Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025)

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
EurekAlert!

A federated anti-forgetting representation method based on hybrid model architecture and gradient truncation

Anti-forgetting representation learning method reduces the weight aggregation interference on model memory and augments the ...
Morning Overview on MSN

Different AI models are converging on how they encode reality

Artificial intelligence systems that look nothing alike on the surface are starting to behave as if they share a common ...
VentureBeat

Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...