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Hugging Face Releases Smol2Operator: A Fully Open-Source Pipeline to Train a 2.2B VLM into an Agentic GUI Coder
ByRicardoHugging Face (HF) has launched Smol2Operator, a reproducible, end-to-end recipe that turns a small vision-language mannequin (VLM) with no prior UI grounding into a GUI-operating, tool-using agent. The launch covers knowledge transformation utilities, coaching scripts, remodeled datasets, and the ensuing 2.2B-parameter mannequin checkpoint—positioned as a full blueprint for constructing GUI brokers from scratch somewhat than…
A Code Implementation for Designing Intelligent Multi-Agent Workflows with the BeeAI Framework
ByRicardoBeeAI FrameworkIn this tutorial, we explore the power and flexibility of the beeai-framework by building a fully functional multi-agent system from the ground up. We walk through the essential components, custom agents, tools, memory management, and event monitoring, to show how BeeAI simplifies the development of intelligent, cooperative agents. Along the way, we demonstrate how…
A Coding Guide to Build Intelligent Multi-Agent Systems with the PEER Pattern
ByRicardoIn this tutorial, we explore a powerful multi-agent system built around the PEER pattern: Plan, Execute, Express, and Review. We run the entire workflow in Google Colab/Notebook, integrating agents with specialized roles and leveraging Google’s Gemini 1.5 Flash model via a free API key. As we walk through the system, we observe how each agent…
Scaling Global Trade with AI-Powered Tools for SMBs – with Kuo Zhang of Alibaba.com
ByRicardoSMBs are overwhelmed by multi-step operational work that drains time and headcount. Global trade processes remain slow, fragmented, and opaque. For all the focus on large enterprises in AI adoption, World Trade Organization working group documentation notes that SMBs make up nearly 90–95% of all global businesses and account for 60% of worldwide employment. Other…
Native RAG vs. Agentic RAG: Which Approach Advances Enterprise AI Decision-Making?
ByRicardoRetrieval-Augmented Era (RAG) has emerged as a cornerstone method for enhancing Massive Language Fashions (LLMs) with real-time, domain-specific data. However the panorama is quickly shifting—at this time, the commonest implementations are “Native RAG” pipelines, and a brand new paradigm referred to as “Agentic RAG” is redefining what’s potential in AI-powered info synthesis and determination help….
How to Build an Agentic Deep Reinforcement Learning System with Curriculum Progression, Adaptive Exploration, and Meta-Level UCB Planning
ByRicardoIn this tutorial, we construct an superior agentic Deep Reinforcement Learning system that guides an agent to study not solely actions inside an surroundings but in addition how to select its personal coaching methods. We design a Dueling Double DQN learner, introduce a curriculum with rising problem, and combine a number of exploration modes that…
