Over the weekend, I carefully read the recent interview with @ SaharaLabsAI Joint Creation Sean @ xiangrenNLP, which contains a lot of in-depth thinking about AI+web3. I would like to share my own views on the wonderful viewpoints presented in the interview 1) Sahara AI seizes an overlooked 'time window' Sean mentioned that the current development of AI is facing the problem of centralization of resources, talents, and data acquisition capabilities, and a few large companies have mastered the key elements of training larger models. I think this judgment hit the nail on the head. The current market is pursuing innovation in the application layer of AI agents, but Sahara AI has chosen to do "production relationship reconstruction" at a lower level. How to put it? The timing was cleverly chosen. There is indeed a contradiction in the current AI industry: while technological capabilities are becoming stronger, the threshold for participation is also increasing. The increasing trend of centralization of data, computing power, and talent has actually given blockchain an opportunity to "reduce dimensionality and strike". Sahara AI is essentially using Crypto's distributed collaborative thinking to solve the monopoly problem in the AI industry. This perspective is much more profound and imaginative than simply focusing on the application layer of AI+Crypto. 2) The technological path of "off chain computing+on chain trust" Sean emphasized the technical architecture of "off chain computing+on chain trust", which achieves AI's off chain operation and on chain authentication through TEE technology. I think this technical approach is quite practical and also very intelligent. Compared to projects that attempt to migrate all AI computing to the blockchain, implementing a trusted execution environment through TEE and then using on chain smart contracts to process ownership confirmation and profit sharing, this hybrid architecture ensures performance while achieving decentralization. Actually, it's about each taking their strengths. The key insight of this path is that it is not about reinventing AI, but about redefining its ownership and value distribution. Pragmatism in technology enables innovation in business models. 3) Reshaping the AI industry chain through data ownership confirmation Sean mentioned the need to automatically and transparently distribute profits to all participants through smart contracts, establishing true 'decentralized production relationships'. I think the most interesting thing is Sahara AI's redefinition of the value of data. In the traditional model, the contributions of data annotators and model trainers are often a one-time buyout, but Sahara AI wants them to continue to benefit from the long-term success of AI applications. In other words, we need to turn 'workers' into' partners'. Once this model is implemented, it may completely change the value allocation logic of AI. Imagine if every data contributor could receive a share of profits from AI applications that use their data, the incentive mechanism of the entire AI industry would undergo fundamental changes. This is not a minor improvement, but a restructuring of the entire industry's interest structure. 4) Challenges of DeAI existence Sean mentioned that in contrast to relying entirely on AI to generate data, the future should be a collaboration between AI and humans, where humans handle long tail scenarios that are difficult for AI to cover. This viewpoint is indeed forward-looking, because no matter how powerful the AI model is, there will still be edge use cases that cannot be processed, and human creativity and situational understanding abilities can precisely fill this gap. But on the other hand, the biggest challenge facing Sahara AI is also here: can decentralized data annotation and model training compete with centralized solutions in terms of quality and efficiency? After all, the reason why Microsoft and Google are able to train powerful AI models largely relies on their centralized resource allocation capabilities. The ideal of distributed collaboration is beautiful, but whether it can overcome the efficiency advantages of centralization in reality still needs time to verify. above. Overall, the path chosen by Sahara AI may be the direction with the most "fundamental transformative" potential in the current DeAI track. Because it is not incremental innovation under existing game rules, but an attempt to rewrite the game rules themselves. The probability of success is unknown, but once successful, the impact will be disruptive. In other words, we have been thinking about how existing chains can adapt to and support AI, but have we considered restructuring from the chain architecture first? To some extent, it is unknown whether there will be other new Crypto species outside the Ethereum smart contract chain in the future. After all, when technological paradigms undergo fundamental changes, infrastructure is often reshaped as well.