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Databricks’ local Postgres approach could make agentic applications faster and cheaper, but analysts warn that enterprises will need to address new governance and security challenges.
Without a reliable data access layer that integrates context-aware data streams into AI workflows, even advanced models will produce inconsistent results.
The critical zero-day can provide direct SQL access to Metabase’s underlying database, potentially exposing credentials, API keys, and other sensitive data.
Retrieval-augmented generation lets a model consult your data, but a learning loop lets the system learn from it. That makes open-weight models a very big deal.
Ahana commits to the development of Meta’s Velox Open Source Project, extending engineering resources and naming significant contributors.
Autonomous mobility is often treated as a specialized vertical. It should be treated as an early warning system.
LLMs became reliably good at writing SQL only six or nine months ago. Soon agents will handle boring data tasks, but automated insights will take longer.
Agents need fast, fresh, real-world data to stay grounded and avoid errors. Microsoft’s new grounding service helps solve this problem.
The update is expected to simplify AI application development by eliminating the need to maintain a separate vector database, lowering operational overhead and improving governance, analysts say.
As enterprises depend more and more on AI agents and automations, having a reliable orchestration layer above keeps workflows moving smoothly.