Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
Robotics is entering a new phase where general-purpose learning matters as much as mechanical design. Instead of programming ...
Imagine trying to teach a child how to solve a tricky math problem. You might start by showing them examples, guiding them step by step, and encouraging them to think critically about their approach.
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% ...
The Rho-alpha model incorporates sensor modalities such as tactile feedback and is trained with human guidance, says ...
Amazon Web Services Inc. wants to solve the efficiency challenges of artificial intelligence agents and reduce their overall inference demands, and it’s tackling the problem with more advanced model ...
This work presents an AI-based world model framework that simulates atomic-level reconstructions in catalyst surfaces under dynamic conditions. Focusing on AgPd nanoalloys, it leverages Dreamer-style ...
AZoLifeSciences on MSN
How the Brain Uses Reinforcement Learning Beyond Just Mean Rewards
What if our brains learned from rewards not just by averaging them but by considering their full range of possibilities? A ...
Among those interviewed, one RL environment founder said, “I’ve seen $200 to $2,000 mostly. $20k per task would be rare but ...
The architecture of FOCUS. Given offline data, FOCUS learns a $p$ value matrix by KCI test and then gets the causal structure by choosing a $p$ threshold. After ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results