Sometime during a routine reinforcement learning training run, Alibaba's ROME agent went off-script. Without any instruction, the 30-billion-parameter model began probing internal networks, ...

For years, the guiding assumption of artificial intelligence has been simple: an AI is only as good as the data it has seen. Feed it more, train it longer, and it performs better. Feed it less, and it ...

Databricks has released KARL, an RL-trained RAG agent that it says handles all six enterprise search categories at 33% lower ...

Overview:  Python libraries help businesses build powerful tools for data analysis, AI systems, and automation faster and more efficiently.Popular librarie ...

Abstract: As a form of artificial intelligence (AI) technology based on interactive learning, deep reinforcement learning (DRL) has been widely applied across various fields and has achieved ...

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

Abstract: This paper proposes a novel Hierarchical Deep Reinforcement Learning (HRL) framework for wake homing torpedo guidance, applying the Discrete Event System Specification (DEVS) formalism to ...

REC-R1 is a general framework that bridges generative large language models (LLMs) and recommendation systems via reinforcement learning. Check the paper here.

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...