Databricks built a RAG agent it says can handle every kind of enterprise search

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.
Semiconductor Engineering

Leveraging Multi-Agent RL for Microprocessor Design Space (Harvard, Google)

A new technical paper titled “Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration” was published by researchers at Harvard University and Google research groups.
WinBuzzer

Databricks KARL Agent Tackles All Enterprise Search Types via RL

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.

From Research To Reality: How RL Environments Can Unlock The Next Wave Of AI Agents

A reinforcement learning environment is a fail-safe digital practice room where an agent can afford to make mistakes and ...