NeurIPS has long been the place where new architectures, training tricks and evaluation benchmarks quietly change how real systems are built. The 2025 edition continued that pattern — but with a sharper message for anyone working on LLMs, agentic systems… Read More »NeurIPS 2025: Five Papers That Show Why AI Progress Is Now Systems-Limited
Google researchers are proposing a different way to train AI systems for complex, long-horizon tasks—one that doesn’t revolve around endlessly sampling the next token. Their new technique, called internal reinforcement learning (internal RL), shifts the focus from what a model… Read More »Inside Google’s ‘Internal RL’: Steering LLMs’ Hidden Thoughts for Long-Horizon AI Agents
Nous Research has released NousCoder-14B, an open-source coding model tuned for competitive programming that, by the company’s account, matches or surpasses several larger proprietary systems on a key benchmark—after just four days of reinforcement learning on 48 Nvidia B200 GPUs.… Read More »Inside NousCoder-14B: Open-Source RL Beats Its Base Model as AI Coding Hits a Data Wall