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Explore the critical role of context in AI systems through this 34-minute conference presentation from a Real-Time Analytics and AI at Scale Meetup in NYC. Discover why most AI systems today struggle with stateless environments and limited prompt windows, and learn how to design scalable, long-term memory solutions for AI applications. Examine real-world architectures and use cases that demonstrate how TiDB's hybrid transactional and analytical engine enables persistent, queryable, versioned, and multi-modal memory systems. Gain insights into moving beyond traditional prompt-based approaches to create AI systems where context becomes the foundation rather than just a feature, with practical examples of implementation strategies for building robust, context-aware AI applications.
