Next morning it knows nothing. The "memory" features in mainstream agents are context-window summarization - fragile, lossy, gone after compaction. The third-party fix is a cloud memory layer: mem0, ...

Abstract: Automatically parsing SQL queries from natural languages can help non-professionals access databases and improve the efficiency of information utilization. It is a long-term research issue ...

LLMFS gives LLMs and AI agents persistent, searchable, structured memory — organized like a filesystem. Instead of losing context when a conversation grows past the token limit, agents offload ...

AgentFS is a filesystem explicitly designed for AI agents. Just as traditional filesystems provide file and directory abstractions for applications, AgentFS provides the storage abstractions that AI ...

With agentic AI, the database must evolve from a passive ledger to an active reasoning engine that informs, guides, and enables autonomous action. For decades, the database has been the silent partner ...

Who needs rewrites? This metadata-powered architecture fuses AI and ETL so smoothly, it turns pipelines into self-evolving engines of insight. In the fast-evolving landscape of enterprise data ...

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