RSS3 joins NVIDIA Inception program to enhance its open AI infrastructure.
The collaboration aims to address challenges in integrating Web3 and AI.
RSS3 is developing infrastructure to provide Web3 native data to AI models.
Decentralized information platform RSS3 has joined NVIDIA's startup program to accelerate the development of its open and verifiable AI training infrastructure. The collaboration highlights the growing convergence of Web3 and AI, with both industries seeking to leverage each other's strengths.
The platform’s two-layer infrastructure combines the incentive layer of the open network with the data layer and will benefit from this advanced technology. Meng Pu, founder of RSS3, said that this cooperation will push the company to a new realm in the field of truly open artificial intelligence and open networks. In addition, RSS3 also stated that its goal is to transform the Internet and serve a wider audience.
The alliance between RSS3 and NVIDIA shows progress in addressing the challenges and integrating Web3 and AI. With both industries on the verge of significant growth, establishing strong infrastructure and standards is critical for future development.
Additionally, on July 17, RSS3 published an X-article focusing on the intersection of AI and Web3. The announcement highlighted that Web3 and AI startups have received nearly $2 billion in investments over the past two years.
The post discusses the importance of high-quality, structured data for AI models. While GPT-4 and Stable Diffusion rely on large datasets, the decentralized nature of Web3 complicates data aggregation. RSS3 is developing infrastructure to deliver Web3-native data in an AI-ready format to address these challenges.
Traditionally, users have provided a lot of data without receiving direct benefits. The integration of Web3 and AI solves this problem by allowing individuals to control and benefit from their own data, aiming to ensure a more equitable distribution of AI benefits.
In addition, efficient infrastructure that provides real-time Web3 data is critical for AI applications. Such infrastructure will simplify data access and improve the effectiveness of AI technology.
RSS3 joins NVIDIA Inception program to enhance its open AI infrastructure.
The collaboration aims to address challenges in integrating Web3 and AI.
RSS3 is developing infrastructure to provide Web3 native data to AI models.
Decentralized information platform RSS3 has joined NVIDIA's startup program to accelerate the development of its open and verifiable AI training infrastructure. The collaboration highlights the growing convergence of Web3 and AI, with both industries seeking to leverage each other's strengths.
The platform’s two-layer infrastructure combines the incentive layer of the open network with the data layer and will benefit from this advanced technology. Meng Pu, founder of RSS3, said that this cooperation will push the company to a new realm in the field of truly open artificial intelligence and open networks. In addition, RSS3 also stated that its goal is to transform the Internet and serve a wider audience.
The alliance between RSS3 and NVIDIA shows progress in addressing the challenges and integrating Web3 and AI. With both industries on the verge of significant growth, establishing strong infrastructure and standards is critical for future development.
Additionally, on July 17, RSS3 published an X-article focusing on the intersection of AI and Web3. The announcement highlighted that Web3 and AI startups have received nearly $2 billion in investments over the past two years.
The post discusses the importance of high-quality, structured data for AI models. While GPT-4 and Stable Diffusion rely on large datasets, the decentralized nature of Web3 complicates data aggregation. RSS3 is developing infrastructure to deliver Web3-native data in an AI-ready format to address these challenges.
Traditionally, users have provided a lot of data without receiving direct benefits. The integration of Web3 and AI solves this problem by allowing individuals to control and benefit from their own data, aiming to ensure a more equitable distribution of AI benefits.
In addition, efficient infrastructure that provides real-time Web3 data is critical for AI applications. Such infrastructure will simplify data access and improve the effectiveness of AI technology.