Many enterprises struggle to locate their data and integrate it with large language models. AI memory should not be seen as a mere context window; it functions like a database requiring strict management similar to transaction logs. Implementing schemas, access controls, and firewalls is crucial to prevent hallucinations or unauthorized data leaks.
When designing your first AI system, prioritize the memory layer—determining what data the AI can access and how it gets updated—before focusing on prompts. Emphasis should be placed on inference, the application of knowledge rather than just model training costs. For enterprises, the true value of AI lies in effectively utilizing governed data, making a retrieval-augmented generation (RAG) pipeline the ideal starting point. By establishing a solid foundation in data memory and inference, businesses can enhance their AI capabilities and unlock significant benefits.
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