Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
MemRL separates stable reasoning from dynamic memory, giving AI agents continual learning abilities without model fine-tuning ...
Reinforcement learning algorithms help AI reach goals by rewarding desirable actions. Real-world applications, like healthcare, can benefit from reinforcement learning's adaptability. Initial setup ...
Researchers in the US developed bipedal robots with a new design, the HybridLeg platform, ...
Using a bunch of carrots to train a pony and rider. (Photo by: Education Images/Universal Images Group via Getty Images) Andrew Barto and Richard Sutton are the recipients of the Turing Award for ...
The age of truly autonomous artificial intelligence, where systems proactively learn, adapt and optimize amid real-world complexities instead of simply reacting, has been a long-held aspiration. Now, ...
Among those interviewed, one RL environment founder said, “I’ve seen $200 to $2,000 mostly. $20k per task would be rare but ...
Robotics is entering a new phase where general-purpose learning matters as much as mechanical design. Instead of programming ...
Someone looking to book a vacation online today might have very different preferences than they did before the COVID-19 pandemic. Instead of flying to an exotic beach, they might feel more comfortable ...
David Silver is responsible for several eye-catching demonstrations of artificial intelligence in recent years, working on advances that helped revive interest in the field after the last great AI ...