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Topic: AI System Architecture

AI System Architecture involves the architectural considerations and challenges involved in building AI systems, including handling diverse data, ensuring privacy and confidentiality, and combining different machine learning techniques.

More on: AI System Architecture

The podcast episodes provided discuss various aspects of AI system architecture, including the challenges and design decisions involved in building AI applications for specific domains like finance and search.

For example, the episode How AI is eating Finance - with Mike Conover of Brightwave explores the architectural considerations and challenges in developing an AI system for financial analysis, such as handling temporal and structured data, ensuring privacy, and combining different machine learning techniques.

The episode Mamba & Jamba delves into the architectural design of large language models, highlighting the importance of task-specific models, reliable and trustworthy AI systems, and the need for AI systems to truly understand what they are processing for enterprise adoption.

The episode Improving search with RAG architecture with Pinecone CEO Edo Liberty discusses the architectural considerations for AI systems, such as the separation of reasoning and knowledge, and the potential benefits of optimizing subsystems for specific roles.

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