Mirage News

Reinforcement Learning, Blockchain Boost IoMT Security

Critical concerns regarding the security and privacy of information transmitted within Internet of Medical Things systems have increased greatly ...

Which Machine Learning Models Are Most Used In Crypto Signal Generation?

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...
Unite.AI

The End of Tabula Rasa: How Pre-Trained World Models are Redefining Reinforcement Learning

For a long time, the core idea in reinforcement learning (RL) was that AI agents should learn every new task from scratch, like a blank slate. This "tabula rasa" approach led to amazing achievements, ...

Inside Ring-1T: Ant engineers solve reinforcement learning bottlenecks at trillion scale

Ant Group, an affiliate of Alibaba, released Ring-1T which it says is the first trillion parameter open-source model.
IEEE

Game-Theoretic Constrained Policy Optimization for Safe Reinforcement Learning

Abstract: Safe reinforcement learning (RL) aims to optimize the task performance with safety guarantees. One common modeling scheme to study safe RL problems is the constrained Markov decision process ...
GitHub

Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models

We propose TraceRL, a trajectory-aware reinforcement learning method for diffusion language models, which demonstrates the best performance among RL approaches for DLMs. We also introduce a ...
komonews

Seattle Public Schools LGBTQ+ curriculum and 'opt out' policy draws attention from parents

SEATTLE — A Seattle Public Schools (SPS) policy about teaching students an LGBTQ-inclusive curriculum is gaining attention from local families and making national headlines Friday. The policy in ...
marktechpost

Biomni-R0: New Agentic LLMs Trained End-to-End with Multi-Turn Reinforcement Learning for Expert-Level Intelligence in Biomedical Research

The research introduced a two-phase training process. First, they used supervised fine-tuning (SFT) on high-quality trajectories sampled from Claude-4 Sonnet using rejection sampling, effectively ...
Frontiers

A novel reinforcement learning framework-based path planning algorithm for unmanned surface vehicle

Unmanned surface vehicles (USVs) nowadays have been widely used in ocean observation missions, helping researchers to monitor climate change, collect environmental data, and observe marine ecosystem ...
C&EN

Reinforcement Learning-Based Nonlinear Model Predictive Controller for a Jacketed Reactor: A Machine Learning Concept Validation Using Jetson Orin

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this research work authors have experimentally validated a blend of Machine ...