Model training is the process of teaching an artificial intelligence model to perform a specific task by exposing it to large datasets. During training, the model adjusts its internal parameters to identify patterns and make accurate predictions or classifications. This iterative procedure is fundamental to developing effective AI systems.
Context
In the context of digital assets and Web3, decentralized model training is gaining traction as a method to distribute computational load and enhance data privacy. Projects aim to allow participants to contribute computing resources for training AI models, often incentivized with tokens. This approach addresses the high computational costs and data centralization issues associated with traditional AI development, potentially leading to more robust and community-governed AI systems.
Gonka's launch of a high-efficiency decentralized AI compute network democratizes access, establishing a permissionless alternative to centralized cloud monopolies.
We use cookies to personalize content and marketing, and to analyze our traffic. This helps us maintain the quality of our free resources. manage your preferences below.
Detailed Cookie Preferences
This helps support our free resources through personalized marketing efforts and promotions.
Analytics cookies help us understand how visitors interact with our website, improving user experience and website performance.
Personalization cookies enable us to customize the content and features of our site based on your interactions, offering a more tailored experience.
