Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
Hardware fragmentation remains a persistent bottleneck for deep learning engineers seeking consistent performance.
A quadruped robot uses deep reinforcement learning to master walking on varied terrains, demonstrating energy-efficient and ...
AZoSensors on MSN
Energy-aware protocol cuts power use in green IoT networks
Researchers introduce the EAVM protocol, achieving 17 % lower energy use and 20 % longer network lifetime in IoT systems with advanced virtualization techniques.
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