Large-scale models, in the context of digital assets, typically refer to sophisticated analytical or predictive algorithms that process vast amounts of data. These models are employed for tasks such as market forecasting, risk assessment, fraud detection, or optimizing trading strategies within cryptocurrency markets. Their operation often requires substantial computational resources and extensive datasets.
Context
The application of large-scale models is a growing area of interest in crypto news, particularly regarding their use by institutional investors and quantitative trading firms. Debates often concern the transparency, explainability, and potential for bias in these models, especially when they influence market liquidity or price discovery. Advancements in artificial intelligence and machine learning continue to drive their adoption and refinement.
Artemis CP-SNARK is a modular construction that eliminates the commitment verification bottleneck in zkML, making large-scale, privacy-preserving AI models practical.
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