From the course: LLMs for Enterprise: Technical Protocols, Considerations, and Data Privacy
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Understanding LLM concerns in enterprise
From the course: LLMs for Enterprise: Technical Protocols, Considerations, and Data Privacy
Understanding LLM concerns in enterprise
- Using large language models in your personal life and an enterprise environment is a little different. Access is often restricted to LMS for three main reasons, data concerns, cost, and risk management. When large language models first came out, it was often unclear how data sent to them would be used. Since then, many LLM providers have added clarity to their agreements and have explicitly mentioned that they do not train on data from corporate and API plans. Even with this assurance, many companies are hesitant. Data is often considered to be the largest moat, and data is invaluable in the AI space. If corporate data is leaked or shared, it could have billion-dollar implications. As a result, many companies are unwilling to take such a risk against potential productivity gains. Many LM providers explicitly mention to avoid personal or sensitive data being entered into a prompt. The second reason is cost. If companies enable LLMs, they may still restrict their usage. Companies are…
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