Federated learning: The killer use case for generative AI [Video]

As enterprises struggle to balance AI capabilities against data privacy concerns, federated learning provides the best of both worlds.

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Let’s imagine a fictional company, Global Retail Corporation, a multinational retail chain struggling with its initial approach to AI integration. They built custom generative AI applications on their cloud provider using OpenAI’s APIs for broader analysis, providing access to their LLMs (large language models) and ChatGPT to get more strategic and valuable answers to their business questions. The process was costly and complex, and it delivered suboptimal results. That all changed when they adopted federated learning.

The strategy of federation in AI deployments

Federated learning is emerging as a game-changing approach for enterprises looking to leverage the power of LLMs while maintaining data privacy and security. Rather than moving sensitive data to LLM providers or building isolated small language models (SLMs), federated learning enables organizations to train LLMs using their private data where it …