Original title: The Intersection of Ai and Web3.0 Technologies
Original source: Pantera
Original text compilation and translation: TechFlow
Editor’s note: Yesterday, the decentralized AI blockchain platform Sahara AI announced that it had completed a $43 million financing round, led by Binance Labs, Pantera Capital, and Polychain Capital. The financing will be used to further expand its global team, improve the performance of its AI blockchain, and accelerate the construction of its developer ecosystem.
In the current market situation, it is hard for such a large amount of financing not to attract attention. In order to let everyone know more about this project, BlockBeats found a podcast of Pantera in June this year to take everyone to review. Guests include Jacob Steeves, founder of Bittensor, Illia Polosukhin, co-founder of NEAR protocol, and Sean Ren, co-founder of Sahara. The host and the three guests discussed the combination of artificial intelligence (AI) and Web3, including how these two major fields promote each other and solve current challenges. During the conversation, Sean emphasized that Sahara has built a decentralized blockchain platform designed specifically for AI, mainly providing users with decentralized solutions for privacy and data sovereignty. He believes that the future development of AI requires a multi-level infrastructure to ensure that users will not sacrifice privacy and data sovereignty while enjoying AI functions.
Moderator: Matt Stephenson, Head of Research, Pantera
Guests:
Jacob Steeves, founder of Bittensor, a mining network that includes built-in token-based incentives to create a pure market for AI.
Illia Polosukhin, Co-founder of NEAR Protocol. NEAR is a chain abstraction stack that enables builders to create applications that scale to billions of users and across all blockchains.
Sean Ren, Co-founder of Sahara. Sahara is a permissionless, high-performance blockchain designed to securely deploy personalized autonomous AI with privacy and provenance.
Podcast source: Pantera
Original title: The Intersection of Ai and Web3.0 Technologies
Discuss three groundbreaking projects exploring the intersection of AI and Web 3.0 technologies.
Discussion Overview
· The theme of this discussion was the combination of artificial intelligence (AI) and Web3, exploring how these two fields can promote each other and solve current challenges. The discussion was moderated by Matt Stevenson, Head of Research at Pantera, and participants included Ilia Pellun, co-founder and CEO of Near Protocol, Jacob (also known as Const), a core developer of BitTensor, and Sean, CEO and co-founder of Sahara.
Jacob shared BitTensor’s efforts in creating a decentralized AI market, improving the quality of AI models and data privacy through market mechanisms and decentralized consensus mechanisms. He believes that the right incentive mechanism and efficient resource allocation are the keys to the success of decentralized AI systems.
Ilia started from the vision of Near Protocol, emphasized the importance of building a decentralized Internet, and introduced how the Near AI project promotes the development of a new generation of the Internet through automated programming and decentralized infrastructure. He pointed out that ensuring the security and privacy of user data is the key to building a decentralized Internet.
Sean started from the perspective of user privacy and data sovereignty, and introduced Sahara, a decentralized blockchain platform designed specifically for AI that prioritizes user asset sovereignty and security. He emphasized that the future development of AI requires a multi-level infrastructure to ensure that users will not sacrifice privacy and data sovereignty while enjoying AI capabilities.
BitTensor: Decentralized AI Market and Incentive Mechanism
Jacob introduced the decentralized network built by BitTensor, where anyone can join and contribute their computing resources and data. This decentralized approach can create a global AI market that anyone can participate in and benefit from.
Jacob emphasized the importance of the right incentive mechanism in decentralized AI systems, which can effectively solve the data privacy and computing resource allocation problems in the current AI and cryptocurrency fields. He mentioned that BitTensor has attracted a large number of teams and talents through market mechanisms, motivating them to drive innovation into the network. This competition mechanism is more efficient than traditional centralized organizations.
When discussing the security and privacy of decentralized AI systems, Jacob mentioned the use of decentralized consensus mechanisms to ensure the security and reliability of the system. He emphasized that the quality of AI models and data privacy can be improved through market mechanisms and decentralized consensus mechanisms. This approach can prevent single point failures and malicious attacks, and ensure the stability and security of the system.
Jacob also talked about how BitTensor can handle large-scale data and computing needs through a decentralized computing network. This approach ensures efficient allocation and utilization of computing resources, thereby ensuring the efficiency and reliability of the system.
Near Protocol: Building a decentralized internet with automated programming
Ilia discussed Near Protocol’s vision to build a new generation of the Internet through decentralized infrastructure and AI technology that enables greater security, privacy, and user sovereignty.
Ilia introduced the Near Protocol vision of building a trustless decentralized Internet. This Internet will provide infrastructure such as payment, identity, provenance, and smart contracts, enabling users to enjoy high-quality AI applications without sacrificing privacy, ensuring the security and privacy of user data. This requires not only advanced technical support, but also ensuring the transparency and verifiability of the system to enhance user trust.
Near was originally an AI project and later transformed into a blockchain project. Ilia emphasized how the combination of AI and blockchain technology can create more useful AI applications and promote the development of a decentralized Internet.
Ilia mentioned the relaunch of Near AI, with the goal of teaching machines to program and changing the way software is built. The relaunch of Near AI is an important step in realizing the vision of Near Protocol, which aims to promote the development of a new generation of the Internet through automated programming and decentralized infrastructure. This will enable computers to write code on their own based on users' natural language requests, providing a more efficient and verifiable software development environment.
Ilia emphasized the use of advanced encryption technology and strict access control mechanisms to ensure the security and privacy of decentralized AI systems. In addition, he mentioned the need for continuous security audits and monitoring to promptly detect and fix potential security vulnerabilities.
Ilia pointed out that decentralized solutions need to compete with centralized solutions in terms of user experience, AI model quality, and dataset value. These are key criteria for evaluating the actual feasibility of decentralized AI projects.
Sahara: A decentralized solution for user privacy and data sovereignty
Sean pointed out that as AI models become more powerful, they begin to affect people's jobs and monetization opportunities. For example, AI models can replace some simple design, text editing, and translation work. This raises concerns about user privacy and data sovereignty.
Sean emphasized that when users use AI functions, they often need to upload personal data, such as health records, financial reports, and chat records. This data may be used to train more powerful AI models, thereby further replacing the user's business. Therefore, protecting user privacy and data sovereignty becomes crucial.
Sahara is committed to creating a high-performance decentralized infrastructure based on the asset sovereignty and security of users. It aims to build a blockchain platform designed specifically for AI, enabling users to enjoy AI functions without sacrificing privacy, ensuring security, fairness and accessibility for all users.
Sean mentioned that Sahara’s high-performance decentralized infrastructure is designed to ensure the privacy and security of user data while providing elastic computing resources to cope with sudden computing needs. This design ensures that the system can maintain efficient and stable operation under high load.
· Sean believes that the future development of AI requires a multi-layered infrastructure to support user privacy and data sovereignty. This requires not only advanced technical support, but also ensuring the transparency and verifiability of the system to enhance user trust. Sahara's multi-layered infrastructure includes an execution layer, a computing layer, and a data layer, which are used for private user data storage, AI model training and reasoning, and data management and exchange, respectively. This multi-layered design not only ensures the efficient and stable operation of the system, but also enhances user trust and security. Sahara's vision is to promote a more fair, secure, and accessible AI ecosystem through technological innovation.
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