Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
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% ...
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 ...
Robotics is entering a new phase where general-purpose learning matters as much as mechanical design. Instead of programming ...
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 ...
Researchers from Fudan University and Shanghai AI Laboratory have conducted an in-depth analysis of OpenAI’s o1 and o3 models, shedding light on their advanced reasoning capabilities. These models, ...
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 ...
The Rho-alpha model incorporates sensor modalities such as tactile feedback and is trained with human guidance, says ...
Results that may be inaccessible to you are currently showing.
Hide inaccessible results