Kioxia has updated its AiSAQ software, a vector search library, enhancing organizational flexibility with Retrieval-Augmented Generation (RAG) systems. The new version allows organizations to balance search performance with SSD capacity for vectors. This trade-off enables refined configurations tailored to specific workloads. Kioxia's approach utilizes SSDs to overcome DRAM limitations, allowing for larger vector databases. As a result, organizations can keep their AI models updated without incurring high retraining costs while enjoying broader applicability beyond just RAG systems.
Kioxia's AiSAQ software update enables organizations to balance search performance and vector storage, enhancing the flexibility of their Retrieval-Augmented Generation (RAG) systems.
By leveraging SSDs, Kioxia allows for the creation of larger vector databases that were previously limited by DRAM, improving the scalability of RAG systems.
The new version of AiSAQ facilitates tailored configurations for different workloads, emphasizing that higher search performance results in reduced SSD capacity for vector storage.
This update is significant as it supports keeping AI models updated with customizable information, thus avoiding the high costs associated with retraining LLMs.
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