The Governed Multi-Expert architecture transforms single large language models into dynamic teams of specialized experts using efficient LoRA modules and real-time governance systems.
GPT-5 Codex shows remarkable performance in cybersecurity benchmarks using a pass@12 scoring method, but this approach can lead to unintended side effects like AI hallucinations.
Discover how constrained domains like mathematics, code debugging, and logic puzzles enable efficient testing of reasoning architectures without requiring enormous computational resources.
Many AI systems struggle with providing accurate answers, but Self-RAG introduces reflection tokens that allow models to verify their own responses and reduce hallucinations.
Exploring Self-RAG and other advanced RAG methods that help AI systems self-assess response quality and reduce hallucinations through reflection tokens and real-time validation.
As AI agents evolve from simple chatbots to complex problem-solvers, the underlying reinforcement learning systems must adapt to handle long-horizon tasks, tool usage, and real-world interactions. This post explores the challenges and solutions in scaling RL for agentic AI.
Retrieval Augmented Generation is not always the optimal solution for knowledge tasks, as naive implementations can introduce latency, compute overhead, and even cause external hallucinations.