and research teams.
Flock, on the other hand, is a decentralized AI training platform that integrates AI federated learning and AI distributed technology architecture. Its main feature is to protect user privacy through distributed training while keeping "data local," ensuring transparent and traceable data contributions, thereby addressing the fine-tuning and application issues of AI models in vertical fields like education and healthcare.
Specifically, Flock has three key components, which I will briefly share:
AI Arena: This is a competitive model training platform where users can submit their models to compete with others for optimization results and rewards. Its main purpose is to incentivize users to continuously fine-tune and improve their local large models through a "gamification" mechanism, thereby selecting better benchmark models.
FL Alliance: To address the cross-organizational collaboration issues in traditional sensitive vertical scenarios like healthcare, education, and finance, the federated learning alliance achieves enhanced model performance among multiple parties without sharing raw data through localized model training and distributed collaboration frameworks.
Moonbase: This serves as the neural hub of the Flock ecosystem, acting as a decentralized model management and optimization platform. It provides various fine-tuning tools and computing power support (computing power providers, data annotators). It not only offers a distributed model repository but also integrates fine-tuning tools, computing resources, and data annotation support, empowering users to efficiently optimize local models.
4) So, how should we view the collaboration between Qwen and Flock? Personally, I believe the extended significance of their collaboration is even greater than the current substance of the partnership.
On one hand, against the backdrop of web3 AI being continuously crushed by web2 AI, Qwen, representing the tech giant Alibaba, already possesses a certain level of authority and influence in the AI circle. Qwen's proactive choice to collaborate with a web3 AI platform fully demonstrates web2 AI's recognition of the Flock technology team. Meanwhile, the subsequent research and development efforts between the Flock team and the Qwen team will deepen the interaction between web3 AI and web2 AI.
On the other hand, the previous web3 AI was once merely a shell of Tokenomics, performing poorly in terms of actual utility. Although it attempted various directions like AI Agents, AI Platforms, and even AI Frameworks, it failed to produce truly effective solutions in areas like DeFi and GameFi. This unveiling by a web2 tech giant somewhat sets the tone for the future development path and focus points of web3 AI.
Most importantly, after experiencing a wave of pure "asset issuance" FOMO, web3 AI needs to regroup and focus on a target that can deliver real results.
In fact, web3 AI has never been just a channel for easier and more efficient deployment of AI Agents to issue assets, nor is it a game for raising funds through asset issuance. It needs to strive for collaboration with web2 AI, complementing each other's ecological niches, and truly demonstrating the irreplaceability of web3 AI in this wave of AI trends.
I am glad to see more cross-border collaborations like that between web2 AI and web3 AI being achieved.
免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。
