In this tutorial, we begin by setting up a compact yet capable AI agent that runs smoothly, leveraging Hugging Face transformers. We integrate dialog generation, question‑answering, sentiment analysis, web search stubs, weather look‑ups, and a safe calculator into a single Python class. As we progress, we install only the essential libraries, load lightweight models that respect…
Building effective AI agents means more than just picking a powerful language model. As the Manus project discovered, how you design and manage the “context” – the information the AI processes to make decisions – is paramount. This “context engineering” directly impacts an agent’s speed, cost, reliability, and intelligence. Initially, the choice was clear: leverage…
WrenAI is an open-source Generative Business Intelligence (GenBI) agent developed by Canner, designed to enable seamless, natural-language interaction with structured data. It targets both technical and non-technical teams, providing the tools to query, analyze, and visualize data without writing SQL. All capabilities and integrations are verified against the official documentation and latest releases. Key Capabilities…
Introduction As large language models (LLMs) advance in software engineering tasks—ranging from code generation to bug fixing—performance optimization remains an elusive frontier, especially at the repository level. To bridge this gap, researchers from TikTok and collaborating institutions have introduced SWE-Perf—the first benchmark specifically designed to evaluate the ability of LLMs to optimize code performance in…
Recent developments in LLM agents have largely focused on enhancing capabilities in complex task execution. However, a critical dimension remains underexplored: memory—the capacity of agents to persist, recall, and reason over user-specific information across time. Without persistent memory, most LLM-based agents remain stateless, unable to build context beyond a single prompt, limiting their usefulness in…
A team of researchers from University of Liverpool, Huawei Noah’s Ark Lab, University of Oxford and University College London presents a report explaining Deep Research Agents (DR agents), a new paradigm in autonomous research. These systems are powered by Large Language Models (LLMs) and designed to handle complex, long-horizon tasks that require dynamic reasoning, adaptive…
Table of contents What is an AI Agent? Why AI Agents Matter in 2025 Types of AI Agents Key Components of an AI Agent Leading AI Agent Frameworks in 2025 Practical Use Cases for AI Agents AI Agent vs. Chatbot vs. LLM The Future of Agentic AI Systems FAQs About AI Agents Conclusion What is…
In this tutorial, we build a complete multi-agent research team system using LangGraph and Google’s Gemini API. We utilize role-specific agents, Researcher, Analyst, Writer, and Supervisor, each responsible for a distinct part of the research pipeline. Together, these agents collaboratively gather data, analyze insights, synthesize a report, and coordinate the workflow. We also incorporate features…
Catch up on every session from the AIAI New York with sessions across 3 co-located summit featuring the likes of Meta, Bank of America, Google DeepMind and many more.
At the AI Accelerator Institute Summit in New York, Oren Michels, Co-founder and CEO of Barndoor AI, joined a one-on-one discussion with Alexander Puutio, Professor and Author, to explore a question facing every enterprise experimenting with AI: Why do so many AI pilots stall, and what will it take to unlock real value? Barndoor AI…