How Are Gemini, Claude, and Meta Using Our Data? – Computerworld

Privacy concerns regarding large language models (LLMs) can be addressed without avoiding their use altogether. Experts suggest that organizations can host LLMs on-premises or through secure cloud services like Amazon Bedrock, ensuring that no data retention occurs. In these setups, LLMs act as processors without retaining any information unless explicitly stored. By controlling memory, data storage, and user history, organizations can safely leverage LLMs’ capabilities while minimizing third-party data exposure risks. Zayas from Ironwall warns that users often underestimate the extent to which their data is collected and repurposed, highlighting risks associated with shared models. Ultimately, businesses can unlock LLM value without relying on external services, thereby safeguarding their data against misuse.

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