- Near Protocol’s open-source AI model aims to surpass Meta’s Llama, reaching 1.4 trillion parameters.
- Decentralized AI model by Near Protocol prioritizes privacy, with rewards for contributors via token funding.
- Near Protocol’s AI project to address centralized AI privacy risks, promoting a collaborative research hub.
Near Protocol has announced its plan to create the world’s largest open-source AI model. This initiative, launched during the Redacted conference in Bangkok, Thailand, will feature a model with 1.4 trillion parameters, surpassing the size of Meta’s Llama model.
Near Protocol aims to crowdsource research and development contributions through a new AI hub, where researchers and other contributors can collaborate.
Starting November 10, the platform will train a smaller 500-million-parameter model as part of the initial phase. The project will gradually expand, following a multi-stage structure with seven models. At each stage, Near Protocol will retain only the top contributors, ensuring quality and efficiency in the model’s development.
Near Protocol also intends to monetize the model while prioritizing data privacy by using an encrypted Trusted Execution Environment. Contributors will receive rewards through this system, fostering continuous involvement in the project.
Funding Model and Resource Allocation
Near Protocol plans to finance the model’s development, estimated at $160 million, through token sales. According to co-founder Illia Polosukin, tokenholders will benefit from the project’s long-term use, as the model generates value over time. He emphasized the project’s sustainable funding loop, where reinvestments support ongoing advancements in AI model development.
Polosukin, instrumental in developing ChatGPT, believes Near Protocol can raise the necessary funds. Co-founder Alex Skidanov, previously with OpenAI, agrees but notes the logistical challenges. He highlighted the need for extensive GPU resources, a requirement that might pose obstacles. The project also requires advanced technology for distributed training, which relies on fast interconnect systems that do not yet exist at scale. However, Skidanov is confident, citing promising research from DeepMind.
Importance of Decentralized AI
Near Protocol’s decentralized approach aims to address significant privacy concerns associated with centralized AI. By leveraging a decentralized network, Near Protocol intends to prevent potential issues tied to centralized control over AI technologies.
Edward Snowden, a guest speaker at the conference, also emphasized the importance of decentralized AI. He warned that centralized AI could lead to widespread surveillance if controlled by a single entity, impacting freedoms on a global scale.
Snowden advocated for an AI system that aligns with Web3’s decentralized principles. This alignment, he argued, is essential to preserving privacy and individual autonomy in the AI-driven future.
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