Agentic AI

Introduction Qwen has unveiled Qwen3-Coder-480B-A35B-Instruct, their most powerful open agentic code model released to date. With a distinctive Mixture-of-Experts (MoE) architecture and comprehensive agentic coding capabilities, Qwen3-Coder not only sets a new standard for open-source coding models but also redefines what’s possible for large-scale, autonomous developer assistance. Model Architecture and Specifications Key Features Model Size: 480 billion…

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…

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…

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…