A Fortune 500 retailer cut robot idle time by 15%, replenishment cycles by 12%, and costs by 8% in two months. Most ...
Deep Learning with Yacine on MSN
What are RLVR environments for LLMs? | Policy, rollouts & rubrics explained
A clear breakdown of RLVR environments for LLMs — what they are, how policies and rollouts work, and the role of rubrics in ...
2d
Nous Research's NousCoder-14B is an open-source coding model landing right in the Claude Code moment
B, an open-source AI coding model trained in four days on Nvidia B200 GPUs, publishing its full reinforcement-learning stack as Claude Code hype underscores the accelerating race to automate software ...
In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...
Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
HeteroRL is a novel heterogeneous reinforcement learning framework designed for stable and scalable training of large language models (LLMs) in geographically distributed, resource-heterogeneous ...
Nvidia’s Isaac Lab simulation powers DoorMan, allowing a humanoid to beat human operators in complex loco-manipulation tasks.Haoru Xue et al. NVIDIA researchers have revealed a new robotic learning ...
Greenhouse vegetable production was a complex agricultural system influenced by multiple interrelated environmental and management factors. Its irrigation control was a critical but not singularly ...
Abstract: In essence, reinforcement learning (RL) solves optimal control problem (OCP) by employing a neural network (NN) to fit the optimal policy from state to action. The accuracy of policy ...
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