The AI revolution has a massive, often overlooked problem: where to put all the data. Large Language Models and AI agents require petabytes of training data and verifiable proofs of training to ensure they haven't been tampered with. @Walrus š¦/acc is uniquely positioned to become the primary data layer for the AI era. Because it is optimized for "large binary objects" (blobs), it can handle the massive datasets that would break a traditional blockchain.
Platforms like OpenGradient are already using #Walrus to store over a terabyte of AI datasets for model training. The $WAL token plays a critical role here because it allows for the "tokenization" of storage capacity. AI companies can prepay for storage, ensuring their models remain accessible and verifiable for years without worrying about centralized service providers hiking prices or censoring their content. This is "data sovereignty" in its purest form.
Furthermore, the programmability of @@Walrus š¦/acc allows AI agents to interact with data on-chain. An AI agent running on Sui can trigger a storage request, verify the availability of a specific dataset, and pay for the bandwidth using $WAL Lāall without human intervention. This creates a "machine-to-machine" economy where data is the most valuable commodity. As the demand for transparent and decentralized AI grows, the role of @@Walrus š¦/acc as the trusted storage vault for these models will only become more vital to the global tech ecosystem.#walrus