Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
What if the very techniques we rely on to make AI smarter are actually holding it back? A new study has sent shockwaves through the AI community by challenging the long-held belief that reinforcement ...
A quadruped robot uses deep reinforcement learning to master walking on varied terrains, demonstrating energy-efficient and ...
Among those interviewed, one RL environment founder said, “I’ve seen $200 to $2,000 mostly. $20k per task would be rare but ...
Whether you like theoretical study or want to get your hands dirty, plenty of reinforcement learning resources are out there. When I was in graduate school in the 1990s, one of my favorite classes was ...
DeepSeek-R1's release last Monday has sent shockwaves through the AI community, disrupting assumptions about what’s required to achieve cutting-edge AI performance. Matching OpenAI’s o1 at just 3%-5% ...
In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...