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

Researchers at the University of Science and Technology of China have developed a new reinforcement learning (RL) framework that helps train large language models (LLMs) for complex agentic tasks ...

Deep reinforcement learning is one of the most interesting branches ofartificial intelligence. It is behind some of the most remarkable achievements of the AI community, including beating human ...

The last decade of tech was to a large part defined by the advent of Deep Supervised Learning (DL). The availability of cheap data at scale, computational power, and researcher interest have made it ...

This form of reinforcement learning was also shown to correct for control scenarios like irregular meal timing and compression errors. Offline reinforcement learning (RL) in hybrid closed-loop systems ...

Multi-impulse orbital rendezvous is a classical spacecraft trajectory optimization problem, which has been widely studied for a long time. Numerical optimization methods, deeplearning (DL) methods, ...