Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
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, ...
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 ...
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 ...
Machine learning technique teaches power-generating kites to extract energy from turbulent airflows more effectively, boosting their efficiency ...
Among those interviewed, one RL environment founder said, “I’ve seen $200 to $2,000 mostly. $20k per task would be rare but ...
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 ...
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% ...
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US researchers build fall-safe biped robots to advance real-world reinforcement learning
Researchers in the US developed bipedal robots with a new design, the HybridLeg platform, ...
This article is published by AllBusiness.com, a partner of TIME. What is "Reinforcement Learning"? Reinforcement Learning (RL) is a type of machine learning where a model learns to make decisions by ...
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