Data enhances foundational LLMs (e.g. GPT-4, Mistral Large and Llama 2) for context-aware outputs. In this session, we cover using unstructured, multi-modal data (e.g. PDFs, images or videos) in retrieval augmented generation (RAG) systems. Learn about how cloud object storage can be an ideal file system for Andrej Karpathy's LLM-OS concept including the transformation and use of domain-specific data, storing user context and much more.
Explain why domain-specific data and the RAG pattern is so important to building customized AI applications for different industries and domains.
Understand the LLM OS concept including the notion of a filesystem for storing domain-specific data, user context, etc. and why cloud object storage is an ideal storage system for this filesystem.
Use cloud object storage in conjunction with a vector database to build sample RAG applications.
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As Machine Learning continues to forge its way into diverse industries and applications, optimizing computational resources, particularly memory, has become a critical aspect of effective model dep
It is well known that storage sensor data on storage systems can detect abnormal symptoms that can lead to failures.
SNIA Developer Conference
September 16-18, 2024
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