Reinforcement Learning news tracks updates, releases, guides, and real uses for teams. We explain ideas in plain terms and show. steps you can apply. Follow tests, results, and simple tips. Learn trade-offs, quick fixes, and ways to pick tools that fit your needs.
Roku began rolling out a software update that adds Roku AI voice search across its platform. Apple and NVIDIA also delivered notable advances that push on-device and robot learning forward this week. Roku AI voice search expands contextual queries Moreover, Roku is enhancing discovery with AI-powered context. Users can now ask natural questions about movies, […]
NVIDIA Research unveiled three robot learning advances at CoRL 2025, led by Neural Robot Dynamics. The team also introduced Dexplore and VT-Refine, which target autonomous exploration and visuo-tactile policy refinement. Together, these methods report notable gains in sim-to-real transfer and dexterous manipulation. Neural Robot Dynamics explained Neural Robot Dynamics (NeRD) replaces hand-tuned simulators with a […]
NVIDIA signaled a busy week for AI research and tooling. The ProRL v2 release anchors a slate of updates across learning systems. New robotics methods and data science features arrived alongside it. ProRL v2 release extends LLM training Moreover, NVIDIA Research introduced ProRL v2, a prolonged reinforcement learning method for language models. The approach tests […]
NVIDIA released an early developer preview of Isaac Lab 2.3, bringing whole-body control, broader teleoperation, and faster policy evaluation. The update advances sim-first robot learning and targets safer, cheaper iteration before deployment. Teams gain new data collection options and better training stability. Isaac Lab 2.3 highlights Moreover, The Isaac Lab 2.3 preview adds advanced whole-body […]
ProRL v2 LLM training delivered sustained improvements in math, code, and reasoning, according to a new release from NVIDIA Research. The prolonged reinforcement learning approach continues to boost performance beyond typical schedules, addressing the question of whether large language models plateau under extended RL. The team reports robust gains after thousands of additional RL steps. […]
