Sometimes the pieces don't fit together, resulting in clunky responses that don't effectively address the user's query.
Solution : Fine-tuning the AI model using supervised learning can help ensure that the generated content better matches the retrieved data. Adding layers of context or employing post-processing techniques can also smooth out mismatches and lead to more consistent and relevant responses.
Concerns about data privacy
With the increasing use of sensitive data in GDR systems, there is poland whatsapp number data concern about the potential for data breaches or inappropriate handling of data, especially when personal or confidential information is involved.
**Solution Implement strong data protection measures such as encryption, anonymization of sensitive data, and regular audits to ensure compliance with privacy laws such as GDPR. By safeguarding user data, organizations can minimize privacy risks and build trust with their users.
High costs and scalability
As RAG systems scale, infrastructure costs can quickly skyrocket due to the need for powerful hardware, increased data storage, and greater processing power, making large-scale deployments difficult to sustain.
Solution : Leverage cloud-based platforms that allow for elastic scaling, which helps manage costs more effectively. Additionally, streamlining queries and optimizing retrieval methods can reduce computational requirements, making the system more cost-effective as it grows.