Computational models predict neural activity for re-establishing connectivity after stroke or injury

Researchers at The Hong Kong University of Science and Technology (HKUST) School of Engineering have developed a novel ...

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!

Reinforcement learning world models for catalyst surface reconstruction: state-of-the-art review

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 ...
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New look at dopamine signaling suggests neuroscientists' model of reinforcement learning may need to be revised

Dopamine is a powerful signal in the brain, influencing our moods, motivations, movements, and more. The neurotransmitter is crucial for reward-based learning, a function that may be disrupted in a ...
EurekAlert!

Offline model-based reinforcement learning with causal structured world models

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 ...
InfoQ

Google Introduces TranslateGemma Open Models for Multilingual Translation

Google has released TranslateGemma, a set of open translation models based on the Gemma 3 architecture, offering 4B, 12B, and ...
SiliconANGLE

AWS simplifies AI agent customization with automated reinforcement learning

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 ...
VentureBeat

Self-improving language models are becoming reality with MIT's updated SEAL technique

Researchers at the Massachusetts Institute of Technology (MIT) are gaining renewed attention for developing and open sourcing a technique that allows large language models (LLMs) — like those ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...