If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...

The American Association of Clinical Endocrinology (AACE) has released the 2026 update to its consensus statement algorithm for the management of adults with type 2 diabetes (T2D). The statement was ...

All results from 3 seeds × 18 test instances = 54 evaluation points. BO static outperforms PPO on small instances, but PPO overtakes at 500-variable scale. learned-control-layers/ ├── src/ │ ├── ...

Many enterprise RAG pipelines handle one type of search well and fail silently on the rest. Databricks on March 4 released a new agent called KARL, or Knowledge Agents via Reinforcement Learning, that ...

ABSTRACT: Oracle-based quantum algorithms cannot use deep loops because quantum states exist only as mathematical amplitudes in Hilbert space with no physical substrate. Critically, quantum wave ...

Agent Lightning is an agent optimization framework that enables agents to learn from their experiences through reinforcement learning and other methods. By treating agents as first-class citizens, ...

Hi, I find that when doing full parameter finetuning (FFT) for RL training in verl often leads to suboptimal performance, especially when using learning rate=1e-6 which are widely used in the recent ...

This article was co-authored with Emma Myer, a student at Washington and Lee University who studies Cognitive/Behavioral Science and Strategic Communication. In today’s digital age, social media has ...

In reinforcement learning (RL), an agent learns to achieve its goal by interacting with its environment and learning from feedback about its successes and failures. This feedback is typically encoded ...

Abstract: Interest in applying Reinforcement Learning (RL) to Autonomous Vehicles (AVs) is experiencing a rapid and substantial expansion. Proximal Policy Optimization (PPO), a well-known RL algorithm ...