My advice to teams deploying real-world AI agents is to build your constraint system before you even start optimizing your ...
A new learning paradigm developed by University College London (UCL) and Huawei Noah’s Ark Lab enables large language model (LLM) agents to dynamically adapt to their environment without fine-tuning ...
The AI industry is obsessed with scale—bigger models, more parameters, higher costs—the assumption being that more always equals better. Today, small language models (SLM) are turning that assumption ...
Researchers at the University of Science and Technology of China have developed a new reinforcement learning (RL) framework that helps train large language models (LLMs) for complex agentic tasks ...
Chief AI Scientist Josh Joseph and BKC Research Coordinator Seán Boddy address the risks that misalignment and loss of control pose to increasingly complex LLM-based agents. Their paper, available ...
Modern computing systems rely heavily on operating-system schedulers to allocate CPU time fairly and efficiently. Yet many of these schedulers operate blindly with respect to the meaning of workloads: ...
Agents could make it easier and cheaper for criminals to hack systems at scale. We need to be ready. Agents are the talk of the AI industry—they’re capable of planning, reasoning, and executing ...
LangGraph has been used to create a multi-agent large language model (LLM) coding framework. This framework is designed to automate various software development tasks, including coding, testing, and ...
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