Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.
Databricks has released KARL, an RL-trained RAG agent that it says handles all six enterprise search categories at 33% lower cost than frontier models.
When RL is paired with human oversight, teams can shape how systems learn, correct course when context changes, and ensure ...
The latest trends in software development from the Computer Weekly Application Developer Network. Developers are set for acceleration… the new wave of agentic AI services will, in and of themselves, ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...
First author Canyu Chen led a multi-institution research team in developing a scalable approach to training AI agents without sacrificing users’ data privacy.
Multi-agent orchestration makes workflow more inspectable, with clear handoffs and a QA backstop. Breaking the work into discrete steps makes the output easier to audit and fix. A timestamped handoff ...
Qwen3.5 comes in an open-weight and hosted API version, with the company advertising improvements in performance and costs from previous versions. Qwen3.5 supports new agentic capabilities and is ...
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