LLM-based agents – whether a single “assistant” or a team of collaborating bots – require careful evaluation across many dimensions. These systems not only need to complete tasks, but also manage t...
Large language models (LLMs) have revolutionized autonomous agents by equipping them with advanced reasoning, planning, and communication capabilities. While single-agent systems have demonstrated ...
The past year has seen a strategic shift in AI systems: instead of solely scaling up model parameters, the industry has pivoted toward tool-augmented AI systems that extend capabilities through ext...
A comprehensive guide to building cooperative AI agent systems that work together effectively in production environments
Agentic AI represents the next frontier in AI - autonomous systems that can reason, plan, and act to achieve specific goals. As LLMs have advanced, a new ecosystem of frameworks has emerged to tran...
As an AI researcher, I’m always seeking fresh perspectives on how we can advance our understanding of intelligence and, ultimately, replicate it in machines. One of the most thought-provoking books...
Memory: The Key to Coherent, Long‑Lived LLM Agents Large language models (LLMs) have impressed us with fluent text generation, but they traditionally operate as stateless systems. Once an interact...
The rise of Transformers has revolutionized the landscape of natural language processing (NLP) and other sequence modeling tasks. Yet, their scalability limitations, particularly with long sequence...
In an era where documents come packed with complex visual elements like tables, charts, and intricate layouts, document retrieval has become more challenging than ever. While modern retrieval syste...
In the world of Information Retrieval (IR), the race for both effectiveness and efficiency has never been more crucial. With vast datasets and real-time search requirements, models must not only de...